From e403872109dcbd1851555808817c4b86e51c31b1 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 18:51:21 +0200
Subject: [PATCH 001/120] ENH: sensors class

---
 rocketpy/sensors/__init__.py |   1 +
 rocketpy/sensors/sensors.py  | 233 +++++++++++++++++++++++++++++++++++
 2 files changed, 234 insertions(+)
 create mode 100644 rocketpy/sensors/__init__.py
 create mode 100644 rocketpy/sensors/sensors.py

diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
new file mode 100644
index 000000000..413a784a8
--- /dev/null
+++ b/rocketpy/sensors/__init__.py
@@ -0,0 +1 @@
+from .sensors import Sensors
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
new file mode 100644
index 000000000..8ba08317b
--- /dev/null
+++ b/rocketpy/sensors/sensors.py
@@ -0,0 +1,233 @@
+from abc import ABC, abstractmethod
+from rocketpy.mathutils.vector_matrix import Matrix, Vector
+import numpy as np
+
+
+class Sensors(ABC):
+    """
+    Abstract class for sensors
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        orientation=(0, 0, 0),
+        measurement_range=np.inf,
+        resolution=0,
+        noise_density=0,
+        random_walk=0,
+        constant_bias=0,
+        operating_temperature=25,
+        temperature_bias=0,
+        temperature_scale_factor=0,
+        cross_axis_sensitivity=0,
+        name="Sensor",
+    ):
+        """
+        Initialize the accelerometer sensor
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor
+        orientation : tuple, list, optional
+            Orientation of the sensor in the rocket. The orientation can be
+            given as:
+            - A list of length 3, where the elements are the Euler angles for
+              the rotation roll (φ), pitch (θ) and yaw (ψ) in radians. The
+              standard rotation sequence is z-y-x (3-2-1) is used, meaning the
+              sensor is first rotated by ψ around the z axis, then by θ around
+              the new y axis and finally by φ around the new x axis.
+            - A list of lists (matrix) of shape 3x3, representing the rotation
+              matrix from the sensor frame to the rocket frame. The sensor frame
+              of reference is defined as to have z axis along the sensor's normal
+              vector pointing upwards, x and y axes perpendicular to the z axis
+              and each other.
+            The rocket frame of reference is defined as to have z axis
+            along the rocket's axis of symmetry pointing upwards, x and y axes
+            perpendicular to the z axis and each other. Default is (0, 0, 0),
+            meaning the sensor is aligned with the rocket's axis of symmetry.
+        measurement_range : float, tuple, optional
+            The measurement range of the sensor in the sensor units. If a float,
+            the same range is applied both for positive and negative values. If
+            a tuple, the first value is the positive range and the second value
+            is the negative range. Default is np.inf.
+        resolution : float, optional
+            The resolution of the sensor in sensor units/LSB. Default is 0,
+            meaning no quantization is applied.
+        noise_density : float, optional
+            The noise density of the sensor in sensor units/√Hz. Sometimes
+            called "white noise drift", "angular random walk" for gyroscopes,
+            "velocity random walk" for the accelerometers or
+            "(rate) noise density". Default is 0, meaning no noise is applied.
+        random_walk : float, optional
+            The random walk of the sensor in sensor units/√Hz. Sometimes called
+            "bias (in)stability" or "bias drift"". Default is 0, meaning no
+            random walk is applied.
+        constant_bias : float, optional
+            The constant bias of the sensor in sensor units. Default is 0,
+            meaning no constant bias is applied.
+        operating_temperature : float, optional
+            The operating temperature of the sensor in degrees Celsius. At 25°C,
+            the temperature bias and scale factor are 0. Default is 25.
+        temperature_bias : float, optional
+            The temperature bias of the sensor in sensor units/°C. Default is 0,
+            meaning no temperature bias is applied.
+        temperature_scale_factor : float, optional
+            The temperature scale factor of the sensor in %/°C. Default is 0,
+            meaning no temperature scale factor is applied.
+        cross_axis_sensitivity : float, optional
+            Skewness of the sensor's axes in percentage. Default is 0, meaning
+            no cross-axis sensitivity is applied.
+        name : str, optional
+            The name of the sensor. Default is "Sensor".
+
+        Returns
+        -------
+        None
+        """
+        self.sampling_rate = sampling_rate
+        self.orientation = orientation
+        self.resolution = resolution
+        self.noise_density = noise_density * Vector([1, 1, 1])
+        self.random_walk = random_walk * Vector([1, 1, 1])
+        self.constant_bias = constant_bias * Vector([1, 1, 1])
+        self.operating_temperature = operating_temperature
+        self.temperature_bias = temperature_bias * Vector([1, 1, 1])
+        self.temperature_scale_factor = temperature_scale_factor * Vector([1, 1, 1])
+        self.cross_axis_sensitivity = cross_axis_sensitivity
+        self.name = name
+        self._random_walk_drift = Vector([0, 0, 0])
+        self.measurement = None
+        self.measured_values = []  # change to data
+
+        # handle measurement range
+        if isinstance(measurement_range, (tuple, list)):
+            if len(measurement_range) != 2:
+                raise ValueError("Invalid measurement range format")
+            self.measurement_range = measurement_range
+        elif isinstance(measurement_range, (int, float)):
+            self.measurement_range = (-measurement_range, measurement_range)
+        else:
+            raise ValueError("Invalid measurement range format")
+
+        # rotation matrix and normal vector
+        if any(isinstance(row, (tuple, list)) for row in orientation):  # matrix
+            self.rotation_matrix = Matrix(orientation)
+        elif len(orientation) == 3:  # euler angles
+            self.rotation_matrix = Matrix.transformation_euler_angles(*orientation)
+        else:
+            raise ValueError("Invalid orientation format")
+        self.normal_vector = Vector(
+            [
+                self.rotation_matrix[0][2],
+                self.rotation_matrix[1][2],
+                self.rotation_matrix[2][2],
+            ]
+        ).unit_vector
+
+        # cross axis sensitivity matrix
+        _cross_axis_matrix = 0.01 * Matrix(
+            [
+                [100, self.cross_axis_sensitivity, self.cross_axis_sensitivity],
+                [self.cross_axis_sensitivity, 100, self.cross_axis_sensitivity],
+                [self.cross_axis_sensitivity, self.cross_axis_sensitivity, 100],
+            ]
+        )
+
+        # compute total rotation matrix given cross axis sensitivity
+        self._total_rotation_matrix = self.rotation_matrix @ _cross_axis_matrix
+
+    def __repr__(self):
+        return f"{self.type} sensor, orientation: {self.orientation}"
+
+    def __call__(self, *args, **kwds):
+        return self.measure(*args, **kwds)
+
+    @abstractmethod
+    def measure(self, *args, **kwargs):
+        pass
+
+    @abstractmethod
+    def export_measured_values(self):
+        pass
+
+    def quantize(self, value):
+        """
+        Quantize the sensor measurement
+
+        Parameters
+        ----------
+        value : float
+            The value to quantize
+
+        Returns
+        -------
+        float
+            The quantized value
+        """
+        x = min(max(value.x, self.measurement_range[0]), self.measurement_range[1])
+        y = min(max(value.y, self.measurement_range[0]), self.measurement_range[1])
+        z = min(max(value.z, self.measurement_range[0]), self.measurement_range[1])
+        if self.resolution != 0:
+            x = round(x / self.resolution) * self.resolution
+            y = round(y / self.resolution) * self.resolution
+            z = round(z / self.resolution) * self.resolution
+        return Vector([x, y, z])
+
+    def apply_noise(self, value):
+        """
+        Add noise to the sensor measurement
+
+        Parameters
+        ----------
+        value : float
+            The value to add noise to
+
+        Returns
+        -------
+        float
+            The value with added noise
+        """
+        # white noise
+        white_noise = (
+            np.random.normal(0, 1) * self.noise_density * self.sampling_rate**0.5
+        )
+
+        # random walk
+        self._random_walk_drift = (
+            self._random_walk_drift
+            + np.random.normal(0, 1) * self.random_walk / self.sampling_rate**0.5
+        )
+
+        # add noise
+        value += white_noise + self._random_walk_drift + self.constant_bias
+
+        return value
+
+    def apply_temperature_drift(self, value):
+        """
+        Apply temperature drift to the sensor measurement
+
+        Parameters
+        ----------
+        value : float
+            The value to apply temperature drift to
+
+        Returns
+        -------
+        float
+            The value with applied temperature drift
+        """
+        # temperature drift
+        value += (self.operating_temperature - 25) * self.temperature_bias
+        # temperature scale factor
+        scale_factor = (
+            Vector([1, 1, 1])
+            + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
+        )
+        value.x *= scale_factor.x
+        value.y *= scale_factor.y
+        value.z *= scale_factor.z
+
+        return value

From 6cd3598fd8827523f472c0921123cdc418ad3011 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:09:52 +0200
Subject: [PATCH 002/120] ENH: add accelerometer and gyroscope classes

---
 rocketpy/__init__.py              |   1 +
 rocketpy/sensors/__init__.py      |   2 +
 rocketpy/sensors/accelerometer.py | 184 ++++++++++++++++++++++++++
 rocketpy/sensors/gyroscope.py     | 212 ++++++++++++++++++++++++++++++
 4 files changed, 399 insertions(+)
 create mode 100644 rocketpy/sensors/accelerometer.py
 create mode 100644 rocketpy/sensors/gyroscope.py

diff --git a/rocketpy/__init__.py b/rocketpy/__init__.py
index 10404b619..fe55dda41 100644
--- a/rocketpy/__init__.py
+++ b/rocketpy/__init__.py
@@ -37,4 +37,5 @@
     Tail,
     TrapezoidalFins,
 )
+from .sensors import Accelerometer, Gyroscope, Sensors
 from .simulation import Flight
diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 413a784a8..044deec43 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1 +1,3 @@
 from .sensors import Sensors
+from .gyroscope import Gyroscope
+from .accelerometer import Accelerometer
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
new file mode 100644
index 000000000..1774fde76
--- /dev/null
+++ b/rocketpy/sensors/accelerometer.py
@@ -0,0 +1,184 @@
+import numpy as np
+from ..mathutils.vector_matrix import Matrix, Vector
+from ..sensors.sensors import Sensors
+from ..prints.sensors_prints import _AccelerometerPrints
+
+
+class Accelerometer(Sensors):
+    """
+    Class for the accelerometer sensor
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        orientation=(0, 0, 0),
+        measurement_range=np.inf,
+        resolution=0,
+        noise_density=0,
+        random_walk=0,
+        constant_bias=0,
+        operating_temperature=25,
+        temperature_bias=0,
+        temperature_scale_factor=0,
+        cross_axis_sensitivity=0,
+        consider_gravity=False,
+        name="Accelerometer",
+    ):
+        """
+        Initialize the accelerometer sensor
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor
+        orientation : tuple, list, optional
+            Orientation of the sensor in the rocket. The orientation can be
+            given as:
+            - A list of length 3, where the elements are the Euler angles for
+              the rotation roll (φ), pitch (θ) and yaw (ψ) in radians. The
+              standard rotation sequence is z-y-x (3-2-1) is used, meaning the
+              sensor is first rotated by ψ around the z axis, then by θ around
+              the new y axis and finally by φ around the new x axis.
+            - A list of lists (matrix) of shape 3x3, representing the rotation
+              matrix from the sensor frame to the rocket frame. The sensor frame
+              of reference is defined as to have z axis along the sensor's normal
+              vector pointing upwards, x and y axes perpendicular to the z axis
+              and each other.
+            The rocket frame of reference is defined as to have z axis
+            along the rocket's axis of symmetry pointing upwards, x and y axes
+            perpendicular to the z axis and each other. A rotation around the x
+            axis configures a pitch, around the y axis a yaw and around z axis a
+            roll. Default is (0, 0, 0), meaning the sensor is aligned with all
+            of the rocket's axis.
+        measurement_range : float, tuple, optional
+            The measurement range of the sensor in the m/s^2. If a float, the
+            same range is applied both for positive and negative values. If a
+            tuple, the first value is the positive range and the second value is
+            the negative range. Default is np.inf.
+        resolution : float, optional
+            The resolution of the sensor in m/s^2/LSB. Default is 0, meaning no
+            quantization is applied.
+        noise_density : float, optional
+            The noise density of the sensor in m/s^2/√Hz. Sometimes called
+            "white noise drift", "angular random walk" for gyroscopes, "velocity
+            random walk" for the accelerometers or "(rate) noise density".
+            Default is 0, meaning no noise is applied.
+        random_walk : float, optional
+            The random walk of the sensor in m/s^2/√Hz. Sometimes called "bias
+            (in)stability" or "bias drift"". Default is 0, meaning no random
+            walk is applied.
+        constant_bias : float, optional
+            The constant bias of the sensor in m/s^2. Default is 0, meaning no
+            constant bias is applied.
+        operating_temperature : float, optional
+            The operating temperature of the sensor in degrees Celsius. At 25°C,
+            the temperature bias and scale factor are 0. Default is 25.
+        temperature_bias : float, optional
+            The temperature bias of the sensor in m/s^2/°C. Default is 0,
+            meaning no temperature bias is applied.
+        temperature_scale_factor : float, optional
+            The temperature scale factor of the sensor in %/°C. Default is 0,
+            meaning no temperature scale factor is applied.
+        cross_axis_sensitivity : float, optional
+            Skewness of the sensor's axes in percentage. Default is 0, meaning
+            no cross-axis sensitivity is applied.
+        consider_gravity : bool, optional
+            If True, the sensor will consider the effect of gravity on the
+            acceleration. Default is False.
+        name : str, optional
+            The name of the sensor. Default is "Accelerometer".
+
+        Returns
+        -------
+        None
+        """
+        self.type = "Accelerometer"
+        self.consider_gravity = consider_gravity
+        self.prints = _AccelerometerPrints(self)
+        super().__init__(
+            sampling_rate,
+            orientation,
+            measurement_range=measurement_range,
+            resolution=resolution,
+            noise_density=noise_density,
+            random_walk=random_walk,
+            constant_bias=constant_bias,
+            operating_temperature=operating_temperature,
+            temperature_bias=temperature_bias,
+            temperature_scale_factor=temperature_scale_factor,
+            cross_axis_sensitivity=cross_axis_sensitivity,
+            name=name,
+        )
+
+    def measure(self, t, u, u_dot, relative_position, gravity, *args):
+        """
+        Measure the acceleration of the rocket
+        """
+        # Linear acceleration of rocket cdm in inertial frame
+        gravity = (
+            Vector([0, 0, -gravity]) if self.consider_gravity else Vector([0, 0, 0])
+        )
+        a_I = Vector(u_dot[3:6]) + gravity
+
+        # Vector from rocket cdm to sensor in rocket frame
+        r = relative_position
+
+        # Angular velocity and accel of rocket
+        omega = Vector(u[10:13])
+        omega_dot = Vector(u_dot[10:13])
+
+        # Measured acceleration at sensor position in inertial frame
+        A = (
+            a_I
+            + Vector.cross(omega_dot, r)
+            + Vector.cross(omega, Vector.cross(omega, r))
+        )
+        # Transform to sensor frame
+        inertial_to_sensor = self._total_rotation_matrix @ Matrix.transformation(
+            u[6:10]
+        )
+        A = inertial_to_sensor @ A
+
+        # Apply noise + bias and quatize
+        A = self.apply_noise(A)
+        A = self.apply_temperature_drift(A)
+        A = self.quantize(A)
+
+        self.measurement = tuple([*A])
+        self.measured_values.append((t, *A))
+
+    def export_measured_values(self, filename, format="csv"):
+        """
+        Export the measured values to a file
+
+        Parameters
+        ----------
+        filename : str
+            Name of the file to export the values to
+        format : str
+            Format of the file to export the values to. Options are "csv" and
+            "json". Default is "csv".
+
+        Returns
+        -------
+        None
+        """
+        if format == "csv":
+            with open(filename, "w") as f:
+                f.write("t,ax,ay,az\n")
+                for t, ax, ay, az in self.measured_values:
+                    f.write(f"{t},{ax},{ay},{az}\n")
+        elif format == "json":
+            import json
+
+            data = {"t": [], "ax": [], "ay": [], "az": []}
+            for t, ax, ay, az in self.measured_values:
+                data["t"].append(t)
+                data["ax"].append(ax)
+                data["ay"].append(ay)
+                data["az"].append(az)
+            with open(filename, "w") as f:
+                json.dump(data, f)
+        else:
+            raise ValueError("Invalid format")
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
new file mode 100644
index 000000000..21543e99c
--- /dev/null
+++ b/rocketpy/sensors/gyroscope.py
@@ -0,0 +1,212 @@
+import numpy as np
+from ..mathutils.vector_matrix import Matrix, Vector
+from ..sensors.sensors import Sensors
+from ..prints.sensors_prints import _GyroscopePrints
+
+
+class Gyroscope(Sensors):
+    """
+    Class for the gyroscope sensor
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        orientation=(0, 0, 0),
+        measurement_range=np.inf,
+        resolution=0,
+        noise_density=0,
+        random_walk=0,
+        constant_bias=0,
+        operating_temperature=25,
+        temperature_bias=0,
+        temperature_scale_factor=0,
+        cross_axis_sensitivity=0,
+        acceleration_sensitivity=0,
+        name="Gyroscope",
+    ):
+        """
+        Initialize the gyroscope sensor
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor
+        orientation : tuple, list, optional
+            Orientation of the sensor in the rocket. The orientation can be
+            given as:
+            - A list of length 3, where the elements are the Euler angles for
+              the rotation roll (φ), pitch (θ) and yaw (ψ) in radians. The
+              standard rotation sequence is z-y-x (3-2-1) is used, meaning the
+              sensor is first rotated by ψ around the z axis, then by θ around
+              the new y axis and finally by φ around the new x axis.
+            - A list of lists (matrix) of shape 3x3, representing the rotation
+              matrix from the sensor frame to the rocket frame. The sensor frame
+              of reference is defined as to have z axis along the sensor's normal
+              vector pointing upwards, x and y axes perpendicular to the z axis
+              and each other.
+            The rocket frame of reference is defined as to have z axis
+            along the rocket's axis of symmetry pointing upwards, x and y axes
+            perpendicular to the z axis and each other. Default is (0, 0, 0),
+            meaning the sensor is aligned with the rocket's axis of symmetry.
+        measurement_range : float, tuple, optional
+            The measurement range of the sensor in the rad/s. If a float, the
+            same range is applied both for positive and negative values. If a
+            tuple, the first value is the positive range and the second value is
+            the negative range. Default is np.inf.
+        resolution : float, optional
+            The resolution of the sensor in rad/s/LSB. Default is 0, meaning no
+            quantization is applied.
+        noise_density : float, optional
+            The noise density of the sensor in rad/s/√Hz. Sometimes called
+            "white noise drift", "angular random walk" for gyroscopes, "velocity
+            random walk" for the accelerometers or "(rate) noise density".
+            Default is 0, meaning no noise is applied.
+        random_walk : float, optional
+            The random walk of the sensor in rad/s/√Hz. Sometimes called "bias
+            (in)stability" or "bias drift"". Default is 0, meaning no random
+            walk is applied.
+        constant_bias : float, optional
+            The constant bias of the sensor in rad/s. Default is 0, meaning no
+            constant bias is applied.
+        operating_temperature : float, optional
+            The operating temperature of the sensor in degrees Celsius. At 25°C,
+            the temperature bias and scale factor are 0. Default is 25.
+        temperature_sensitivity : float, optional
+            The temperature bias of the sensor in rad/s/°C. Default is 0,
+            meaning no temperature bias is applied.
+        temperature_scale_factor : float, optional
+            The temperature scale factor of the sensor in %/°C. Default is 0,
+            meaning no temperature scale factor is applied.
+        cross_axis_sensitivity : float, optional
+            Skewness of the sensor's axes in percentage. Default is 0, meaning
+            no cross-axis sensitivity is applied.
+        acceleration_sensitivity : float, optional
+            Sensitivity of the sensor to linear acceleration in rad/s/g. Default
+            is 0, meaning no sensitivity to linear acceleration is applied.
+
+        Returns
+        -------
+        None
+        """
+        self.type = "Gyroscope"
+        self.acceleration_sensitivity = acceleration_sensitivity
+        self.prints = _GyroscopePrints(self)
+        super().__init__(
+            sampling_rate,
+            orientation,
+            measurement_range=measurement_range,
+            resolution=resolution,
+            noise_density=noise_density,
+            random_walk=random_walk,
+            constant_bias=constant_bias,
+            operating_temperature=operating_temperature,
+            temperature_bias=temperature_bias,
+            temperature_scale_factor=temperature_scale_factor,
+            cross_axis_sensitivity=cross_axis_sensitivity,
+            name=name,
+        )
+
+    def measure(self, t, u, u_dot, relative_position, *args):
+        """
+        Measure the angular velocity of the rocket
+        """
+        # Angular velocity of the rocket in the rocket frame
+        omega = Vector(u[10:13])
+
+        # Transform to sensor frame
+        inertial_to_sensor = self._total_rotation_matrix @ Matrix.transformation(
+            u[6:10]
+        )
+        W = inertial_to_sensor @ omega
+
+        # Apply noise + bias
+        # Apply noise + bias and quatize
+        W = self.apply_noise(W)
+        W = self.apply_temperature_drift(W)
+
+        # Apply acceleration sensitivity
+        if self.acceleration_sensitivity != 0 and self.acceleration_sensitivity != None:
+            W += self.apply_acceleration_sensitivity(
+                omega, u_dot, relative_position, inertial_to_sensor
+            )
+
+        W = self.quantize(W)
+
+        self.measurement = tuple([*W])
+        self.measured_values.append((t, *W))
+
+    def apply_acceleration_sensitivity(
+        self, omega, u_dot, relative_position, rotation_matrix
+    ):
+        """
+        Apply acceleration sensitivity to the sensor measurement
+
+        Parameters
+        ----------
+        omega : Vector
+            The angular velocity to apply acceleration sensitivity to
+        cache : tuple
+            The cache of the rocket state
+        relative_position : Vector
+            The vector from the rocket's center of mass to the sensor in the
+            rocket frame
+        rotation_matrix : Matrix
+            The rotation matrix from the inertial frame to the sensor frame
+
+        Returns
+        -------
+        Vector
+            The angular velocity with applied acceleration sensitivity
+        """
+        # Linear acceleration of rocket cdm in inertial frame
+        a_I = Vector(u_dot[3:6])
+
+        # Angular velocity and accel of rocket
+        omega_dot = Vector(u_dot[10:13])
+
+        # Acceleration felt in sensor
+        A = (
+            a_I
+            + Vector.cross(omega_dot, relative_position)
+            + Vector.cross(omega, Vector.cross(omega, relative_position))
+        )
+        # Transform to sensor frame
+        A = rotation_matrix @ A
+
+        return self.acceleration_sensitivity * A
+
+    def export_measured_values(self, filename, format="csv"):
+        """
+        Export the measured values to a file
+
+        Parameters
+        ----------
+        filename : str
+            Name of the file to export the values to
+        format : str
+            Format of the file to export the values to. Options are "csv" and
+            "json". Default is "csv".
+
+        Returns
+        -------
+        None
+        """
+        if format == "csv":
+            with open(filename, "w") as f:
+                f.write("t,wx,wy,wz\n")
+                for t, wx, wy, wz in self.measured_values:
+                    f.write(f"{t},{wx},{wy},{wz}\n")
+        elif format == "json":
+            import json
+
+            data = {"t": [], "wx": [], "wy": [], "wz": []}
+            for t, wx, wy, wz in self.measured_values:
+                data["t"].append(t)
+                data["wx"].append(wx)
+                data["wy"].append(wy)
+                data["wz"].append(wz)
+            with open(filename, "w") as f:
+                json.dump(data, f)
+        else:
+            raise ValueError("Invalid format")

From 3b817771ed458f1eedb9c8ad5a3fc115d39ef16d Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:12:04 +0200
Subject: [PATCH 003/120] ENH: euler to quaternions tool function

---
 rocketpy/mathutils/vector_matrix.py | 28 +++++++++++++++++++++--
 rocketpy/tools.py                   | 35 ++++++++++++++++++++++++++++-
 2 files changed, 60 insertions(+), 3 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 50d827659..8263da2bf 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1,7 +1,7 @@
 from cmath import isclose
 from itertools import product
 
-from rocketpy.tools import cached_property
+from rocketpy.tools import cached_property, euler_to_quaternions
 
 
 class Vector:
@@ -153,7 +153,10 @@ def __len__(self):
     @cached_property
     def unit_vector(self):
         """R3 vector with the same direction of self, but normalized."""
-        return self / abs(self)
+        try:
+            return self / abs(self)
+        except ZeroDivisionError:
+            return self
 
     @cached_property
     def cross_matrix(self):
@@ -984,6 +987,27 @@ def transformation(quaternion):
             ]
         )
 
+    @staticmethod
+    def transformation_euler_angles(roll, pitch, yaw):
+        """Returns the transformation Matrix from frame B to frame A, where B
+        is rotated by the Euler angles roll, pitch and yaw with respect to A.
+
+        Parameters
+        ----------
+        roll : float
+            The roll angle in radians.
+        pitch : float
+            The pitch angle in radians.
+        yaw : float
+            The yaw angle in radians.
+
+        Returns
+        -------
+        Matrix
+            The transformation matrix from frame B to frame A.
+        """
+        return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))
+
 
 if __name__ == "__main__":
     import doctest
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 1ce588636..5666fdbdf 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -40,7 +40,7 @@ def __get__(self, instance, owner=None):
 
 def tuple_handler(value):
     """Transforms the input value into a tuple that
-    represents a range. If the input is an input or float,
+    represents a range. If the input is an int or float,
     the output is a tuple from zero to the input value. If
     the input is a tuple or list, the output is a tuple with
     the same range.
@@ -472,6 +472,39 @@ def quaternions_to_nutation(e1, e2):
     return (180 / np.pi) * 2 * np.arcsin(-((e1**2 + e2**2) ** 0.5))
 
 
+def euler_to_quaternions(roll, pitch, yaw):
+    """Calculates the quaternions from the Euler angles in 3-2-1 sequence.
+
+    Parameters
+    ----------
+    roll : float
+        Euler angle due to roll (psi) in degrees
+    pitch : float
+        Euler angle due to pitch (theta) in degrees
+    yaw : float
+        Euler angle due to yaw (phi) in degrees
+
+    Returns
+    -------
+    tuple
+        Tuple containing the Euler parameters e0, e1, e2, e3
+    """
+    psi = np.radians(roll)
+    theta = np.radians(pitch)
+    phi = np.radians(yaw)
+    cr = np.cos(phi / 2)
+    sr = np.sin(phi / 2)
+    cp = np.cos(theta / 2)
+    sp = np.sin(theta / 2)
+    cy = np.cos(psi / 2)
+    sy = np.sin(psi / 2)
+    e0 = cr * cp * cy + sr * sp * sy
+    e1 = sr * cp * cy - cr * sp * sy
+    e2 = cr * sp * cy + sr * cp * sy
+    e3 = cr * cp * sy - sr * sp * cy
+    return e0, e1, e2, e3
+
+
 if __name__ == "__main__":
     import doctest
 

From 4c8aa136c4c379672d650c75b639a9ead61cee70 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:54:28 +0200
Subject: [PATCH 004/120] ENH: add sensors to other classes

---
 rocketpy/control/controller.py | 52 ++++++++++++++++++-
 rocketpy/rocket/components.py  | 19 ++++++-
 rocketpy/rocket/rocket.py      | 37 +++++++++++---
 rocketpy/simulation/flight.py  | 91 ++++++++++++++++++++++++++++------
 4 files changed, 173 insertions(+), 26 deletions(-)

diff --git a/rocketpy/control/controller.py b/rocketpy/control/controller.py
index 81fc8b332..497161c22 100644
--- a/rocketpy/control/controller.py
+++ b/rocketpy/control/controller.py
@@ -1,3 +1,4 @@
+from inspect import signature
 from ..prints.controller_prints import _ControllerPrints
 
 
@@ -52,6 +53,10 @@ def __init__(
                the controller function can interact with. The objects are
                listed in the same order as they are provided in the
                `interactive_objects`.
+            7. `sensors` (list): A list of sensors that are attached to the
+                rocket. The most recent measurements of the sensors are provided
+                with the ``sensor.measurement`` attribute. The sensors are
+                listed in the same order as they are added to the rocket
 
             This function will be called during the simulation at the specified
             sampling rate. The function should evaluate and change the interactive
@@ -78,7 +83,7 @@ def __init__(
         None
         """
         self.interactive_objects = interactive_objects
-        self.controller_function = controller_function
+        self.controller_function = self.__init_controller_function(controller_function)
         self.sampling_rate = sampling_rate
         self.name = name
         self.prints = _ControllerPrints(self)
@@ -88,7 +93,44 @@ def __init__(
         else:
             self.observed_variables = []
 
-    def __call__(self, time, state_vector, state_history):
+    def __init_controller_function(self, controller_function):
+        """Checks number of arguments of the controller function and initializes
+        it with the correct number of arguments. This is a workaround to allow
+        the controller function to receive sensors without breaking changes"""
+        sig = signature(controller_function)
+        if len(sig.parameters) == 6:
+
+            def new_controller_function(
+                time,
+                sampling_rate,
+                state_vector,
+                state_history,
+                observed_variables,
+                interactive_objects,
+                sensors,
+            ):
+                return controller_function(
+                    time,
+                    sampling_rate,
+                    state_vector,
+                    state_history,
+                    observed_variables,
+                    interactive_objects,
+                )
+
+        elif len(sig.parameters) == 7:
+            new_controller_function = controller_function
+        else:
+            raise ValueError(
+                "The controller function must have 6 or 7 arguments. "
+                "The arguments must be in the following order: "
+                "(time, sampling_rate, state_vector, state_history, "
+                "observed_variables, interactive_objects, sensors)."
+                "Sensors argument is optional."
+            )
+        return new_controller_function
+
+    def __call__(self, time, state_vector, state_history, sensors):
         """Call the controller function. This is used by the simulation class.
 
         Parameters
@@ -104,6 +146,11 @@ def __call__(self, time, state_vector, state_history):
             history is a list of every state vector of every step of the
             simulation. The state history is a list of lists, where each
             sublist is a state vector and is ordered from oldest to newest.
+        sensors : list
+            A list of sensors that are attached to the rocket. The most recent
+            measurements of the sensors are provided with the
+            ``sensor.measurement`` attribute. The sensors are listed in the same
+            order as they are added to the rocket.
 
         Returns
         -------
@@ -116,6 +163,7 @@ def __call__(self, time, state_vector, state_history):
             state_history,
             self.observed_variables,
             self.interactive_objects,
+            sensors,
         )
         if observed_variables is not None:
             self.observed_variables.append(observed_variables)
diff --git a/rocketpy/rocket/components.py b/rocketpy/rocket/components.py
index 1d1d33e56..4a033507c 100644
--- a/rocketpy/rocket/components.py
+++ b/rocketpy/rocket/components.py
@@ -23,6 +23,11 @@ def __init__(self):
         self.component_tuple = namedtuple("component_tuple", "component position")
         self._components = []
 
+        # List of components and their positions to avoid extra for loops in
+        # simulation time
+        self._component_list = []
+        self._position_list = []
+
     def __repr__(self):
         """Return a string representation of the Components instance."""
         components_str = "\n".join(
@@ -61,6 +66,8 @@ def add(self, component, position):
         -------
         None
         """
+        self._component_list.append(component)
+        self._position_list.append(position)
         self._components.append(self.component_tuple(component, position))
 
     def get_by_type(self, component_type):
@@ -103,6 +110,16 @@ def get_tuple_by_type(self, component_type):
         ]
         return component_type_list
 
+    def get_components(self):
+        """Return a list of all the components in the list of components.
+
+        Returns
+        -------
+        list
+            A list of all the components in the list of components.
+        """
+        return self._component_list
+
     def get_positions(self):
         """Return a list of all the positions of the components in the list of
         components.
@@ -113,7 +130,7 @@ def get_positions(self):
             A list of all the positions of the components in the list of
             components.
         """
-        return [c.position for c in self._components]
+        return self._position_list
 
     def remove(self, component):
         """Remove a component from the list of components. If more than one
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index aaf585091..cfc0ad3eb 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -4,6 +4,7 @@
 
 from rocketpy.control.controller import _Controller
 from rocketpy.mathutils.function import Function
+from rocketpy.mathutils.vector_matrix import Vector
 from rocketpy.motors.motor import EmptyMotor
 from rocketpy.plots.rocket_plots import _RocketPlots
 from rocketpy.prints.rocket_prints import _RocketPrints
@@ -282,16 +283,11 @@ def __init__(
         self.thrust_eccentricity_y = 0
         self.thrust_eccentricity_x = 0
 
-        # Parachute, Aerodynamic and Rail buttons data initialization
+        # Parachute, Aerodynamic, Buttons, Controllers, Sensors data initialization
         self.parachutes = []
-
-        # Controllers data initialization
         self._controllers = []
-
-        # AirBrakes data initialization
         self.air_brakes = []
-
-        # Aerodynamic data initialization
+        self.sensors = Components()
         self.aerodynamic_surfaces = Components()
         self.rail_buttons = Components()
 
@@ -1170,6 +1166,29 @@ def add_parachute(
         self.parachutes.append(parachute)
         return self.parachutes[-1]
 
+    def add_sensor(self, sensor, position, x_position=0, y_position=0):
+        """Adds a sensor to the rocket.
+
+        Parameters
+        ----------
+        sensor : Sensor
+            Sensor to be added to the rocket.
+        position : int, float, tuple
+            Position, in meters, of the sensor's coordinate system origin
+            relative to the user defined rocket coordinate system.
+        x_position : int, float, optional
+            Distance in meters by which the CM is to be translated in the x
+            direction relative to geometrical center line. Default is 0.
+        y_position : int, float, optional
+            Distance in meters by which the CM is to be translated in the y
+            direction relative to geometrical center line. Default is 0.
+
+        Returns
+        -------
+        None
+        """
+        self.sensors.add(sensor, Vector([x_position, y_position, position]))
+
     def add_air_brakes(
         self,
         drag_coefficient_curve,
@@ -1238,6 +1257,10 @@ def add_air_brakes(
                the controller function can interact with. The objects are
                listed in the same order as they are provided in the
                `interactive_objects`
+            7. `sensors` (list): A list of sensors that are attached to the
+                rocket. The most recent measurements of the sensors are provided
+                with the ``sensor.measurement`` attribute. The sensors are
+                listed in the same order as they are added to the rocket
 
             This function will be called during the simulation at the specified
             sampling rate. The function should evaluate and change the observed
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 77632d2f2..dc922dba2 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -57,6 +57,8 @@ class Flight:
         Name of the flight.
     Flight._controllers : list
         List of controllers to be used during simulation.
+    Flight._component_sensors : list
+        List of sensors to be used during simulation.
     Flight.max_time : int, float
         Maximum simulation time allowed. Refers to physical time
         being simulated, not time taken to run simulation.
@@ -594,6 +596,8 @@ def __init__(
             raise ValueError("Rail length must be a positive value.")
         self.parachutes = self.rocket.parachutes[:]
         self._controllers = self.rocket._controllers[:]
+        self._component_sensors = self.rocket.sensors
+        self._sensors_list = self.rocket.sensors.get_components()
         self.inclination = inclination
         self.heading = heading
         self.max_time = max_time
@@ -662,17 +666,20 @@ def __init__(
             # Initialize phase time nodes
             phase.TimeNodes = TimeNodes()
             # Add first time node to permanent list
-            phase.TimeNodes.add_node(phase.t, [], [])
+            phase.TimeNodes.add_node(phase.t, [], [], [])
             # Add non-overshootable parachute time nodes
             if self.time_overshoot is False:
                 phase.TimeNodes.add_parachutes(
                     self.parachutes, phase.t, phase.time_bound
                 )
+                phase.TimeNodes.add_sensors(
+                    self._component_sensors, phase.t, phase.time_bound
+                )
                 phase.TimeNodes.add_controllers(
                     self._controllers, phase.t, phase.time_bound
                 )
             # Add lst time node to permanent list
-            phase.TimeNodes.add_node(phase.time_bound, [], [])
+            phase.TimeNodes.add_node(phase.time_bound, [], [], [])
             # Sort time nodes
             phase.TimeNodes.sort()
             # Merge equal time nodes
@@ -702,8 +709,28 @@ def __init__(
                 for callback in node.callbacks:
                     callback(self)
 
+                for sensor, position in node._component_sensors:
+                    relative_position = position - self.rocket._csys * Vector(
+                        [0, 0, self.rocket.center_of_dry_mass_position]
+                    )
+                    u_dot = phase.derivative(
+                        self.t, self.y_sol
+                    )  # calling udot for each sensor. Not optimal
+                    sensor.measure(
+                        self.t,
+                        self.y_sol,
+                        u_dot,
+                        relative_position,
+                        self.env.gravity(self.solution[-1][3]),
+                    )
+
                 for controller in node._controllers:
-                    controller(self.t, self.y_sol, self.solution)
+                    controller(
+                        self.t,
+                        self.y_sol,
+                        self.solution,
+                        self._sensors_list,
+                    )
 
                 for parachute in node.parachutes:
                     # Calculate and save pressure signal
@@ -718,7 +745,9 @@ def __init__(
                         self.env.barometric_height(pressure + noise)
                         - self.env.elevation
                     )
-                    if parachute.triggerfunc(pressure + noise, hAGL, self.y_sol):
+                    if parachute.triggerfunc(
+                        pressure + noise, hAGL, self.y_sol, self._sensors_list
+                    ):
                         # print('\nEVENT DETECTED')
                         # print('Parachute Triggered')
                         # print('Name: ', parachute.name, ' | Lag: ', parachute.lag)
@@ -750,7 +779,7 @@ def __init__(
                         )
                         # Prepare to leave loops and start new flight phase
                         phase.TimeNodes.flush_after(node_index)
-                        phase.TimeNodes.add_node(self.t, [], [])
+                        phase.TimeNodes.add_node(self.t, [], [], [])
                         phase.solver.status = "finished"
                         # Save parachute event
                         self.parachute_events.append([self.t, parachute])
@@ -868,7 +897,7 @@ def __init__(
                         )
                         # Prepare to leave loops and start new flight phase
                         phase.TimeNodes.flush_after(node_index)
-                        phase.TimeNodes.add_node(self.t, [], [])
+                        phase.TimeNodes.add_node(self.t, [], [], [])
                         phase.solver.status = "finished"
 
                     # Check for apogee event
@@ -902,7 +931,7 @@ def __init__(
                             self.FlightPhases.add_phase(self.t)
                             # Prepare to leave loops and start new flight phase
                             phase.TimeNodes.flush_after(node_index)
-                            phase.TimeNodes.add_node(self.t, [], [])
+                            phase.TimeNodes.add_node(self.t, [], [], [])
                             phase.solver.status = "finished"
                     # Check for impact event
                     if self.y_sol[2] < self.env.elevation:
@@ -965,7 +994,7 @@ def __init__(
                         self.FlightPhases.add_phase(self.t)
                         # Prepare to leave loops and start new flight phase
                         phase.TimeNodes.flush_after(node_index)
-                        phase.TimeNodes.add_node(self.t, [], [])
+                        phase.TimeNodes.add_node(self.t, [], [], [])
                         phase.solver.status = "finished"
 
                     # List and feed overshootable time nodes
@@ -977,7 +1006,7 @@ def __init__(
                             self.parachutes, self.solution[-2][0], self.t
                         )
                         # Add last time node (always skipped)
-                        overshootable_nodes.add_node(self.t, [], [])
+                        overshootable_nodes.add_node(self.t, [], [], [])
                         if len(overshootable_nodes) > 1:
                             # Sort overshootable time nodes
                             overshootable_nodes.sort()
@@ -1026,7 +1055,10 @@ def __init__(
                                     )
 
                                     if parachute.triggerfunc(
-                                        pressure + noise, hAGL, overshootable_node.y
+                                        pressure + noise,
+                                        hAGL,
+                                        overshootable_node.y,
+                                        self._sensors_list,
                                     ):
                                         # print('\nEVENT DETECTED')
                                         # print('Parachute Triggered')
@@ -1069,7 +1101,7 @@ def __init__(
                                             overshootable_index
                                         )
                                         phase.TimeNodes.flush_after(node_index)
-                                        phase.TimeNodes.add_node(self.t, [], [])
+                                        phase.TimeNodes.add_node(self.t, [], [], [])
                                         phase.solver.status = "finished"
                                         # Save parachute event
                                         self.parachute_events.append(
@@ -1943,6 +1975,8 @@ def u_dot_parachute(self, t, u, post_processing=False):
         ay = Dy / (mp + ma)
         az = (Dz - 9.8 * mp) / (mp + ma)
 
+        u_dot = [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
+
         if post_processing:
             # Dynamics variables
             self.R1_list.append([t, Dx])
@@ -3566,6 +3600,8 @@ def __init__(self, t, derivative=None, callbacks=None, clear=True):
                 self.derivative = derivative
                 self.callbacks = callbacks[:] if callbacks is not None else []
                 self.clear = clear
+                self.time_bound = None
+                self.TimeNodes = None
 
             def __repr__(self):
                 if self.derivative is None:
@@ -3594,8 +3630,8 @@ def __repr__(self):
         def add(self, time_node):
             self.list.append(time_node)
 
-        def add_node(self, t, parachutes, callbacks):
-            self.list.append(self.TimeNode(t, parachutes, callbacks))
+        def add_node(self, t, parachutes, controllers, sensors):
+            self.list.append(self.TimeNode(t, parachutes, controllers, sensors))
 
         def add_parachutes(self, parachutes, t_init, t_end):
             # Iterate over parachutes
@@ -3603,7 +3639,7 @@ def add_parachutes(self, parachutes, t_init, t_end):
                 # Calculate start of sampling time nodes
                 pcDt = 1 / parachute.sampling_rate
                 parachute_node_list = [
-                    self.TimeNode(i * pcDt, [parachute], [])
+                    self.TimeNode(i * pcDt, [parachute], [], [])
                     for i in range(
                         math.ceil(t_init / pcDt), math.floor(t_end / pcDt) + 1
                     )
@@ -3616,7 +3652,7 @@ def add_controllers(self, controllers, t_init, t_end):
                 # Calculate start of sampling time nodes
                 controller_time_step = 1 / controller.sampling_rate
                 controller_node_list = [
-                    self.TimeNode(i * controller_time_step, [], [controller])
+                    self.TimeNode(i * controller_time_step, [], [controller], [])
                     for i in range(
                         math.ceil(t_init / controller_time_step),
                         math.floor(t_end / controller_time_step) + 1,
@@ -3624,6 +3660,22 @@ def add_controllers(self, controllers, t_init, t_end):
                 ]
                 self.list += controller_node_list
 
+        def add_sensors(self, sensors, t_init, t_end):
+            # Iterate over sensors
+            for sensor_component_tuple in sensors:
+                # Calculate start of sampling time nodes
+                sensor_time_step = 1 / sensor_component_tuple.component.sampling_rate
+                sensor_node_list = [
+                    self.TimeNode(
+                        i * sensor_time_step, [], [], [sensor_component_tuple]
+                    )
+                    for i in range(
+                        math.ceil(t_init / sensor_time_step),
+                        math.floor(t_end / sensor_time_step) + 1,
+                    )
+                ]
+                self.list += sensor_node_list
+
         def sort(self):
             self.list.sort(key=(lambda node: node.t))
 
@@ -3637,6 +3689,8 @@ def merge(self):
                 if abs(node.t - self.tmp_list[-1].t) < 1e-7:
                     self.tmp_list[-1].parachutes += node.parachutes
                     self.tmp_list[-1].callbacks += node.callbacks
+                    self.tmp_list[-1]._component_sensors += node._component_sensors
+                    self.tmp_list[-1]._controllers += node._controllers
                 # Add new node to tmp list if there is none with the same time
                 else:
                     self.tmp_list.append(node)
@@ -3647,11 +3701,12 @@ def flush_after(self, index):
             del self.list[index + 1 :]
 
         class TimeNode:
-            def __init__(self, t, parachutes, controllers):
+            def __init__(self, t, parachutes, controllers, sensors):
                 self.t = t
                 self.parachutes = parachutes
                 self.callbacks = []
                 self._controllers = controllers
+                self._component_sensors = sensors
 
             def __repr__(self):
                 return (
@@ -3659,5 +3714,9 @@ def __repr__(self):
                     + str(self.t)
                     + " | Parachutes: "
                     + str(len(self.parachutes))
+                    + " | Controllers: "
+                    + str(len(self._controllers))
+                    + " | Sensors: "
+                    + str(len(self._sensors_list))
                     + "}"
                 )

From 09e0d751a8dc1f6dccbce19ebe03f33ee4b03784 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:56:39 +0200
Subject: [PATCH 005/120] ENH: prints and sensors draw

---
 rocketpy/plots/rocket_plots.py    | 329 +++++++++++++++++-------------
 rocketpy/prints/sensors_prints.py |  99 +++++++++
 rocketpy/rocket/rocket.py         |   8 +-
 3 files changed, 294 insertions(+), 142 deletions(-)
 create mode 100644 rocketpy/prints/sensors_prints.py

diff --git a/rocketpy/plots/rocket_plots.py b/rocketpy/plots/rocket_plots.py
index 7074704e6..50b24e0e9 100644
--- a/rocketpy/plots/rocket_plots.py
+++ b/rocketpy/plots/rocket_plots.py
@@ -3,6 +3,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
+from rocketpy.mathutils.vector_matrix import Vector
 from rocketpy.motors import EmptyMotor, HybridMotor, LiquidMotor, SolidMotor
 from rocketpy.rocket.aero_surface import Fins, NoseCone, Tail
 
@@ -168,7 +169,7 @@ def thrust_to_weight(self):
 
         return None
 
-    def draw(self, vis_args=None):
+    def draw(self, vis_args=None, plane="xz"):
         """Draws the rocket in a matplotlib figure.
 
         Parameters
@@ -188,8 +189,10 @@ def draw(self, vis_args=None):
             }
             A full list of color names can be found at:
             https://matplotlib.org/stable/gallery/color/named_colors
+        plane : str, optional
+            Plane in which the rocket will be drawn. Default is 'xz'. Other
+            options is 'yz'. Used only for sensors representation.
         """
-        # TODO: we need to modularize this function, it is too big
         if vis_args is None:
             vis_args = {
                 "background": "#EEEEEE",
@@ -202,20 +205,34 @@ def draw(self, vis_args=None):
                 "line_width": 1.0,
             }
 
-        # Create the figure and axis
-        _, ax = plt.subplots(figsize=(8, 6), facecolor="#EEEEEE")
+        fig, ax = plt.subplots(figsize=(8, 6), facecolor=vis_args["background"])
         ax.set_aspect("equal")
-        ax.set_facecolor(vis_args["background"])
         ax.grid(True, linestyle="--", linewidth=0.5)
 
         csys = self.rocket._csys
         reverse = csys == 1
         self.rocket.aerodynamic_surfaces.sort_by_position(reverse=reverse)
 
+        drawn_surfaces = self._draw_aerodynamic_surfaces(ax, vis_args)
+        last_radius, last_x = self._draw_tubes(ax, drawn_surfaces, vis_args)
+        self._draw_motor(last_radius, last_x, ax, vis_args)
+        self._draw_rail_buttons(ax, vis_args)
+        self._draw_center_of_mass_and_pressure(ax)
+        self._draw_sensor(ax, self.rocket.sensors, plane, vis_args)
+
+        plt.title("Rocket Representation")
+        plt.xlim()
+        plt.ylim([-self.rocket.radius * 4, self.rocket.radius * 6])
+        plt.xlabel("Position (m)")
+        plt.ylabel("Radius (m)")
+        plt.legend(bbox_to_anchor=(1.05, 1), loc="upper left")
+        plt.tight_layout()
+        plt.show()
+
+    def _draw_aerodynamic_surfaces(self, ax, vis_args):
         # List of drawn surfaces with the position of points of interest
         # and the radius of the rocket at that point
         drawn_surfaces = []
-
         # Idea is to get the shape of each aerodynamic surface in their own
         # coordinate system and then plot them in the rocket coordinate system
         # using the position of each surface
@@ -225,113 +242,98 @@ def draw(self, vis_args=None):
 
         for surface, position in self.rocket.aerodynamic_surfaces:
             if isinstance(surface, NoseCone):
-                x_nosecone = -csys * surface.shape_vec[0] + position
-                y_nosecone = surface.shape_vec[1]
+                self._draw_nose_cone(ax, surface, position, drawn_surfaces, vis_args)
+            elif isinstance(surface, Tail):
+                self._draw_tail(ax, surface, position, drawn_surfaces, vis_args)
+            elif isinstance(surface, Fins):
+                self._draw_fins(ax, surface, position, drawn_surfaces, vis_args)
+        return drawn_surfaces
 
-                ax.plot(
-                    x_nosecone,
-                    y_nosecone,
-                    color=vis_args["nose"],
-                    linewidth=vis_args["line_width"],
-                )
-                ax.plot(
-                    x_nosecone,
-                    -y_nosecone,
-                    color=vis_args["nose"],
-                    linewidth=vis_args["line_width"],
-                )
-                # close the nosecone
-                ax.plot(
-                    [x_nosecone[-1], x_nosecone[-1]],
-                    [y_nosecone[-1], -y_nosecone[-1]],
-                    color=vis_args["nose"],
-                    linewidth=vis_args["line_width"],
-                )
+    def _draw_nose_cone(self, ax, surface, position, drawn_surfaces, vis_args):
+        x_nosecone = -self.rocket._csys * surface.shape_vec[0] + position
+        y_nosecone = surface.shape_vec[1]
+        ax.plot(
+            x_nosecone,
+            y_nosecone,
+            color=vis_args["nose"],
+            linewidth=vis_args["line_width"],
+        )
+        ax.plot(
+            x_nosecone,
+            -y_nosecone,
+            color=vis_args["nose"],
+            linewidth=vis_args["line_width"],
+        )
+        # close the nosecone
+        ax.plot(
+            [x_nosecone[-1], x_nosecone[-1]],
+            [y_nosecone[-1], -y_nosecone[-1]],
+            color=vis_args["nose"],
+            linewidth=vis_args["line_width"],
+        )
+        # Add the nosecone to the list of drawn surfaces
+        drawn_surfaces.append(
+            (surface, x_nosecone[-1], surface.rocket_radius, x_nosecone[-1])
+        )
 
-                # Add the nosecone to the list of drawn surfaces
-                drawn_surfaces.append(
-                    (surface, x_nosecone[-1], surface.rocket_radius, x_nosecone[-1])
-                )
+    def _draw_tail(self, ax, surface, position, drawn_surfaces, vis_args):
+        x_tail = -self.rocket._csys * surface.shape_vec[0] + position
+        y_tail = surface.shape_vec[1]
+        ax.plot(
+            x_tail, y_tail, color=vis_args["tail"], linewidth=vis_args["line_width"]
+        )
+        ax.plot(
+            x_tail, -y_tail, color=vis_args["tail"], linewidth=vis_args["line_width"]
+        )
+        # close above and below the tail
+        ax.plot(
+            [x_tail[-1], x_tail[-1]],
+            [y_tail[-1], -y_tail[-1]],
+            color=vis_args["tail"],
+            linewidth=vis_args["line_width"],
+        )
+        ax.plot(
+            [x_tail[0], x_tail[0]],
+            [y_tail[0], -y_tail[0]],
+            color=vis_args["tail"],
+            linewidth=vis_args["line_width"],
+        )
+        # Add the tail to the list of drawn surfaces
+        drawn_surfaces.append((surface, position, surface.bottom_radius, x_tail[-1]))
 
-            elif isinstance(surface, Tail):
-                x_tail = -csys * surface.shape_vec[0] + position
-                y_tail = surface.shape_vec[1]
+    def _draw_fins(self, ax, surface, position, drawn_surfaces, vis_args):
+        num_fins = surface.n
+        x_fin = -self.rocket._csys * surface.shape_vec[0] + position
+        y_fin = surface.shape_vec[1] + surface.rocket_radius
+        rotation_angles = [2 * np.pi * i / num_fins for i in range(num_fins)]
 
-                ax.plot(
-                    x_tail,
-                    y_tail,
-                    color=vis_args["tail"],
-                    linewidth=vis_args["line_width"],
-                )
-                ax.plot(
-                    x_tail,
-                    -y_tail,
-                    color=vis_args["tail"],
-                    linewidth=vis_args["line_width"],
-                )
-                # close above and below the tail
-                ax.plot(
-                    [x_tail[-1], x_tail[-1]],
-                    [y_tail[-1], -y_tail[-1]],
-                    color=vis_args["tail"],
-                    linewidth=vis_args["line_width"],
-                )
-                ax.plot(
-                    [x_tail[0], x_tail[0]],
-                    [y_tail[0], -y_tail[0]],
-                    color=vis_args["tail"],
-                    linewidth=vis_args["line_width"],
-                )
+        for angle in rotation_angles:
+            x_rotated, y_rotated = self._rotate_points(x_fin, y_fin, angle)
+            ax.plot(
+                x_rotated,
+                y_rotated,
+                color=vis_args["fins"],
+                linewidth=vis_args["line_width"],
+            )
 
-                # Add the tail to the list of drawn surfaces
-                drawn_surfaces.append(
-                    (surface, position, surface.bottom_radius, x_tail[-1])
-                )
+        drawn_surfaces.append((surface, position, surface.rocket_radius, x_rotated[-1]))
 
-            # Draw fins
-            elif isinstance(surface, Fins):
-                num_fins = surface.n
-                x_fin = -csys * surface.shape_vec[0] + position
-                y_fin = surface.shape_vec[1] + surface.rocket_radius
-
-                # Calculate the rotation angles for the other two fins (symmetrically)
-                rotation_angles = [2 * np.pi * i / num_fins for i in range(num_fins)]
-
-                # Apply rotation transformations to get points for the other fins in 2D space
-                for angle in rotation_angles:
-                    # Create a rotation matrix for the current angle around the x-axis
-                    rotation_matrix = np.array([[1, 0], [0, np.cos(angle)]])
-
-                    # Apply the rotation to the original fin points
-                    rotated_points_2d = np.dot(
-                        rotation_matrix, np.vstack((x_fin, y_fin))
-                    )
-
-                    # Extract x and y coordinates of the rotated points
-                    x_rotated, y_rotated = rotated_points_2d
-
-                    # Project points above the XY plane back into the XY plane (set z-coordinate to 0)
-                    x_rotated = np.where(
-                        rotated_points_2d[1] > 0, rotated_points_2d[0], x_rotated
-                    )
-                    y_rotated = np.where(
-                        rotated_points_2d[1] > 0, rotated_points_2d[1], y_rotated
-                    )
-
-                    # Plot the fins
-                    ax.plot(
-                        x_rotated,
-                        y_rotated,
-                        color=vis_args["fins"],
-                        linewidth=vis_args["line_width"],
-                    )
-
-                # Add the fin to the list of drawn surfaces
-                drawn_surfaces.append(
-                    (surface, position, surface.rocket_radius, x_rotated[-1])
-                )
+    def _rotate_points(self, x_fin, y_fin, angle):
+        # Create a rotation matrix for the current angle around the x-axis
+        rotation_matrix = np.array([[1, 0], [0, np.cos(angle)]])
+
+        # Apply the rotation to the original fin points
+        rotated_points_2d = np.dot(rotation_matrix, np.vstack((x_fin, y_fin)))
+
+        # Extract x and y coordinates of the rotated points
+        x_rotated, y_rotated = rotated_points_2d
 
-        # Draw tubes
+        # Project points above the XY plane back into the XY plane (set z-coordinate to 0)
+        x_rotated = np.where(rotated_points_2d[1] > 0, rotated_points_2d[0], x_rotated)
+        y_rotated = np.where(rotated_points_2d[1] > 0, rotated_points_2d[1], y_rotated)
+        return x_rotated, y_rotated
+
+    def _draw_tubes(self, ax, drawn_surfaces, vis_args):
         for i, d_surface in enumerate(drawn_surfaces):
             # Draw the tubes, from the end of the first surface to the beginning
             # of the next surface, with the radius of the rocket at that point
@@ -368,18 +370,39 @@ def draw(self, vis_args=None):
                 color=vis_args["body"],
                 linewidth=vis_args["line_width"],
             )
+        return radius, last_x
 
-        # Draw motor
+    def _draw_motor(self, last_radius, last_x, ax, vis_args):
         total_csys = self.rocket._csys * self.rocket.motor._csys
         nozzle_position = (
             self.rocket.motor_position + self.rocket.motor.nozzle_position * total_csys
         )
 
-        # List of motor patches
+        # Get motor patches translated to the correct position
+        motor_patches = self._generate_motor_patches(total_csys, ax, vis_args)
+
+        # Draw patches
+        if not isinstance(self.rocket.motor, EmptyMotor):
+            # Add nozzle last so it is in front of the other patches
+            nozzle = self.rocket.motor.plots._generate_nozzle(
+                translate=(nozzle_position, 0), csys=self.rocket._csys
+            )
+            motor_patches += [nozzle]
+
+            outline = self.rocket.motor.plots._generate_motor_region(
+                list_of_patches=motor_patches
+            )
+            # add outline first so it is behind the other patches
+            ax.add_patch(outline)
+            for patch in motor_patches:
+                ax.add_patch(patch)
+
+        self._draw_nozzle_tube(last_radius, last_x, nozzle_position, ax, vis_args)
+
+    def _generate_motor_patches(self, total_csys, ax, vis_args):
         motor_patches = []
 
-        # Get motor patches translated to the correct position
-        if isinstance(self.rocket.motor, (SolidMotor)):
+        if isinstance(self.rocket.motor, SolidMotor):
             grains_cm_position = (
                 self.rocket.motor_position
                 + self.rocket.motor.grains_center_of_mass_position * total_csys
@@ -452,27 +475,16 @@ def draw(self, vis_args=None):
                 )
                 motor_patches += [tank]
 
-        # add nozzle last so it is in front of the other patches
-        if not isinstance(self.rocket.motor, EmptyMotor):
-            nozzle = self.rocket.motor.plots._generate_nozzle(
-                translate=(nozzle_position, 0), csys=self.rocket._csys
-            )
-            motor_patches += [nozzle]
-            outline = self.rocket.motor.plots._generate_motor_region(
-                list_of_patches=motor_patches
-            )
-            # add outline first so it is behind the other patches
-            ax.add_patch(outline)
-            for patch in motor_patches:
-                ax.add_patch(patch)
+        return motor_patches
 
+    def _draw_nozzle_tube(self, last_radius, last_x, nozzle_position, ax, vis_args):
         # Check if nozzle is beyond the last surface, if so draw a tube
         # to it, with the radius of the last surface
         if self.rocket._csys == 1:
             if nozzle_position < last_x:
                 x_tube = [last_x, nozzle_position]
-                y_tube = [radius, radius]
-                y_tube_negated = [-radius, -radius]
+                y_tube = [last_radius, last_radius]
+                y_tube_negated = [-last_radius, -last_radius]
 
                 ax.plot(
                     x_tube,
@@ -489,8 +501,8 @@ def draw(self, vis_args=None):
         else:  # if self.rocket._csys == -1:
             if nozzle_position > last_x:
                 x_tube = [last_x, nozzle_position]
-                y_tube = [radius, radius]
-                y_tube_negated = [-radius, -radius]
+                y_tube = [last_radius, last_radius]
+                y_tube_negated = [-last_radius, -last_radius]
 
                 ax.plot(
                     x_tube,
@@ -505,11 +517,11 @@ def draw(self, vis_args=None):
                     linewidth=vis_args["line_width"],
                 )
 
-        # Draw rail buttons
+    def _draw_rail_buttons(self, ax, vis_args):
         try:
             buttons, pos = self.rocket.rail_buttons[0]
             lower = pos
-            upper = pos + buttons.buttons_distance * csys
+            upper = pos + buttons.buttons_distance * self.rocket._csys
             ax.scatter(
                 lower, -self.rocket.radius, marker="s", color=vis_args["buttons"], s=15
             )
@@ -519,6 +531,7 @@ def draw(self, vis_args=None):
         except IndexError:
             pass
 
+    def _draw_center_of_mass_and_pressure(self, ax):
         # Draw center of mass and center of pressure
         cm = self.rocket.center_of_mass(0)
         ax.scatter(cm, 0, color="#1565c0", label="Center of Mass", s=10)
@@ -528,17 +541,55 @@ def draw(self, vis_args=None):
             cp, 0, label="Static Center of Pressure", color="red", s=10, zorder=10
         )
 
-        # Set plot attributes
-        plt.title("Rocket Representation")
-        plt.xlim()
-        plt.ylim([-self.rocket.radius * 4, self.rocket.radius * 6])
-        plt.xlabel("Position (m)")
-        plt.ylabel("Radius (m)")
-        plt.legend(bbox_to_anchor=(1.05, 1), loc="upper left")
-        plt.tight_layout()
-        plt.show()
+    def _draw_sensor(self, ax, sensors, plane, vis_args):
+        """Draw the sensor as a small thick line at the position of the sensor,
+        with a vector pointing in the direction normal of the sensor. Get the
+        normal vector from the sensor orientation matrix."""
+        colors = plt.rcParams["axes.prop_cycle"].by_key()["color"]
+        for i, sensor_pos in enumerate(sensors):
+            sensor = sensor_pos[0]
+            pos = sensor_pos[1]
+            if plane == "xz":
+                # z position of the sensor is the x position in the plot
+                x_pos = pos[2]
+                normal_x = sensor.normal_vector.z
+                # x position of the sensor is the y position in the plot
+                y_pos = pos[0]
+                normal_y = sensor.normal_vector.x
+            elif plane == "yz":
+                # z position of the sensor is the x position in the plot
+                x_pos = pos[2]
+                normal_x = sensor.normal_vector.z
+                # y position of the sensor is the y position in the plot
+                y_pos = pos[1]
+                normal_y = sensor.normal_vector.y
+            else:
+                raise ValueError("Plane must be 'xz' or 'yz'.")
 
-        return None
+            # line length is 1/10 of the rocket radius
+            line_length = self.rocket.radius / 2.5
+
+            ax.plot(
+                [x_pos, x_pos],
+                [y_pos + line_length, y_pos - line_length],
+                linewidth=2,
+                color=colors[(i + 1) % len(colors)],
+                zorder=10,
+                label=sensor.name,
+            )
+            ax.quiver(
+                x_pos,
+                y_pos,
+                normal_x,
+                normal_y,
+                color=colors[(i + 1) % len(colors)],
+                scale_units="xy",
+                angles="xy",
+                minshaft=2,
+                headwidth=2,
+                headlength=4,
+                zorder=10,
+            )
 
     def all(self):
         """Prints out all graphs available about the Rocket. It simply calls
diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
new file mode 100644
index 000000000..d41227de7
--- /dev/null
+++ b/rocketpy/prints/sensors_prints.py
@@ -0,0 +1,99 @@
+from abc import ABC, abstractmethod
+
+
+UNITS = {
+    "Gyroscope": "rad/s",
+    "Accelerometer": "m/s^2",
+    "Magnetometer": "T",
+    "PressureSensor": "Pa",
+    "TemperatureSensor": "K",
+}
+
+
+class _SensorsPrints(ABC):
+    def __init__(self, sensor):
+        self.sensor = sensor
+        self.units = UNITS[sensor.type]
+
+    def _print_aligned(self, label, value):
+        """Prints a label and a value aligned vertically."""
+        print(f"{label:<26} {value}")
+
+    def identity(self):
+        """Prints the identity of the sensor."""
+        print("Identification of the Sensor:\n")
+        self._print_aligned("Name:", self.sensor.name)
+        self._print_aligned("Type:", self.sensor.type)
+
+    def orientation(self):
+        """Prints the orientation of the sensor."""
+        print("\nOrientation of the Sensor:\n")
+        self._print_aligned("Orientation:", self.sensor.orientation)
+        self._print_aligned("Normal Vector:", self.sensor.normal_vector)
+        print("Rotation Matrix:")
+        for row in self.sensor.rotation_matrix:
+            value = " ".join(f"{val:.2f}" for val in row)
+            value = [float(val) for val in value.split()]
+            self._print_aligned("", value)
+
+    def quantization(self):
+        """Prints the quantization of the sensor."""
+        print("\nQuantization of the Sensor:\n")
+        self._print_aligned(
+            "Measurement Range:",
+            f"{self.sensor.measurement_range[0]} to {self.sensor.measurement_range[1]} ({self.units})",
+        )
+        self._print_aligned("Resolution:", f"{self.sensor.resolution} {self.units}/LSB")
+
+    def noise(self):
+        """Prints the noise of the sensor."""
+        print("\nNoise of the Sensor:\n")
+        self._print_aligned(
+            "Noise Density:", f"{self.sensor.noise_density} {self.units}/√Hz"
+        )
+        self._print_aligned(
+            "Random Walk:", f"{self.sensor.random_walk} {self.units}/√Hz"
+        )
+        self._print_aligned(
+            "Constant Bias:", f"{self.sensor.constant_bias} {self.units}"
+        )
+        self._print_aligned(
+            "Operating Temperature:", f"{self.sensor.operating_temperature} °C"
+        )
+        self._print_aligned(
+            "Temperature Bias:", f"{self.sensor.temperature_bias} {self.units}/°C"
+        )
+        self._print_aligned(
+            "Temperature Scale Factor:", f"{self.sensor.temperature_scale_factor} %/°C"
+        )
+        self._print_aligned(
+            "Cross Axis Sensitivity:", f"{self.sensor.cross_axis_sensitivity} %"
+        )
+        if self.sensor.type == "Gyroscope":
+            self._print_aligned(
+                "Acceleration Sensitivity:",
+                f"{self.sensor.acceleration_sensitivity} rad/s/g",
+            )
+
+    def all(self):
+        """Prints all information of the sensor."""
+        self.identity()
+        self.orientation()
+        self.quantization()
+        self.noise()
+
+
+class _AccelerometerPrints(_SensorsPrints):
+    """Class that contains all accelerometer prints."""
+
+    def __init__(self, accelerometer):
+        """Initialize the class."""
+        super().__init__(accelerometer)
+
+
+class _GyroscopePrints(_SensorsPrints):
+    """Class that contains all gyroscope prints."""
+
+    def __init__(self, gyroscope):
+        """Initialize the class."""
+        super().__init__(gyroscope)
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index cfc0ad3eb..9c179557e 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -1454,7 +1454,7 @@ def add_thrust_eccentricity(self, x, y):
         self.thrust_eccentricity_x = y
         return self
 
-    def draw(self, vis_args=None):
+    def draw(self, vis_args=None, plane="xz"):
         """Draws the rocket in a matplotlib figure.
 
         Parameters
@@ -1474,9 +1474,11 @@ def draw(self, vis_args=None):
             }
             A full list of color names can be found at:
             https://matplotlib.org/stable/gallery/color/named_colors
+        plane : str, optional
+            Plane in which the rocket will be drawn. Default is 'xz'. Other
+            options is 'yz'. Used only for sensors representation.
         """
-        self.plots.draw(vis_args)
-        return None
+        self.plots.draw(vis_args, plane)
 
     def info(self):
         """Prints out a summary of the data and graphs available about

From 38866f4e712f3b9f9136100fc335c6862abc9a6a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:58:23 +0200
Subject: [PATCH 006/120] ENH: add sensors to parachutes

---
 rocketpy/rocket/parachute.py | 22 +++++++++++++++++++---
 1 file changed, 19 insertions(+), 3 deletions(-)

diff --git a/rocketpy/rocket/parachute.py b/rocketpy/rocket/parachute.py
index 31f9252ed..4c5e5d7f3 100644
--- a/rocketpy/rocket/parachute.py
+++ b/rocketpy/rocket/parachute.py
@@ -1,4 +1,5 @@
 import numpy as np
+from inspect import signature
 
 from ..mathutils.function import Function
 from ..prints.parachute_prints import _ParachutePrints
@@ -31,6 +32,11 @@ class Parachute:
 
            `[x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz]`.
 
+        4. A list of sensors that are attached to the rocket. The most recent
+           measurements of the sensors are provided with the
+           ``sensor.measurement`` attribute. The sensors are listed in the same
+           order as they are added to the rocket.
+
         The function should return True if the parachute ejection system should
         be triggered and False otherwise.
 
@@ -177,12 +183,22 @@ def __evaluate_trigger_function(self, trigger):
         """This is used to set the triggerfunc attribute that will be used to
         interact with the Flight class.
         """
+        # The parachute is deployed by a custom function
         if callable(trigger):
-            self.triggerfunc = trigger
+            # work around for having added sensors to parachute triggers
+            # to avoid breaking changes
+            triggerfunc = trigger
+            sig = signature(triggerfunc)
+            if len(sig.parameters) == 3:
+
+                def triggerfunc(p, h, y, sensors):
+                    return trigger(p, h, y)
+
+            self.triggerfunc = triggerfunc
 
         elif isinstance(trigger, (int, float)):
             # The parachute is deployed at a given height
-            def triggerfunc(p, h, y):
+            def triggerfunc(p, h, y, sensors):
                 # p = pressure considering parachute noise signal
                 # h = height above ground level considering parachute noise signal
                 # y = [x, y, z, vx, vy, vz, e0, e1, e2, e3, w1, w2, w3]
@@ -192,7 +208,7 @@ def triggerfunc(p, h, y):
 
         elif trigger.lower() == "apogee":
             # The parachute is deployed at apogee
-            def triggerfunc(p, h, y):
+            def triggerfunc(p, h, y, sensors):
                 # p = pressure considering parachute noise signal
                 # h = height above ground level considering parachute noise signal
                 # y = [x, y, z, vx, vy, vz, e0, e1, e2, e3, w1, w2, w3]

From b386e388f05ad466564d336ad28f46401ddb67bb Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:59:10 +0200
Subject: [PATCH 007/120] TST: add sensors fixtures

---
 tests/conftest.py                          |  1 +
 tests/fixtures/flight/flight_fixtures.py   | 30 +++++++++
 tests/fixtures/rockets/rocket_fixtures.py  | 27 ++++++++
 tests/fixtures/sensors/__init__.py         |  0
 tests/fixtures/sensors/sensors_fixtures.py | 78 ++++++++++++++++++++++
 5 files changed, 136 insertions(+)
 create mode 100644 tests/fixtures/sensors/__init__.py
 create mode 100644 tests/fixtures/sensors/sensors_fixtures.py

diff --git a/tests/conftest.py b/tests/conftest.py
index 4766b570a..e8eda67ce 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -13,6 +13,7 @@
     "tests.fixtures.rockets.rocket_fixtures",
     "tests.fixtures.surfaces.surface_fixtures",
     "tests.fixtures.units.numerical_fixtures",
+    "tests.fixtures.sensors.sensors_fixtures",
 ]
 
 
diff --git a/tests/fixtures/flight/flight_fixtures.py b/tests/fixtures/flight/flight_fixtures.py
index c8f73d52c..9976ddac2 100644
--- a/tests/fixtures/flight/flight_fixtures.py
+++ b/tests/fixtures/flight/flight_fixtures.py
@@ -158,3 +158,33 @@ def flight_calisto_air_brakes(calisto_air_brakes_clamp_on, example_plain_env):
         time_overshoot=False,
         terminate_on_apogee=True,
     )
+
+
+@pytest.fixture
+def flight_calisto_accel_gyro(calisto_accel_gyro, example_plain_env):
+    """A rocketpy.Flight object of the Calisto rocket. This uses the calisto
+    with an ideal accelerometer and a gyroscope. The environment is the simplest
+    possible, with no parameters set.
+
+    Parameters
+    ----------
+    calisto_accel_gyro : rocketpy.Rocket
+        An object of the Rocket class.
+    example_plain_env : rocketpy.Environment
+        An object of the Environment class.
+
+    Returns
+    -------
+    rocketpy.Flight
+        A rocketpy.Flight object of the Calisto rocket in a more complex
+        condition.
+    """
+    return Flight(
+        rocket=calisto_accel_gyro,
+        environment=example_plain_env,
+        rail_length=5.2,
+        inclination=85,
+        heading=0,
+        time_overshoot=False,
+        terminate_on_apogee=True,
+    )
diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index 3a1c82988..c461a78f4 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -243,6 +243,33 @@ def calisto_air_brakes_clamp_off(calisto_robust, controller_function):
     return calisto
 
 
+@pytest.fixture
+def calisto_accel_gyro(calisto_robust, ideal_accelerometer, ideal_gyroscope):
+    """Create an object class of the Rocket class to be used in the tests. This
+    is the same Calisto rocket that was defined in the calisto fixture, but with
+    an ideal accelerometer and a gyroscope added at the center of dry mass.
+    Meaning the readings will be the same as the values saved on a Flight object.
+
+    Parameters
+    ----------
+    calisto : rocketpy.Rocket
+        An object of the Rocket class. This is a pytest fixture.
+    accelerometer : rocketpy.Accelerometer
+        An object of the Accelerometer class. This is a pytest fixture.
+    gyroscope : rocketpy.Gyroscope
+        An object of the Gyroscope class. This is a pytest fixture.
+
+    Returns
+    -------
+    rocketpy.Rocket
+        An object of the Rocket class
+    """
+    calisto = calisto_robust
+    calisto.add_sensor(ideal_accelerometer, -0.10482544178314143)
+    calisto.add_sensor(ideal_gyroscope, -0.10482544178314143)
+    return calisto
+
+
 @pytest.fixture  # old name: dimensionless_rocket
 def dimensionless_calisto(kg, m, dimensionless_cesaroni_m1670):
     """The dimensionless version of the Calisto rocket. This is the same rocket
diff --git a/tests/fixtures/sensors/__init__.py b/tests/fixtures/sensors/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
new file mode 100644
index 000000000..d334a0a46
--- /dev/null
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -0,0 +1,78 @@
+import pytest
+from rocketpy import Accelerometer, Gyroscope
+
+
+@pytest.fixture
+def noisy_rotated_accelerometer():
+    """Returns an accelerometer with all parameters set to non-default values,
+    i.e. with noise and rotation."""
+    # mpu6050 values
+    return Accelerometer(
+        sampling_rate=100,
+        orientation=(60, 60, 60),
+        noise_density=0.05,
+        random_walk=0.02,
+        constant_bias=0.5,
+        operating_temperature=25,
+        temperature_bias=0.02,
+        temperature_scale_factor=0.02,
+        cross_axis_sensitivity=0.5,
+        consider_gravity=True,
+        name="Accelerometer",
+    )
+
+
+@pytest.fixture
+def noisy_rotated_gyroscope():
+    """Returns a gyroscope with all parameters set to non-default values,
+    i.e. with noise and rotation."""
+    # mpu6050 values
+    return Gyroscope(
+        sampling_rate=100,
+        orientation=(-60, -60, -60),
+        noise_density=0.05,
+        random_walk=0.02,
+        constant_bias=0.5,
+        operating_temperature=25,
+        temperature_bias=0.02,
+        temperature_scale_factor=0.02,
+        cross_axis_sensitivity=0.5,
+        acceleration_sensitivity=0.0017,
+        name="Gyroscope",
+    )
+
+
+@pytest.fixture
+def quantized_accelerometer():
+    """Returns an accelerometer with all parameters set to non-default values,
+    i.e. with noise and rotation."""
+    return Accelerometer(
+        sampling_rate=100,
+        measurement_range=2,
+        resolution=0.4882,
+    )
+
+
+@pytest.fixture
+def quantized_gyroscope():
+    """Returns a gyroscope with all parameters set to non-default values,
+    i.e. with noise and rotation."""
+    return Gyroscope(
+        sampling_rate=100,
+        measurement_range=15,
+        resolution=0.4882,
+    )
+
+
+@pytest.fixture
+def ideal_accelerometer():
+    return Accelerometer(
+        sampling_rate=100,
+    )
+
+
+@pytest.fixture
+def ideal_gyroscope():
+    return Gyroscope(
+        sampling_rate=100,
+    )

From 6ff2dde621df293231c67801faf2d7000a278714 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 19:59:22 +0200
Subject: [PATCH 008/120] TST: add sensors tests

---
 tests/test_sensors.py      |  63 ++++++
 tests/unit/test_sensors.py | 398 +++++++++++++++++++++++++++++++++++++
 2 files changed, 461 insertions(+)
 create mode 100644 tests/test_sensors.py
 create mode 100644 tests/unit/test_sensors.py

diff --git a/tests/test_sensors.py b/tests/test_sensors.py
new file mode 100644
index 000000000..666e5f8e3
--- /dev/null
+++ b/tests/test_sensors.py
@@ -0,0 +1,63 @@
+import numpy as np
+
+from rocketpy.mathutils.vector_matrix import Vector
+from rocketpy.rocket.components import Components
+from rocketpy.sensors.accelerometer import Accelerometer
+from rocketpy.sensors.gyroscope import Gyroscope
+
+
+def test_sensor_on_rocket(calisto_accel_gyro):
+    """Test the sensor on the rocket.
+
+    Parameters
+    ----------
+    calisto_accel_gyro : Rocket
+        Pytest fixture for the calisto rocket with an accelerometer and a gyroscope.
+    """
+    sensors = calisto_accel_gyro.sensors
+    assert isinstance(sensors, Components)
+    assert isinstance(sensors[0].component, Accelerometer)
+    assert isinstance(sensors[1].position, Vector)
+    assert isinstance(sensors[1].component, Gyroscope)
+    assert isinstance(sensors[1].position, Vector)
+
+
+def test_ideal_accelerometer(flight_calisto_accel_gyro):
+    """Test the ideal accelerometer.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    """
+    accelerometer = flight_calisto_accel_gyro.rocket.sensors[0].component
+    time, ax, ay, az = zip(*accelerometer.measured_values)
+    ax = np.array(ax)
+    ay = np.array(ay)
+    az = np.array(az)
+    a = np.sqrt(ax**2 + ay**2 + az**2)
+    sim_accel = flight_calisto_accel_gyro.acceleration(time)
+
+    # tolerance is bounded to numerical errors in the transformation matrixes
+    assert np.allclose(a, sim_accel, atol=1e-2)
+
+
+def test_ideal_gyroscope(flight_calisto_accel_gyro):
+    """Test the ideal gyroscope.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    """
+    gyroscope = flight_calisto_accel_gyro.rocket.sensors[1].component
+    time, wx, wy, wz = zip(*gyroscope.measured_values)
+    wx = np.array(wx)
+    wy = np.array(wy)
+    wz = np.array(wz)
+    w = np.sqrt(wx**2 + wy**2 + wz**2)
+    flight_wx = np.array(flight_calisto_accel_gyro.w1(time))
+    flight_wy = np.array(flight_calisto_accel_gyro.w2(time))
+    flight_wz = np.array(flight_calisto_accel_gyro.w3(time))
+    sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
+    assert np.allclose(w, sim_w, atol=1e-8)
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
new file mode 100644
index 000000000..c7ee8175b
--- /dev/null
+++ b/tests/unit/test_sensors.py
@@ -0,0 +1,398 @@
+import json
+import os
+import numpy as np
+from pytest import approx
+from rocketpy.mathutils.vector_matrix import Matrix, Vector
+from rocketpy.tools import euler_to_quaternions
+
+# calisto standard simulation no wind solution index 200
+SOLUTION = [
+    3.338513236767685,
+    0.02856482783411794,
+    50.919436628139216,
+    1898.9056294848442,
+    0.021620542063162787,
+    30.468683793837055,
+    284.19140267225384,
+    -0.0076008223256743114,
+    0.0004430927976100488,
+    0.05330950836930627,
+    0.9985245671704497,
+    0.0026388673982115224,
+    0.00010697759229808481,
+    19.72526891699468,
+]
+UDOT = [
+    0.021620542063162787,
+    30.468683793837055,
+    284.19140267225384,
+    0.0009380154986373648,
+    1.4853035773069556,
+    4.377014845613867,
+    -9.848086239924413,
+    0.5257087555505318,
+    -0.0030529818895471124,
+    -0.07503444684343626,
+    0.028008532884449017,
+    -0.052789015849051935,
+    2.276425320359305,
+]
+
+
+def test_accelerometer_prints(noisy_rotated_accelerometer, quantized_accelerometer):
+    """Test the print methods of the Accelerometer class. Checks if all
+    attributes are printed correctly.
+    """
+    noisy_rotated_accelerometer.prints.all()
+    quantized_accelerometer.prints.all()
+    assert True
+
+
+def test_gyroscope_prints(noisy_rotated_gyroscope, quantized_gyroscope):
+    """Test the print methods of the Gyroscope class. Checks if all
+    attributes are printed correctly.
+    """
+    noisy_rotated_gyroscope.prints.all()
+    quantized_gyroscope.prints.all()
+    assert True
+
+
+def test_rotation_matrix(noisy_rotated_accelerometer):
+    """Test the rotation_matrix property of the Accelerometer class. Checks if
+    the rotation matrix is correctly calculated.
+    """
+    expected_matrix = np.array(
+        [
+            [0.2500000, -0.0580127, 0.9665064],
+            [0.4330127, 0.8995190, -0.0580127],
+            [-0.8660254, 0.4330127, 0.2500000],
+        ]
+    )
+    rotation_matrix = np.array(noisy_rotated_accelerometer.rotation_matrix.components)
+    assert np.allclose(expected_matrix, rotation_matrix, atol=1e-8)
+
+
+def test_ideal_accelerometer_measure(ideal_accelerometer):
+    """Test the measure method of the Accelerometer class. Checks if saved
+    measurement is (ax,ay,az) and if measured_values is [(t, (ax,ay,az)), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+
+    relative_position = Vector([0, 0, 0])
+    gravity = 9.81
+    a_I = Vector(UDOT[3:6])
+    omega = Vector(u[10:13])
+    omega_dot = Vector(UDOT[10:13])
+    accel = (
+        a_I
+        + Vector.cross(omega_dot, relative_position)
+        + Vector.cross(omega, Vector.cross(omega, relative_position))
+    )
+    ax, ay, az = Matrix.transformation(u[6:10]) @ accel
+    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+
+    # check last measurement
+    assert len(ideal_accelerometer.measurement) == 3
+    assert all(isinstance(i, float) for i in ideal_accelerometer.measurement)
+    assert ideal_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
+
+    # check measured values
+    assert len(ideal_accelerometer.measured_values) == 1
+    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    assert len(ideal_accelerometer.measured_values) == 2
+
+    assert all(isinstance(i, tuple) for i in ideal_accelerometer.measured_values)
+    assert ideal_accelerometer.measured_values[0][0] == t
+    assert ideal_accelerometer.measured_values[0][1:] == approx([ax, ay, az], abs=1e-10)
+
+
+def test_ideal_gyroscope_measure(ideal_gyroscope):
+    """Test the measure method of the Gyroscope class. Checks if saved
+    measurement is (wx,wy,wz) and if measured_values is [(t, (wx,wy,wz)), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector(
+        [np.random.randint(-1, 1), np.random.randint(-1, 1), np.random.randint(-1, 1)]
+    )
+
+    rot = Matrix.transformation(u[6:10])
+    ax, ay, az = rot @ Vector(u[10:13])
+
+    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+
+    # check last measurement
+    assert len(ideal_gyroscope.measurement) == 3
+    assert all(isinstance(i, float) for i in ideal_gyroscope.measurement)
+    assert ideal_gyroscope.measurement == approx([ax, ay, az], abs=1e-10)
+
+    # check measured values
+    assert len(ideal_gyroscope.measured_values) == 1
+    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    assert len(ideal_gyroscope.measured_values) == 2
+
+    assert all(isinstance(i, tuple) for i in ideal_gyroscope.measured_values)
+    assert ideal_gyroscope.measured_values[0][0] == t
+    assert ideal_gyroscope.measured_values[0][1:] == approx([ax, ay, az], abs=1e-10)
+
+
+def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
+    """Test the measure method of the Accelerometer class. Checks if saved
+    measurement is (ax,ay,az) and if measured_values is [(t, (ax,ay,az)), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+
+    # calculate acceleration at sensor position in inertial frame
+    relative_position = Vector([0.4, 0.4, 1])
+    gravity = 9.81
+    a_I = Vector(UDOT[3:6]) + Vector([0, 0, -gravity])
+    omega = Vector(u[10:13])
+    omega_dot = Vector(UDOT[10:13])
+    accel = (
+        a_I
+        + Vector.cross(omega_dot, relative_position)
+        + Vector.cross(omega, Vector.cross(omega, relative_position))
+    )
+
+    # calculate total rotation matrix
+    cross_axis_sensitivity = Matrix(
+        [
+            [1, 0.005, 0.005],
+            [0.005, 1, 0.005],
+            [0.005, 0.005, 1],
+        ]
+    )
+    sensor_rotation = Matrix.transformation(euler_to_quaternions(60, 60, 60))
+    total_rotation = sensor_rotation @ cross_axis_sensitivity
+    rocket_rotation = Matrix.transformation(u[6:10])
+    # expected measurement without noise
+    ax, ay, az = total_rotation @ (rocket_rotation @ accel)
+    # expected measurement with constant bias
+    ax += 0.5
+    ay += 0.5
+    az += 0.5
+
+    # check last measurement considering noise error bounds
+    noisy_rotated_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.5)
+
+
+def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
+    """Test the measure method of the Gyroscope class. Checks if saved
+    measurement is (wx,wy,wz) and if measured_values is [(t, (wx,wy,wz)), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    # calculate acceleration at sensor position in inertial frame
+    relative_position = Vector([0.4, 0.4, 1])
+    gravity = 9.81
+    omega = Vector(u[10:13])
+    # calculate total rotation matrix
+    cross_axis_sensitivity = Matrix(
+        [
+            [1, 0.005, 0.005],
+            [0.005, 1, 0.005],
+            [0.005, 0.005, 1],
+        ]
+    )
+    sensor_rotation = Matrix.transformation(euler_to_quaternions(-60, -60, -60))
+    total_rotation = sensor_rotation @ cross_axis_sensitivity
+    rocket_rotation = Matrix.transformation(u[6:10])
+    # expected measurement without noise
+    wx, wy, wz = total_rotation @ (rocket_rotation @ omega)
+    # expected measurement with constant bias
+    wx += 0.5
+    wy += 0.5
+    wz += 0.5
+
+    # check last measurement considering noise error bounds
+    noisy_rotated_gyroscope.measure(t, u, UDOT, relative_position, gravity)
+    assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.5)
+
+
+def test_quatization_accelerometer(quantized_accelerometer):
+    """Test the measure method of the Accelerometer class. Checks if saved
+    measurement is (ax,ay,az) and if measured_values is [(t, (ax,ay,az)), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    # calculate acceleration at sensor position in inertial frame
+    relative_position = Vector([0, 0, 0])
+    gravity = 9.81
+    a_I = Vector(UDOT[3:6])
+    omega = Vector(u[10:13])
+    omega_dot = Vector(UDOT[10:13])
+    accel = (
+        a_I
+        + Vector.cross(omega_dot, relative_position)
+        + Vector.cross(omega, Vector.cross(omega, relative_position))
+    )
+
+    # calculate total rotation matrix
+    rocket_rotation = Matrix.transformation(u[6:10])
+    # expected measurement without noise
+    ax, ay, az = rocket_rotation @ accel
+    # expected measurement with quantization
+    az = 2  # saturated
+    ax = round(ax / 0.4882) * 0.4882
+    ay = round(ay / 0.4882) * 0.4882
+    az = round(az / 0.4882) * 0.4882
+
+    # check last measurement considering noise error bounds
+    quantized_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    assert quantized_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
+
+
+def test_quatization_gyroscope(quantized_gyroscope):
+    """Test the measure method of the Gyroscope class. Checks if saved
+    measurement is (wx,wy,wz) and if measured_values is [(t, (wx,wy,wz)), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    # calculate acceleration at sensor position in inertial frame
+    relative_position = Vector([0.4, 0.4, 1])
+    gravity = 9.81
+    omega = Vector(u[10:13])
+    # calculate total rotation matrix
+    rocket_rotation = Matrix.transformation(u[6:10])
+    # expected measurement without noise
+    wx, wy, wz = rocket_rotation @ omega
+    # expected measurement with quantization
+    wz = 15  # saturated
+    wx = round(wx / 0.4882) * 0.4882
+    wy = round(wy / 0.4882) * 0.4882
+    wz = round(wz / 0.4882) * 0.4882
+
+    # check last measurement considering noise error bounds
+    quantized_gyroscope.measure(t, u, UDOT, relative_position, gravity)
+    assert quantized_gyroscope.measurement == approx([wx, wy, wz], abs=1e-10)
+
+
+def test_export_accel_data_csv(ideal_accelerometer):
+    """Test the export_data method of accelerometer. Checks if the data is
+    exported correctly.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector([0, 0, 0])
+    gravity = 9.81
+    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+
+    file_name = "sensors.csv"
+
+    ideal_accelerometer.export_measured_values(file_name, format="csv")
+
+    with open(file_name, "r") as file:
+        contents = file.read()
+
+    expected_data = "t,ax,ay,az\n"
+    for t, ax, ay, az in ideal_accelerometer.measured_values:
+        expected_data += f"{t},{ax},{ay},{az}\n"
+
+    assert contents == expected_data
+    os.remove(file_name)
+
+
+def test_export_accel_data_json(ideal_accelerometer):
+    """Test the export_data method of the accelerometer. Checks if the data is
+    exported correctly.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal
+        accelerometer and a gyroscope.
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector([0, 0, 0])
+    gravity = 9.81
+    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+
+    file_name = "sensors.json"
+
+    ideal_accelerometer.export_measured_values(file_name, format="json")
+
+    contents = json.load(open(file_name, "r"))
+
+    expected_data = {"t": [], "ax": [], "ay": [], "az": []}
+    for t, ax, ay, az in ideal_accelerometer.measured_values:
+        expected_data["t"].append(t)
+        expected_data["ax"].append(ax)
+        expected_data["ay"].append(ay)
+        expected_data["az"].append(az)
+
+    assert contents == expected_data
+    os.remove(file_name)
+
+
+def test_export_gyro_data_csv(ideal_gyroscope):
+    """Test the export_data method of the gyroscope. Checks if the data is
+    exported correctly.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal
+        accelerometer and a gyroscope.
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector([0, 0, 0])
+    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+
+    file_name = "sensors.csv"
+
+    ideal_gyroscope.export_measured_values(file_name, format="csv")
+
+    with open(file_name, "r") as file:
+        contents = file.read()
+
+    expected_data = "t,wx,wy,wz\n"
+    for t, wx, wy, wz in ideal_gyroscope.measured_values:
+        expected_data += f"{t},{wx},{wy},{wz}\n"
+
+    assert contents == expected_data
+    os.remove(file_name)
+
+
+def test_export_gyro_data_json(ideal_gyroscope):
+    """Test the export_data method of the gyroscope. Checks if the data is
+    exported correctly.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector([0, 0, 0])
+    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+
+    file_name = "sensors.json"
+
+    ideal_gyroscope.export_measured_values(file_name, format="json")
+
+    contents = json.load(open(file_name, "r"))
+
+    expected_data = {"t": [], "wx": [], "wy": [], "wz": []}
+    for t, wx, wy, wz in ideal_gyroscope.measured_values:
+        expected_data["t"].append(t)
+        expected_data["wx"].append(wx)
+        expected_data["wy"].append(wy)
+        expected_data["wz"].append(wz)
+
+    assert contents == expected_data
+    os.remove(file_name)

From 5ae01b9f5db9e17a8a9f0ac38ee33cc2e793dab6 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 1 Apr 2024 20:15:56 +0200
Subject: [PATCH 009/120] DEV: sensors testing notebook

---
 docs/notebooks/sensors_testing.ipynb | 690 +++++++++++++++++++++++++++
 1 file changed, 690 insertions(+)
 create mode 100644 docs/notebooks/sensors_testing.ipynb

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors_testing.ipynb
new file mode 100644
index 000000000..76a0815a9
--- /dev/null
+++ b/docs/notebooks/sensors_testing.ipynb
@@ -0,0 +1,690 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "nvAT8wcRNVEk"
+   },
+   "source": [
+    "# -----------\n",
+    "\n",
+    "notebook to test sensors... should not be merged"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "XGK9M8ecNVEp"
+   },
+   "outputs": [],
+   "source": [
+    "from rocketpy import Environment, SolidMotor, Rocket, Flight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "uRa566HoNVE9"
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "5kl-Je8dNVFI"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Gravity Details\n",
+      "\n",
+      "Acceleration of gravity at surface level:    9.7913 m/s²\n",
+      "Acceleration of gravity at  10.000 km (ASL): 9.7649 m/s²\n",
+      "\n",
+      "\n",
+      "Launch Site Details\n",
+      "\n",
+      "Launch Site Latitude: 32.99025°\n",
+      "Launch Site Longitude: -106.97500°\n",
+      "Reference Datum: SIRGAS2000\n",
+      "Launch Site UTM coordinates: 315468.64 W    3651938.65 N\n",
+      "Launch Site UTM zone: 13S\n",
+      "Launch Site Surface Elevation: 1400.0 m\n",
+      "\n",
+      "\n",
+      "Atmospheric Model Details\n",
+      "\n",
+      "Atmospheric Model Type: custom_atmosphere\n",
+      "custom_atmosphere Maximum Height: 10.000 km\n",
+      "\n",
+      "\n",
+      "Surface Atmospheric Conditions\n",
+      "\n",
+      "Surface Wind Speed: 4.69 m/s\n",
+      "Surface Wind Direction: 219.81°\n",
+      "Surface Wind Heading: 39.81°\n",
+      "Surface Pressure: 856.02 hPa\n",
+      "Surface Temperature: 279.07 K\n",
+      "Surface Air Density: 1.069 kg/m³\n",
+      "Surface Speed of Sound: 334.55 m/s\n",
+      "\n",
+      "\n",
+      "Earth Model Details\n",
+      "\n",
+      "Earth Radius at Launch site: 6371.83 km\n",
+      "Semi-major Axis: 6378.14 km\n",
+      "Semi-minor Axis: 6356.75 km\n",
+      "Flattening: 0.0034\n",
+      "\n",
+      "\n",
+      "Atmospheric Model Plots\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x450 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "env = Environment(latitude=32.990254, longitude=-106.974998, elevation=1400)\n",
+    "env.set_atmospheric_model(\n",
+    "    type=\"custom_atmosphere\", wind_u=[(0, 3), (10000, 3)], wind_v=[(0, 5), (10000, -5)]\n",
+    ")\n",
+    "env.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "Vx1dZObwNVFX"
+   },
+   "outputs": [],
+   "source": [
+    "Pro75M1670 = SolidMotor(\n",
+    "    thrust_source=\"../../data/motors/Cesaroni_M1670.eng\",\n",
+    "    dry_mass=1.815,\n",
+    "    dry_inertia=(0.125, 0.125, 0.002),\n",
+    "    nozzle_radius=33 / 1000,\n",
+    "    grain_number=5,\n",
+    "    grain_density=1815,\n",
+    "    grain_outer_radius=33 / 1000,\n",
+    "    grain_initial_inner_radius=15 / 1000,\n",
+    "    grain_initial_height=120 / 1000,\n",
+    "    grain_separation=5 / 1000,\n",
+    "    grains_center_of_mass_position=0.397,\n",
+    "    center_of_dry_mass_position=0.317,\n",
+    "    nozzle_position=0,\n",
+    "    burn_time=3.9,\n",
+    "    throat_radius=11 / 1000,\n",
+    "    coordinate_system_orientation=\"nozzle_to_combustion_chamber\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "D1fyK8u_NVFh"
+   },
+   "outputs": [],
+   "source": [
+    "calisto = Rocket(\n",
+    "    radius=127 / 2000,\n",
+    "    mass=14.426,\n",
+    "    inertia=(6.321, 6.321, 0.034),\n",
+    "    power_off_drag=\"../../data/calisto/powerOffDragCurve.csv\",\n",
+    "    power_on_drag=\"../../data/calisto/powerOnDragCurve.csv\",\n",
+    "    center_of_mass_without_motor=0,\n",
+    "    coordinate_system_orientation=\"tail_to_nose\",\n",
+    ")\n",
+    "\n",
+    "rail_buttons = calisto.set_rail_buttons(\n",
+    "    upper_button_position=0.0818,\n",
+    "    lower_button_position=-0.618,\n",
+    "    angular_position=45,\n",
+    ")\n",
+    "\n",
+    "calisto.add_motor(Pro75M1670, position=-1.255)\n",
+    "\n",
+    "nose_cone = calisto.add_nose(length=0.55829, kind=\"vonKarman\", position=1.278)\n",
+    "\n",
+    "fin_set = calisto.add_trapezoidal_fins(\n",
+    "    n=4,\n",
+    "    root_chord=0.120,\n",
+    "    tip_chord=0.060,\n",
+    "    span=0.110,\n",
+    "    position=-1.04956,\n",
+    "    cant_angle=0.5,\n",
+    "    airfoil=(\"../../data/calisto/NACA0012-radians.csv\", \"radians\"),\n",
+    ")\n",
+    "\n",
+    "tail = calisto.add_tail(\n",
+    "    top_radius=0.0635, bottom_radius=0.0435, length=0.060, position=-1.194656\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from rocketpy import Accelerometer, Gyroscope\n",
+    "accel_noisy_nosecone = Accelerometer(sampling_rate=100,\n",
+    "                  consider_gravity=False,\n",
+    "                  orientation=(60,60,60),\n",
+    "                  measurement_range=70,\n",
+    "                  resolution=0.4882,\n",
+    "                  noise_density=0.05,\n",
+    "                  random_walk=0.02,\n",
+    "                  constant_bias=1 ,\n",
+    "                  operating_temperature=25,\n",
+    "                  temperature_bias=0.02,\n",
+    "                  temperature_scale_factor=0.02,\n",
+    "                  cross_axis_sensitivity=0.02,\n",
+    "                  name='Accelerometer in Nosecone'\n",
+    "                )\n",
+    "accel_clean_cdm = Accelerometer(sampling_rate=100,\n",
+    "                  consider_gravity=False,\n",
+    "                  orientation=[[0.25, -0.0581, 0.9665],\n",
+    "                               [0.433, 0.8995, -0.0581],\n",
+    "                               [-0.8661, 0.433, 0.25]\n",
+    "                               ],\n",
+    "                  name='Accelerometer in CDM'\n",
+    "                  )\n",
+    "calisto.add_sensor(accel_noisy_nosecone, 1.278)\n",
+    "calisto.add_sensor(accel_clean_cdm, -0.10482544178314143)#, 127/2000)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Identification of the Sensor:\n",
+      "\n",
+      "Name:                      Accelerometer in Nosecone\n",
+      "Type:                      Accelerometer\n",
+      "\n",
+      "Orientation of the Sensor:\n",
+      "\n",
+      "Orientation:               (60, 60, 60)\n",
+      "Normal Vector:             (0.9665063509461097, -0.05801270189221941, 0.2500000000000002)\n",
+      "Rotation Matrix:\n",
+      "                           [0.25, -0.06, 0.97]\n",
+      "                           [0.43, 0.9, -0.06]\n",
+      "                           [-0.87, 0.43, 0.25]\n",
+      "\n",
+      "Quantization of the Sensor:\n",
+      "\n",
+      "Measurement Range:         -70 to 70 (m/s^2)\n",
+      "Resolution:                0.4882 m/s^2/LSB\n",
+      "\n",
+      "Noise of the Sensor:\n",
+      "\n",
+      "Noise Density:             (0.05, 0.05, 0.05) m/s^2/√Hz\n",
+      "Random Walk:               (0.02, 0.02, 0.02) m/s^2/√Hz\n",
+      "Constant Bias:             (1, 1, 1) m/s^2\n",
+      "Operating Temperature:     25 °C\n",
+      "Temperature Bias:          (0.02, 0.02, 0.02) m/s^2/°C\n",
+      "Temperature Scale Factor:  (0.02, 0.02, 0.02) %/°C\n",
+      "Cross Axis Sensitivity:    0.02 %\n",
+      "Identification of the Sensor:\n",
+      "\n",
+      "Name:                      Accelerometer in CDM\n",
+      "Type:                      Accelerometer\n",
+      "\n",
+      "Orientation of the Sensor:\n",
+      "\n",
+      "Orientation:               [[0.25, -0.0581, 0.9665], [0.433, 0.8995, -0.0581], [-0.8661, 0.433, 0.25]]\n",
+      "Normal Vector:             (0.9665010341566599, -0.05810006216709978, 0.25000026750042936)\n",
+      "Rotation Matrix:\n",
+      "                           [0.25, -0.06, 0.97]\n",
+      "                           [0.43, 0.9, -0.06]\n",
+      "                           [-0.87, 0.43, 0.25]\n",
+      "\n",
+      "Quantization of the Sensor:\n",
+      "\n",
+      "Measurement Range:         -inf to inf (m/s^2)\n",
+      "Resolution:                0 m/s^2/LSB\n",
+      "\n",
+      "Noise of the Sensor:\n",
+      "\n",
+      "Noise Density:             (0, 0, 0) m/s^2/√Hz\n",
+      "Random Walk:               (0, 0, 0) m/s^2/√Hz\n",
+      "Constant Bias:             (0, 0, 0) m/s^2\n",
+      "Operating Temperature:     25 °C\n",
+      "Temperature Bias:          (0, 0, 0) m/s^2/°C\n",
+      "Temperature Scale Factor:  (0, 0, 0) %/°C\n",
+      "Cross Axis Sensitivity:    0 %\n"
+     ]
+    }
+   ],
+   "source": [
+    "accel_noisy_nosecone.prints.all()\n",
+    "accel_clean_cdm.prints.all() # should have the same rotation matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gyro_clean = Gyroscope(sampling_rate=100)\n",
+    "gyro_noisy = Gyroscope(sampling_rate=100, \n",
+    "              orientation=(180, 0, 0),\n",
+    "              acceleration_sensitivity=0.02,\n",
+    "                  measurement_range=70,\n",
+    "                  resolution=0.4882,\n",
+    "                  noise_density=0.05,\n",
+    "                  random_walk=0.02,\n",
+    "                  constant_bias=1 ,\n",
+    "                  operating_temperature=25,\n",
+    "                  temperature_bias=0.02,\n",
+    "                  temperature_scale_factor=0.02,\n",
+    "                  cross_axis_sensitivity=0.02,\n",
+    "                  )\n",
+    "calisto.add_sensor(gyro_clean, -0.10482544178314143+0.5, 127/2000)\n",
+    "calisto.add_sensor(gyro_noisy, 1.278-0.4, 127/2000-127/4000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "calisto.draw(plane=\"xz\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "calisto.draw(plane=\"yz\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def controller_function(\n",
+    "    time, sampling_rate, state, state_history, observed_variables, air_brakes, sensors\n",
+    "):\n",
+    "    # state = [x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz]\n",
+    "    altitude_ASL = state[2]\n",
+    "    altitude_AGL = altitude_ASL - env.elevation\n",
+    "    vx, vy, vz = state[3], state[4], state[5]\n",
+    "\n",
+    "    # Get winds in x and y directions\n",
+    "    wind_x, wind_y = env.wind_velocity_x(altitude_ASL), env.wind_velocity_y(\n",
+    "        altitude_ASL\n",
+    "    )\n",
+    "\n",
+    "    # Calculate Mach number\n",
+    "    free_stream_speed = ((wind_x - vx) ** 2 + (wind_y - vy) ** 2 + (vz) ** 2) ** 0.5\n",
+    "    mach_number = free_stream_speed / env.speed_of_sound(altitude_ASL)\n",
+    "\n",
+    "    # Get previous state from state_history\n",
+    "    previous_state = state_history[-1]\n",
+    "    previous_vz = previous_state[5]\n",
+    "\n",
+    "    # If we wanted to we could get the returned values from observed_variables:\n",
+    "    # returned_time, deployment_level, drag_coefficient = observed_variables[-1]\n",
+    "\n",
+    "\n",
+    "    # Check if the rocket has reached burnout\n",
+    "    accelerometer = sensors[0]\n",
+    "    if accelerometer.measurement[2] > 0:\n",
+    "        return None\n",
+    "\n",
+    "    # If below 1500 meters above ground level, air_brakes are not deployed\n",
+    "    if altitude_AGL < 1500:\n",
+    "        air_brakes.deployment_level = 0\n",
+    "\n",
+    "    # Else calculate the deployment level\n",
+    "    else:\n",
+    "        # Controller logic\n",
+    "        new_deployment_level = (\n",
+    "            air_brakes.deployment_level + 0.1 * vz + 0.01 * previous_vz**2\n",
+    "        )\n",
+    "\n",
+    "        # Limiting the speed of the air_brakes to 0.2 per second\n",
+    "        # Since this function is called every 1/sampling_rate seconds\n",
+    "        # the max change in deployment level per call is 0.2/sampling_rate\n",
+    "        max_change = 0.2 / sampling_rate\n",
+    "        lower_bound = air_brakes.deployment_level - max_change\n",
+    "        upper_bound = air_brakes.deployment_level + max_change\n",
+    "        new_deployment_level = min(max(new_deployment_level, lower_bound), upper_bound)\n",
+    "\n",
+    "        air_brakes.deployment_level = new_deployment_level\n",
+    "\n",
+    "    # Return variables of interest to be saved in the observed_variables list\n",
+    "    return (\n",
+    "        time,\n",
+    "        air_brakes.deployment_level,\n",
+    "        air_brakes.drag_coefficient(air_brakes.deployment_level, mach_number),\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "air_brakes = calisto.add_air_brakes(\n",
+    "    drag_coefficient_curve=\"../../data/calisto/air_brakes_cd.csv\",\n",
+    "    controller_function=controller_function,\n",
+    "    sampling_rate=10,\n",
+    "    reference_area=None,\n",
+    "    clamp=True,\n",
+    "    initial_observed_variables=[0, 0, 0],\n",
+    "    override_rocket_drag=False,\n",
+    "    name=\"AirBrakes\",\n",
+    "    controller_name=\"AirBrakes Controller\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# air_brakes.all_info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "v__Ud2p2NVFx"
+   },
+   "outputs": [],
+   "source": [
+    "test_flight = Flight(\n",
+    "    rocket=calisto,\n",
+    "    environment=env,\n",
+    "    rail_length=5.2,\n",
+    "    inclination=85,\n",
+    "    heading=0,\n",
+    "    time_overshoot=False,\n",
+    "    terminate_on_apogee=True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_flight.altitude()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# get first column of every row as time from [(time,(ax,ay,az)),...] = a.measured_values\n",
+    "time1, ax, ay, az = zip(*accel_noisy_nosecone.measured_values)\n",
+    "time2, bx, by, bz = zip(*accel_clean_cdm.measured_values)\n",
+    "\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(time1, ax, label='Noisy Accelerometer')\n",
+    "plt.plot(time2, bx, label='Clean Accelerometer')\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.plot(time1, ay, label='Noisy Accelerometer')\n",
+    "plt.plot(time2, by, label='Clean Accelerometer')\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.plot(time1, az, label='Noisy Accelerometer')\n",
+    "plt.plot(time2, bz, label='Clean Accelerometer')\n",
+    "plt.legend()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 4.0)"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "abs_a = (np.array(ax)**2 + np.array(ay)**2 + np.array(az)**2)**0.5\n",
+    "abs_b = (np.array(bx)**2 + np.array(by)**2 + np.array(bz)**2)**0.5\n",
+    "plt.plot(time1, abs_a, label='noisy')\n",
+    "plt.plot(time2, abs_b, label='clean')\n",
+    "plt.legend()\n",
+    "plt.xlim(0,4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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OknyIHEp6dZ0QQojSTZIPkYOkHkIIIdxJkg+RQ9aKD+l8KoQQwtUk+RA5ZE04pAVGCCGEq0nyIYQQwqM0Gg2LFi3ydhjCiyT5EDkppw+FECJf8fHxPPnkk9SsWROTyUS1atXo3bs3K1as8HZoTsXGxjJ06FCio6MxmUxUqVKFLl26MGvWLDIyMrwdXpklk4yJHLImHDLyRQhRUHFxcXTo0IGQkBCmTJlCkyZNMJvN/PHHH4wcOZL9+/d7O0QHmzdvpmvXrjRq1IipU6dSv359ALZu3crUqVNp3LgxzZo1K9Kx09PTMRqNrgy3TJGaD5GDQ4dTyT2EEAU0YsQINBoNmzdvpn///tStW5dGjRoxZswYNm7cmOvrjh8/zr333ktISAhhYWH06dOHuLg4+/YtW7bQrVs3KlasSHBwMLfccgvbt293OIZGo+F///sfd911F35+ftSpU4dffvkl13MqpRgyZAh169Zl3bp19O7dmzp16lCnTh0GDBjA33//TdOmTQHo3Lkzo0aNcnh9QkICRqPRXqNTvXp1Jk6cyEMPPURQUBCPPvooAPPnz6dRo0aYTCaqV6/Oe++953Cczz77jDp16uDj40NERAR33323fZvVauWdd96hdu3amEwmoqOjefPNN+3bd+/eTefOnfH19aVChQo8+uijJCcn27cPGTKEvn378vrrrxMeHk5QUBCPP/446enpDueYNGkSNWrUwNfXl2bNmvHTTz/l+r65TL7r3npYYZbkFe5x6tIVFfPCYhXzwmJ17HyKt8MRotzJsWy51apUWrJ3blZrgWI+f/680mg06q233sp3X0AtXLhQKaVUenq6atCggRo6dKjatWuX2rt3rxo4cKCqV6+eSktLU0optWLFCvX999+rffv2qb1796phw4apiIgIlZSU5HDMqlWrqtmzZ6uDBw+q0aNHq4CAAHX+/HmnMWzfvl0Bas6cOfnGO2vWLBUaGqpSU1PtZe+//76qXr26sl57f2JiYlRQUJB69913VWxsrIqNjVVbt25VWq1WTZgwQR04cEBNnz5d+fr6qunTpyullNqyZYvS6XRq9uzZKi4uTm3fvl199NFH9nM8//zzKjQ0VM2YMUPFxsaqtWvXqq+++koppVRycrKqXLmy6tevn9q9e7dasWKFqlGjhho8eLD99YMHD1YBAQHqvvvuU3v27FGLFy9W4eHh6sUXX7Tv88Ybb6j69eurpUuXqkOHDqnp06crk8mkVq1a5fS9yPHZzKIw129JPkQOJy9eTz6OnpPkQwhPy/EFn5as1KtB3rmlJRco5k2bNilALViwIN99syYf33//vapXr579Iq6UUmlpacrX11f98ccfTl9vsVhUYGCg+vXXXx2O+fLLL9ufJycnK0D9/vvvTo/xww8/KEBt377dXnbmzBnl7+9vv02dOlUpZft9hIaGqrlz59r3bdq0qXrttdfsz2NiYlTfvn0dzjFw4EDVrVs3h7LnnntONWzYUCml1Pz581VQUJBDEpUpKSlJmUwme7KR3ZdffqlCQ0NVcvL138+SJUuUVqtV8fHxSilb8hEWFqZSUq5/j0+bNk0FBAQoi8WiUlNTlZ+fn1q/fr3DsYcNG6YGDBjg9LyuSj6k2UXk4NDnQ7qcCiEKQBWxjXbnzp3ExsYSGBhIQEAAAQEBhIWFkZqayqFDhwA4c+YMw4cPp06dOgQHBxMUFERycjLHjh1zOFZmMwmAv78/QUFBnD17tsCxVKhQgR07drBjxw5CQkLszRM+Pj48+OCDfPPNNwBs376dPXv2MGTIEIfXt27d2uH5vn376NChg0NZhw4dOHjwIBaLhW7duhETE0PNmjV58MEHmTVrFleuXLG/Ni0tjS5dujiNdd++fTRr1gx/f3+HY1utVg4cOGAva9asGX5+fvbn7du3Jzk5mePHjxMbG8uVK1fo1q2b/b0PCAjgu+++s7/37iIdTkUOWb9EpM+HECWAwQ9ePOW9cxdAnTp10Gg0he5UmpycTKtWrZg1a1aObeHh4QAMHjyY8+fP89FHHxETE4PJZKJ9+/YOfRcADAaDw3ONRoPVas01XoADBw7QokULAHQ6HbVr1wZAr3e8PD7yyCM0b96cEydOMH36dDp37kxMTIzDPlkTgYIIDAxk+/btrFq1ij///JPx48fz2muvsWXLFnx9fQt1rKLI7B+yZMkSqlSp4rDNZDK59dxS8yFyUDLUVoiSRaMBo793bhpNgUIMCwujR48eTJ06lZSUlBzbL1265PR1LVu25ODBg1SqVInatWs73IKDgwFYt24do0eP5rbbbrN33jx37lyR306AFi1aUL9+fd59991cE5SsmjRpQuvWrfnqq6+YPXs2Q4cOzfc1DRo0YN26dQ5l69ato27duuh0OsCW5HTt2pV33nmHXbt2ERcXx19//UWdOnXw9fXNdYhygwYN2Llzp8N7vW7dOrRaLfXq1bOX7dy5k6tXr9qfb9y4kYCAAKpVq0bDhg0xmUwcO3Ysx3tfrVq1fH++4pDkQ+SpqFWpQojyZ+rUqVgsFtq0acP8+fM5ePAg+/bt4+OPP6Z9+/ZOXzNo0CAqVqxInz59WLt2LUeOHGHVqlWMHj2aEydOALZaiu+//559+/axadMmBg0aVOyaAY1Gw/Tp0zlw4AAdOnTgl19+4eDBg+zdu5fPP/+chIQEe4KQ6ZFHHmHy5MkopbjrrrvyPcczzzzDihUrmDhxIv/99x/ffvstn376Kc8++ywAixcv5uOPP2bHjh0cPXqU7777DqvVSr169fDx8eGFF17g+eeftzeDbNy4ka+//tr+vvn4+DB48GD27NnDypUrefLJJ3nwwQeJiIiwx5Cens6wYcPYu3cvv/32G6+++iqjRo1Cq9USGBjIs88+y9NPP823337LoUOH2L59O5988gnffvttsd7ffOXbK8TDpMOp9x09l2LvcBp79rK3wxGi3MmrU19Jd+rUKTVy5EgVExOjjEajqlKlirrzzjvVypUr7fuQpcOpUkqdPn1aPfTQQ6pixYrKZDKpmjVrquHDh9uvA9u3b1etW7dWPj4+qk6dOmrevHkqJiZGffDBB7keUymlgoOD7SNLcnPgwAE1ePBgVbVqVaXX61VwcLDq2LGj+uKLL5TZbHbY9/Lly8rPz0+NGDEix3Gyx5Ppp59+Ug0bNlQGg0FFR0erKVOm2LetXbtW3XLLLSo0NFT5+vqqpk2bOnRqtVgs6o033lAxMTH212cdTbRr1y516623Kh8fHxUWFqaGDx+uLl++/p09ePBg1adPHzV+/HhVoUIFFRAQoIYPH+4wasdqtaoPP/xQ1atXTxkMBhUeHq569OihVq9e7fT9clWHU41SJetf26SkJIKDg0lMTCQoKMjb4ZRLR8+ncMuUVQAsH3MLtSsFeDcgIcqZ1NRUjhw5Qo0aNfDx8fF2OOKauLg4atWqxZYtW2jZsqW3w8nXkCFDuHTpkkunss/rs1mY67d0OBVCCCHyYDabOX/+PC+//DLt2rUrFYlHSSd9PkQOjnVhJapiTAghPG7dunVUrlyZLVu28Pnnn3s7nDJBaj5EDo5ru3gtDCGEKBE6depUKjvfz5gxw9sh5EpqPkQOWf/ISt+fmxBCiJJOaj7KoM9XH2Le1uPMfaw9FQNM3DhpBacSUwGIDvNj6sCWNKkazHPzdnL0whXmDG+HTnt9LL/UfAghhHAnqfkogyb/vp9DCSlMXRkLYE88AI5duMLjM7cBMG/bCTYfucD2YxcdXu84yZhkH0J4S2ms6hdlm6s+k5J8lGEWq/MPyVWzJZ/9ZHp1Ibwpc5rwzHU+hCgpMqe0zz4BW2FJs0sZpi3gtMjZEwyHmg9JPoTwOJ1OR0hIiH1RND8/PzQF/HsWwl2sVisJCQn4+fnlWPumsCT5KMPySj4cO5U6Zhiyqq0Q3hcZGQlQqFVZhXA3rVZLdHR0sZNhST7KMJ029/Y55Zhh5LpNaj6E8A6NRkPlypWpVKkSZrPZ2+EIAYDRaESrLX6PDUk+yrBjF66Q4aTfx4WUdC5eub4Udc4eH5JxCFFS6HS6YrevC1HSSIfTMmb53jP2x3/8e4bvNhx1ul+rN5bbH1ulekMIIYQHSfJRxsxYH+fwfMof+/N9jXQ4FUII4UmSfJQx2ZtMUs3WArwm23OZ50MIIYQbSfIhcnRKVTLPhxBCCDeS5KOM0VD44U9513wIIYQQriXJRxmT26ymecrjJTK9sxBCCFfTqBJ2dUlKSiI4OJjExESCgoK8HU6psv3YRfp9tr5Ir21aNRh/o55alfyZufGYw7Y7mlamVUwoD7aLQa+7nq+uP3SOpKtmejauXKy4hRBClH6FuX7LPB9lSFETD4BdJxIB2HD4fI5ti3edZvGu0wA83KGGvXzgV5sAWDe2M1VCfIt8biGEEOWLNLuIAtt29KLT8nOX0zwciRBCiNJMkg9RYCWrgU4IIURpJcmHKDDHIbiSiQghhCgaST5EgcnMp0IIIVxBkg9RYFnXgMn6WPIQIYQQhSGjXcqIWZucLyDnSn/8e4bqY5fgY9ASHebnsE0pxYsLd1MtzI8RnWq7PRYhhBCllyQfZcRLC/d47FypZiv/nUl2KNt5IpE5m48DSPIhhBAiT9LsUk58NqglXw9u7ZZja4Ar6RluObYQQoiyR5KPcsKg09KlQYS3wxBCCCEKl3xMmjSJG264gcDAQCpVqkTfvn05cOCAwz6pqamMHDmSChUqEBAQQP/+/Tlz5oxLgxaFV6Q1X4QQQgg3KFTysXr1akaOHMnGjRtZtmwZZrOZ7t27k5KSYt/n6aef5tdff2XevHmsXr2aU6dO0a9fP5cHLgrHncmHpDVCCCEKo1AdTpcuXerwfMaMGVSqVIlt27bRsWNHEhMT+frrr5k9ezadO3cGYPr06TRo0ICNGzfSrl0710Uu7FLNlnz3sbhxYg6LVXE59XqfD6tVodVqsFiVfUiuXqtBo9G4LQYhhBClR7FGuyQm2hYjCwsLA2Dbtm2YzWa6du1q36d+/fpER0ezYcMGp8lHWloaaWnX1wZJSkoqTkjlzuu//sv0dXH57ufOGUn7T3Nc0G7x7tPc1jiSm95eSXxSKgAd64bz3dA2botBCCFE6VHkDqdWq5WnnnqKDh060LhxYwDi4+MxGo2EhIQ47BsREUF8fLzT40yaNIng4GD7rVq1akUNqVxylnjc1aIKnetXokqIL7c3rUydSgH0aBQJwDt3NyXIR0/ragF00u5glG4hY/VzGKJbSkNNHK5oRBk95x8OJaTYEw+ANf8lFPu4QgghyoYi13yMHDmSPXv28PfffxcrgHHjxjFmzBj786SkJElAiumD+5rnuu3e1tW4NzQWfn0SjDknJtttrc4nGXcxadxYjl68Sr/P1js5Sv7MFmuRXieEEKLsK1LyMWrUKBYvXsyaNWuoWrWqvTwyMpL09HQuXbrkUPtx5swZIiMjnR7LZDJhMpmKEoYoin8Xwk/DQFnAryLU6QY+IXDhMNbDq2hCHF8aP8D8ywEMbd4q8mnSJfkQQgiRi0IlH0opnnzySRYuXMiqVauoUaOGw/ZWrVphMBhYsWIF/fv3B+DAgQMcO3aM9u3buy5qUTRn9sLCx22JR5N74I4PwRRg37z134NsmTOB4bolGA/+Rt343dTTjOSAii70qTIsMgZGCCGEc4Xq8zFy5EhmzpzJ7NmzCQwMJD4+nvj4eK5evQpAcHAww4YNY8yYMaxcuZJt27bx8MMP0759exnp4m1WK/w8AjJSoXZXuOtLh8QDIM0YwpSM++mT/gYqtDqmy8eZZ5xAK82BXA6aO2l2EUIIkZtCJR/Tpk0jMTGRTp06UblyZftt7ty59n0++OAD7rjjDvr370/Hjh2JjIxkwYIFLg+8PFNKsf7QOZbsOl3wF+1dBKf+AWMA9PkMtDl/9RnX5gLZp2LQDF9JcsQNBGmu8L1xMh20uwsV4wvzdzkt3xp3gYTLaew5mchvu09z6tJV+8+08fB5Ll1JL9R5hBBClD6FbnbJj4+PD1OnTmXq1KlFDkrkbevRiwz8alPBX6AUrJlie3zjkxDofJr1IJ8sHwe/MA71/J5L39zLLbpdfGOYwiPmZ1lrbVqgU564eDVH2frYcwz8X8644ybfzuJdp3lyzj9UCjSx+aWuOfYRQghRdsjaLqXQvtO5z4UyfcgNOQuPb4Kze0HvC20fz/W1LaNDefyWWrxz97UEQ+/LcPMz/GFpjUmTwVeG92in3VvkuP/afzbXbX/8axuKffZyWq77CCGEKBsk+SiFcuvMadJrubV+pZwbtn5ju29yN/iG5HpcjUbD2F71ubf19aHO6RgYZR7NCksLfDRmvjZMKVIfELjerOOMTiuznwohRHkhyUcplNs6LUadk19nWjLs/dn2uPXDRTqfGT0jzP/HGksT/DVpzDC+QzNNbKGPk9fwW51MvS6EEOWGJB+lUG41CFpntQexy2wjXEJrQFTLIp8zDSOPmsewwdKQQM1VvjNOppEmrlDHMGc4Tz4s19aCEUIIUT5I8lEKWazOL+J6Zxfwvb/Y7hveCcWsXUjFxDDzs2y11iVYc4XvjJOoozlR4NfnNvw2PcMqNR9CCFGOSPJRCi3f57zjZo7aA3MqHPzT9rjBnYU+j7P6lSv48HD68+y01qSC5jKzjG9RXVOwIb+LdpxyWt5g/FLmb887iVkfe473/jxAhswfIoQQpZ4kH6XQjuOXnJbf1aKKY8GRNZCeDIFRRWpyiQr2yVEWYNJzGT8eSh/LPms0lTSXmG18k6qa3EeyFERenVEBBv5vE5/8FZtvkiKEEKLkK/LCcqJkeaxjTcZ0r+tYeHil7b5ON6eTiuWnUpAPcx9tR4CPHqUgJS2DWpUCWLLrNG/+to8H0scx1ziR2tpTzDa8yfNBb1O9Rh1+2HLcBT+Rc87mDxFCCFG6SM1HGfF0t7qY9DrHwsOrbPc1OxX5uG1rVqBRVDCNqwTTtmYFKgaYGHxjdXo1juQ8wQxMf4k4awTR2gR+ML3F2JtCi3yugtBK3xAhhCj1JPkoI3IMs70cb5tYDA3UuMXl58tsJjlLKIPSX+Q0FeF8LIE/3UMouU+CVlxOO9UKIYQoVST5KGVym+I+R2fTw6tt95Wbgn8Fl8eRtePnScJ5Qv86BESiS9jH98bJBJHi8nMC6HSSfAghRGknyUcpk9dEXQ7sTS63uiWO7LOsntREwuBfUH4VaayNY4bxbfxxff8MGZIrhBClnyQfpcDmIxfo8cEaNh0+z/nkAq76GrfWdl/T9U0uAGZno1PC65HxwEIuKX9aamP5xjgFP1ILfezqY5dQfewS5mw+Ro8P1jDp9332bTqthh82H6PXR2s5nSidT4UQojSS5KMUuPeLDRw4c5n7vtzIwbPJObY3igpyLEg8AYnHQaODqm3cEtOTnWs7PH/9zkYA6Cs34cH0cSQpX9pq9xerBmTcgt0cOHOZL1YftpdpNRrGLtjNvtNJvPXb/qL/AEIIIbxGhtqWMulOpij/eWQHx4JjG233kY3BFOCWOG6oHsbOV7sT5KMnKTWDYF8DYFuc7qZbuvHgaivfGyfTRnuAGca3GZL+Ain45jhO94YR7Dh+qcCr2Wbt2pKcanbJzyKEEMKzpOajlEnLsOQo02cf6XJ8k+2+Wju3xhLsa0Cj0dgTj0wmvZadqjYPpI8jSflxg/Y/vjW+TQBXchwj0MdAxQBTgc+pydLnI5fFfYUQQpRwknyUMs5qPnLIrPmIbuveYHKhwZYg7FK1GJT+IonKj9a5JCBKKUyGgn8Ms/Y3zW3kjxBCiJJNko9SJt/kIy0ZzuyxPXZzzUdusjaN7FY1GZj+EpeUP620B/nOOJnALAmIwskcJXnImm9YJfkQQohSSZKPUmb7sYt573ByKygrBFeD4Cp57+sm2UfD/qtqMCj9RfsomKwJiFIKo77gH8PYLB1ur6ZbOJOUitWqOBB/mWPnczbrXLqSTqo5Z1OVEEII75EOp6XMj1vzWVjtWGZ/D+80uQD4m3J+rGwJyEvMNL5FC20s3xsn8VD6CwT6GEhOyyjwsb/feNT+ePuxS7R9a4XD9tmPtOXG2hUBuJiSTouJywjzN7L9lW5F/GmEEEK4mtR8lGItokOY/0R7x8Ljmf09vNPkAjCgTTQdalcgzN/ILXXDWf1cJwD+VdUZmP4SF1QAzbWHmGN8kzEdwhw6kRbXl2uvD8vddtRWS3QhpYBzowghhPAIqfkopaqG+rJwRLYhtlYLHN9ie+zFmg8fg45ZjzgmP3GTbwdg7PxdDNj6MjONk2ikPQo/3kWQzwSXnduSZfKzDGsBZ4MVQgjhUVLzUZac3Qvpl8EYCBGNvB2NU0rBARXNfemvcF5bERL28/zpp4ninEuOn7VDrlnG4gohRIkkyUdZkjnEtmpr0Oq8G0s+Dqso3qj0HoTEEJFxkh9NE4jRxBf7uGlZkg+LsynghRBCeJ0kH2XJia22ey82ueQna/eOc4bK8PDvxBuqUlVzjh+NE6ityadDbT7MFqvTx0IIIUoOST5KKadTXJy8lnxUbe3RWAojR9zBVXin8gfss1YjQnOJucaJNNTEFfn4/55KYtvRC3y84iDP/bTLXt7xnZUs2H6C1f8lsOifk8zfdsJeM2KxKhZsP+F0qK4QQgjXkw6npVTbGmGOBVcvwvlY2+MqrTwfUAE1qBxof9ysaggAmxP0/JX+Mt8a36aZ9jBzjG8wOH0sO1TtXI6St/7TNuQoO3bhCmN+3OlQdsVs4cF2MczdcpwXF+4GrneMFUII4T5S81FKvXpntg6lJ7fZ7kNrgF9YzheUEIPaxdC7WRTdGkYw6trKuGaLlUsE8kD6i+zQ1CdYc4VZprcYWz+BjnXD3RbL5iMXANhw+LzbziGEECInST5KqeyLuXFyu+2+BDe5ABh0Wj4Z0IKvHmqNj8HWKTaza8Zl/Gg+7i+ocQv+pPL48ef5rv1Zt8WSOQ28TNMuhBCeJclHCVfgERuZnU2rlOzkwxlL1vk4jP4w8EeofwdY0uDHB7lHt8ot59Vm9n6V3EMIITxKko8SztlCcjptthlBlbre2bQE9/fITUb2BMvgA/d8Cy0eAGVliuFLHtEtcfl5M5MPqfkQQgjPkuSjhCtQ8nHpKFw5D1oDRDbxUGSuY3VWu6PTw52fwo1PAvCyYRbP63/AldUUmYvpSvIhhBCeJclHCXfgzOUcZbrsa6FkNrlENrHVGpQyOWo+Mmk00P0NJpkHADBC/wtv6f+HFtfM3/Hj1hNUH7uEVPP141Ufu4T1h5zPtvrO0v1MXRnrknMLIUR5JslHCbf2YEKOssdvqeVYkDnSpRQ2ucD1n+fOZlFOt39h6c0L5uFYlIaB+pV8avgYI2aXnX/1f47v8cCvNuXY5+Slq3y26hBT/jggM6cKIUQxyTwfJVz2JoGfHm9Pi+hQx50yk48SPtIlN6O71OGWeuE0jgp2un3Xa935dWdjzlpaE7n8SW5jM60itBzoNI2HZu7zSIzp2aZtz9H0JYQQosAk+SjhsjZJ9GwUSevq2ebwsJjh9LXJs0rhSBew9WFpmT2hyiLIx8CgtjFADEREwA+DiDi3kYj1wwjjUS4Q5PYYs+YaUvMhhBDFI80uJVzWzphOO0ae2QMZqeATDBVq5dxe1tS6FQb/Cr5hcGo7Pxlfo5rmjNtPq83SzybDKmvGCCFEcUjyUcJlrflw+v921v4e2TuillVVW8HQPyA4mpraeBYYX6Wx5rBbT5n1rZXcQwghikeSjxLKalVYrt0yKWc1Hycyk4/S2eRSZOF14ZFl/GuNIVyTxFzjRG7R7sz/dQWU+d6nZ1hzDAU2W21lTocICyGEyJf0+SiB9p1OotdHa3OUO73WlYKVbN0mMJL70l9hmuFDbtbt4WvDFMZmDOcnyy3FPnStF3/Lddsj325lx/FL+Bp0fDPkBtrXqlDs8wkhRHkiNR8l0MuL9jgtf+n2Bo4FqYlw7j/b41I6zLa4+rdvwFDz8yyw3IReY+VdwxeM0i0ks5HKqHf9R3zH8UsAXDVbGP7dVpcfXwghyjpJPkogZ6MposP8qBUe4FiYuZhcSAz4V/RAZCXP630as/+tO7nr9V/hpqcBeNYwj7f0X6PDwspnO/Fy9qTNhcpJLxshhHApaXYpJfQ6J5e58tzkkoVtzg0NdH0NgqqgfnuOgfq/CNdcwmC5yWGkistJ9iGEEIUmNR+lhN7ZpFaZNR/ltMnFqTbDOX/7/0hVBrrpthP20934pF9w2+kk9xBCiMKT5KOU0Gmz/aqUur6mS3kb6ZKPKzVvY1D6i1xS/uhPb+OOLQ9RU3PKLefSlJfhzUII4UKSfJQSOWo+Eo9DylnQ6qFyU+8EVUJZlWKbqkf/9NewhsQQdPUEC4yv0k671+XnSrxqW2MmOS2Dnccv2YdDJ1xOY/uxiw5lV9Iz+OfYRedDpoUQohyR5KMEcnZpql7R37Egs9YjojEYfN0eU2liMtg+1odUFTIeXsaF0GaEaFL4zjCJu3WrXX6+VLOFOz/9mz5T1/HnXttsqze8uZx+n62nz9R1LN0TD8CALzdy12frmbf1hMtjEEKI0kSSjxLIWfeOV3s3dCw4Jf09clM52JcnO9fmuR71MAZHEPTY7/wT1BmjxsK7hi94v8Iv3NaoEm1qhNEm+1o5RZB01czhhBQAFv1zMsf2hdfKdp5IBODHrceLfU4hhCjNZLRLCaRz0o+gYoDJseDUDtt9lZbuD6gUeqZ7PftjvY8/LZ6aDyvfgLXv0S/lB/r5pMP9n4HBl4NnLtPtgzVFPpc2S7ZotuSst8q+Jo80ugghyjup+SiB8h0aarVeTz6iWrg9njJBq4Uu46HPVFs/mX8XwLd3Qso55zPHFkLW5MJsybnwS0a2EzhdIFAIIcoRST5KoOwDW3K4cAjSL4PeFyrWy2dn4aDFA/DgQtsqwCc2w1ed0Z47UKxDZp0UzlnykX3SOMk9hBDlnSQfJZDOWaePrE79Y7uv3BR00nJWaDU6wrDlEFodLh2lxi99uUm7u8iHy5pcZDhpdsmRfBT5TEIIUTbIlasEORB/mWmrYlkXez7vHTOTD2lyKbrwuvDICvhhIPrjm5hheJs3Mh5ghqUHhZ067Ka3V9ofb467wPR1Rxy2rz90nomLrw/z3Xn8Evd/uYGKASY0Gg3Pdq9LTIXro5l+2nYCDXDy0lU6169E4yrBRfoRhRCipNKoEjbpQFJSEsHBwSQmJhIUFOTtcDyq10dr2Xc6KUd5n+ZRfHR/lkTjm55wbAPc9QU0u9+DEZZB5lRS5o/Cf/88AH7I6MQrGUMxezAvD/M3sv2VboBtfpAb3lzusD1u8u0ei0UIIYqqMNdvaXYpQZwlHgDj78gyzNZqgdM7bY+l5qP4DD743/cVsc3HotByv34VPwe8zdQ+VT0WwoWUdPvjpFSzx84rhBDeIslHCedn1FEh6zDbc/+B+QoYA6BCbe8FVpZoNNTuOw7NoB/BFETDjH+5feMgGmriPB5KCauIFEIIt5Dko7SxdzZtBlqdd2Mpa+p0s/UDCasFicf5yfg6PbWbPRpCcYf9CiFEaSDJRwmXo+ujdDZ1r/C6MHwF1LwVP00anxs/5P9089GQcwitO8gcIEKI8qDQyceaNWvo3bs3UVFRaDQaFi1a5LB9yJAhaDQah1vPnj1dFW+5k2PVVEk+3M83FAb9xDcZts/t04b5fGr4GF9S3X5qyT2EEOVBobv0p6Sk0KxZM4YOHUq/fv2c7tOzZ0+mT59uf24ymZzuJ67bH++8s6kDixnir81HIcmHe+n0TMh4iP2qGm/ov+F23Waqa87waPoYThLu8tNtOHSepXtO83fsuRzbrFbFs/N24mPU8dZdTVx+biGE8LRCJx+9evWiV69eee5jMpmIjIwsclDlUc8P1zotd6j3SNgPGalgCobQGh6JqzyrGGDkx+RbOWytzOfGD2mkPcovppd5Iv0pNqsGLj3Xy4t2c+ja4nTZLdl9mgXXFqd75faG+Bqlr48QonRzy2QGq1atolKlSoSGhtK5c2feeOMNKlSo4HTftLQ00tLS7M+TkgpQA1Be2ZtcmhVgDnZRXH+/0JlUswWjvgcn4m4jaNkjVEjYw1zfSZzp8DqJjQbT48OiL0iXVW6JB0CG9Xp/E7PVii+SfAghSjeXX8F69uzJd999x4oVK3j77bdZvXo1vXr1wmKxON1/0qRJBAcH22/VqlVzdUilW9aqD+nv4VE+Bh0hfkb8jHrq1m2AcfgyaNwfjTWDyLUvUW/LKxjIcHsc+iyJZnqGZzq+CiGEO7k8+bj//vu58847adKkCX379mXx4sVs2bKFVatWOd1/3LhxJCYm2m/Hjx93dUilmkOzi32YbXMvRCIw+kH/r6HLq4AGtk1nlvFNKpDosRAk+RBClAVur7uvWbMmFStWJDY21ul2k8lEUFCQw004YTHDmWvrg1Ru5t1YyjONBm4eAwPngimINtoD/GJ6mUZunJAs6/DbNEk+hBBlgNuTjxMnTnD+/HkqV67s7lOVSfahtucOgiUNjIHS2bQkqNsDHlnBIWtlqmjO85PxNe7QbnDLqbLWdmQ+TjVbuJpuIcNi5fK1KdkzywASr5hltlQhRIlV6A6nycnJDrUYR44cYceOHYSFhREWFsbrr79O//79iYyM5NChQzz//PPUrl2bHj16uDTwsmTNfwm5bgvyvfYrit9lu49sLJ1NS4rwutyVPoGPDZ/SSbeTT42f0CDjKO9l3IvVhXn9cz/tsj9Oz7BitSpueGM5V8wWYsL8OHwuhS0vdaXzu6tITs9g/hM30u+z9fRoFMEXD7Z2WRxCCOEqhf6G3Lp1Ky1atKBFC1unxzFjxtCiRQvGjx+PTqdj165d3HnnndStW5dhw4bRqlUr1q5dK3N95GHmxqNOy+tHBvLFA9cuHpnze0TKPA8lycNdmjPU/ByfZ9wBwEj9L3xleI9ArrjlfBlWK+kWK5fTMrBYFYfP2UbJrNh3hstpGSgFExfbmuf++PeMW2IQQojiKnTNR6dOnfKszv3jjz+KFVB5lOFkQY+BbaMdJ5TKXMk2sqmHohIF8XS3ujzdrS7Vx2rZZ43mfd+v6cI/7I54h63tp3L3vNxrtYrCqpTTWVCzFklrixCipJP6+xLAWfKRYcnSsVApqfkoBX623sSe7j9AYBSc+4/mS/txi3anS89hVc7Xf8laJrmHEKKkk+SjBLBYc45gyLBkuYQknoDUS6DVQyXXzqwpXCu5QlN4dBVUbYPefJlvDO8wXLcYV6UEFqvC4iz5yJLASkdTIURJJ8lHCWBxUvNhzlqW2dk0vD7ope9MSaYUEBgBQxZzosbd6DSKlwyzed8wDRPpxT6+VSmUk9G2WT8uknsIIUo6ST68zGyxsvHwhRzlDs0u0uRSaqjMGg69id0tJjLePJgMpaWf7m9+NE4ggpy/68IY+NUm/twbn6N8w6HzOWMAxi3YzZX0ws3CmpKWwS87T9mH8AohhKtJ8uFlC7efdFpeu1LA9SenM4fZSmfTki7M32h/XDHIh+8sPXjQPI6LKoBm2sP8anqZlpr/inWOrENvMy3993pCkrUVb87mYzzy7dZCHX/sgt2MnvMPo2b/U+QYhRAiL5J8eNn2YxdzlEUF+zCiU+3rBVLzUeJNG9SSl29vQKOoYHtZ65hQXuhZnytRN7L/zp+5EFCHSppLzDG+wT26VW6LJXury/ostSIF8evOUwCszmP+GSGEKA63rGoriufZHvWuL5t+9SIkHrM9luSjxOrVJOcMvhqNhic61eKJTrVsBY1XwcLHMO1fzBTDlzTUHOXNjEFkuPjPUDqcCiFKOqn5KOkyaz1CosE3xKuhiGIyBcC937Or9hMAPKz/g28NbxPCZS8HJoQQniXJRwnk8I+rvclF+nuUCVotu+s8wWPpT5OiTHTQ/csvxpeppznmslM4mwdECCFKEkk+SjrpbFom/WG9gX7pr3PMGk60NoEFxlfpod3ikmM7G7othBAliSQfXpR41cwPW47nvZN0Ni2zDqho7kx/g3WWRvhr0vjC+AH/p5uPBicTeRTCoYSUHGXVxy7hyzWHGDV7O+tizzl93dI98by8aHexzi2EEAUhyYcXvf/ngbx3MKdCwn7b48pS81FWtIoJtT++RCAPmcfyTUZPAJ42zGea4SP8SHX5ed/6bT+Ld53mse+3Od3++MxtzNzouuYfIYTIjYx28aJjF66vfNqjUYR9FVJ7pXnCPlAW8A2FoCqeD1C4Rf3IIH4e2QGdVsOJi1eIDPYl9mxLdpy8mQbbXqWnbgvVNfEMN4/huIpw+fmT0wo36ZgQQria1Hx4kU57/e0fdlPNnDuc+dd2H9EYNBoPRSU8oVm1EBpXCaZn48o0rxbC3a2qUq3zcAakv8xZFUJ97XF+Mb7Cjdo93g5VCCFcTpIPL9JlefeN+utP7PM0ZE0+RJmn1WjYrurSO+0NdlhrEqpJ5jvDZIboliJr1QohyhJJPrxIp71em2HUOflVnLn2X29EIw9FJEqCM4RxX/p4FlhuQq+x8prhO97Wf4URWWtFCFE2SPLhRVmbXUyGLDUfYJvsw17z0dCzgQmvS8PIGPMTvGEehEVpuE+/ih+MEwkn53T8RaWUcrjlt58QQriKdDj1knWx5+xraICTmo/ks3DlPKCB8AaeDU6UEBr+Z7md/1RVPjF8QkttLL+YXuGx9KfZpWoV68jVxy4p8H56rYYQPyOv3dmQO5pGFeu8QggBUvPhNdnnWogI8qF7wwiCfQ30bBwJZ6/VelSoBUY/L0QoPC3Y10D9yEDqVArg04Et0GigYoCJNdZm9EmfyEFrFSprLjDPOIG+2r89FleGVXEuOU1WuRVCuIzUfHhJ9kkojXotXzzYCotVoddprze5VJIml/JCq9Xw2+ibUdj6A/VsFIlepyXVbEGv1UDa3Syf1Jeuun/40PgZDTKO8nbGAKzyP4QQopSRby0vcbb+hkajsSUeICNdyimtVmPviJz5WfAx6NDrtOj9QhhufoZPM/oA8Jh+CTMMbxNEstfiFUKIopDkw0us+a2/IZ1NhRMKLe9m3MeeGz/gqjLSUbebn42vUEtz0tuhCSFEgUny4SWWvEYPWDIg4drU6zLMVjiREH0H/dNf44SqSA3tGRYZx9NZu93bYQkhRIFI8uEFhxKS+e/M5dx3uHAILGlg8IeQ6h6LS5QiGtirqtMnbSKbrPUJ1Fzlf4b3GKFbhDsnJNt29CJL95xm85ELHE6wNfdYrIp/TyXmX5snhBDXSIdTD9tzMpE7PnEcqRAeaHLcKXNysUoNQCv5ocgpwGT70z1PMA+kv8ir+m95QL+C5w0/0lB7jOfMj3IVH5eft/+09Q7Plz51MzM3HmXmxmOM7lKHMd3quvycQoiyR65sHrZ835kcZd8Pa+NYcGav7V6aXEQ2L95Wn/tvqEbrmFDG32HrD2RGz8sZw3jJPBSrRs8duo38ZHydKiS4PZ5VBxLsK+F+vOKg288nhCgbJPnwML3WcYG4EZ1qUT8yyHEne2dTST6Eo0c71mJy/6ZoNBqG3lSDuMm327fNsnRFO+RXzqkgGmmP8rPpFQZEHCdu8u32W51KAV6MXgghbCT58DBdtmaUDGft5JJ8iKKKuZE+aRP51xpDRU0SExNfhC1f2zfrtK5dHVlmXRdCFIUkHx6WvebDbLE67pCaCIm2amyZYEwUxUnC6Z/+Gr9a2qHHAkvGwK9PQUa665MPWW1XCFEEknx4mDbbl78le83H2X22+8Ao8AvzUFSirEnFxJPmJ5kb9DCggW3T4bs+VCDRpeeRmg8hRFFI8uFh32+Ic3hutmT79pYmF+EyGn4PHQgDfgBjIBxbz3uXnqKR5ojLzjDljwMOz19cuJuZG48yavZ2/vw3ni9WH+Lo+RSXnU8IUTbIUFsPSs+wEnf+ikNZjmYXmdlUFFKbGmFsPnKBm+tUBMDHoCXVbPtcta9ZAeq1geErYM4Awi8cYr7xNcaah7PIepPLY5m96Zj98eJdpwH4aMVB9k7o6fJzCSFKL0k+PChHE4uzMlnTRRTS5w+0YvGuU9zZzLbc/bKnb+Hb9XFUCfXlgXYxtp3C68Hwv7DMfwSf2GV8aPyMJhlHmJQxgCB/Py6kpBMeaCLhcprL47uSbnH5MYUQpZskHx7kbEp1h5oPpeDstTk+pLOpKKAwfyMPta9uf14tzI+X73Dy+fENQTdwLtu/e56Wcf9jmP53GmqO0n7Mr+Bf0b5b9bFLPBC1EKI8kz4fHmTJ3r8DyMhalngc0pJAq4eKMlOkcAOtjm01R/JY+lMkKx/a6/bCF7fAqX+8HZkQohyR5MODnNV8ZFiz1HxkzmxasS7ojR6KSpQ3CsUf1jb0TZ/AYWskJJ2Ar3vAjjneDk0IUU5I8uFBDonGNQ6jXexNLg08FJEoz2JVVfqmT4Q6PWwLGS56HH5/AT0Z3g5NCFHGSZ8PD3LW4dQhIUnYb7sPl+RDuI+G63PNJOFvG4q7ahKseQc2fc5M42pGpo/mPMEuO2fWfiQhfgbev7cZnetHuOz4QojSRWo+PMhZ8jHkxhrXn2ROMFapvociEuVR14bXL/o1w/1tKyd3fgnumwnGANpp9/GL6WWaaA675fyXrpgZOmOrW44thCgdpObDg7ImH3MfbUfFQBO1wq8t9GW1wLn/bI+l5kO4UY2K/mwY15mr6RaqhPpe39CgN1Ssy6FP+lBLe5qfjK/zonkY860dAWgUFcS/p5K8FLUQoiyRmg8PylxELshHT9uaFa4nHgAX4yAjFXQmCKvh/ABCuEjlYF9qhgdg0uscN4TXo2/6RJZbWmDSmHnP+Dmv6r9FTwYdald0fjAhhCgkST48yHot+dDrnLztmf09KtYFrS7ndiE85DJ+DDc/w0cZ/QB4WP8Hs4xv4W++4OXIhBBlhSQfHpRZ86HVOFlZVPp7iBJEoeWDjLsZnj6Gy8qXttr9PPzvEJpqDnk7NCFEGSDJh4copYhPSgVA72xZ84RrC3SFS/IhSo5l1tb0TZ/AIWtlgtLPMs84gbt1q11y7JS0DBIup5FqtpBwOY3Eq2aupltQSnHVyZTsWcusVkWqWaZtF6K0kg6nHtL707/Zc9LWWU/nNPnIrPmQzqaiZDmkqtA3fSKLor6j1oU1vGv4gsaaI7yR8QAZxfgKafTqH3luX/zkTTSuYhvu+8qiPXy/8Sg/j+xAs2ohPPD1JtYfOs/Wl7tSMcBU5BiEEN4hNR8ekpl4AHSoXcFxo9UC5w7aHkvNh/Cyyf2aULOiPxX8r8+y+9aADhgHzeEbw/0ADNH/ySzjW1Qk0W1xfLTioP3x9xuPAvDxtbL1h84D8Pvu0247vxDCfST58IJXsi/6lTnSRe8DodW9EZIQdve3ieavZztRNczPXta7WRTVKgQw9KUvSLhjhr0fyK+ml+hXKZ64ybdTLyLQ4Tgf3d+8WHEoJ8sR5NinWGcQQniLJB9eYNRne9szO5vKSBdRkuRy8U+r1YO+6ROItUZRWXOByUkvwD8zMWdbPiDDyUKKLji9EKIMkOTDC4zZh9pKfw9RAuV27ddqNNf6gUxgmaUVRszw80ievPo5hizrwjhby6i455d8RIiyQZIPL9BkH2p7NnNNF+nvIUqO3GoeMj++yfjxqPlpZvs9AMBdGb8zy/gm4VwCsi2aWATWgjS7SDYiRKkkyYcHbDx8Pu8dMicYk5oPUYKoXOoZss5To9AyL2AgDJhLMn600R7gF9PLNNfEkmEpXs3HqgMJ/LzjJF+svj63yF/7z/LO0v3250t25d7h9NSlq6w9mFCsGIQQ7iHJh5udS07j/i835r6DJSPLmi5S8yFKjrrZOpBm8jE49kuqHxkI9XryRtSn9n4gc40TaHlhidPXF8b//bCDSb/vdyj7bNX1ZGRz3AVizyY7fe2Nk//iwa83SwIiRAkkyYebnbp01eF5z0aRjjtcPAKWdDD4QUiMByMTIm/j72jIkBur8+uomxzKg30NvH5nI/q3rMqQG6sztpetxm7MgNuZ2eQbtvreiEmTQdNtL/FV2GyHfiDusD8+78XuMoflCiFKDplkzM00OPbveKJTLccdHEa6SC4oSo4QPyOv3dnI6bbBN1bPUVYp0IfX7mkP1iWw9j1Y+SbdrixmtvE/RqQ/RQIhOV4TN/l2ftp2gmfn7SxynNZ8+n1Y8ttBCOFxcrVzs+x9S3PMbir9PURZo9XCLc/BwLlYjYHcoP2PX00v0UJz0OnuBZnPIy/5vV6SDyFKHkk+PEyvyz7S5VrNh/T3EGVN3R6cG7iU/6xViNRc5AfjRAboVuDpAbOSfAhR8kjy4WY5aj6yF8iCcqIMSw+uyV3pE/jdcgMmTQaTDF8zRf8FJtLt+xQ3NchvSG5x5xsRQrie9Plwo4TLafT7bL1DmUOzi9UC52Ntj8PrejAyITxDKUjBlxHm/+Mx62Ke08/lHv0aGmmP8rj5KZec4+m5O5m75TjdGkYS5KPnuZ920aZ6mH37rE3HuJpuRaEY2Caa1te2bYm7wJJdp3muRz38Tde/ChOvmvlg2X8E+ehJzbDyQs/6zheDFEIUWaFrPtasWUPv3r2JiopCo9GwaNEih+1KKcaPH0/lypXx9fWla9euHDzovK23rHt23k7SMhz/6wr1u75YF5eOgSUNdEYZ6SLKpBA/A2CbD2R3jYd5wPwi51QQDbVHWWx8CQ4sdcl5Nh6+wMTFe3nup12AbQhuJqVg/vYTLNh+krs/32Avv+fzDcxYH8cnf8U6HOvtpfuZsT6Oj/+K5cs1h1mw/YRLYhRCXFfo5CMlJYVmzZoxdepUp9vfeecdPv74Yz7//HM2bdqEv78/PXr0IDU1tdjBljb/nnJc8bN3syhCs6wUaq/1qFBb1nQRZVKgj4H5T9zI8z3r8cWDrXnhiUdZcMNsEis0J0hzBebcR+P9H6PlepLer2UVj8Z49HyKw/PYM47zhpy6VP6+u4Rwt0I3u/Tq1YtevXo53aaU4sMPP+Tll1+mT58+AHz33XdERESwaNEi7r///uJFW8pkb4puUz3UsSBzcrGKdTwTkBBe0ComlFYxts9+82ohNK92M2Qsgz9fhs1f0DD2S741rOf/zKO4QBC1wgM8Gp8+21pL2btlCSFcz6UdTo8cOUJ8fDxdu3a1lwUHB9O2bVs2bNjg9DVpaWkkJSU53MqK7N3gdNnn8bAnH9LfQ5QzeiPc9g70+x8ZOl9u1u3hV9NLNNPEYvXw6BRDtv4c2ft3SDIihOu5NPmIj48HICIiwqE8IiLCvi27SZMmERwcbL9Vq1bNlSF5VfZe+NkXs+Xctb4wFaTmQ5RTTe9h2Y2zOGStTBXNeeYZX6fRqZ/w5HDc7MPftZJtCOF2Xh9qO27cOBITE+2348ePezskl8ne7JLjS02aXYTgUmAd+qRPZKnlBowaC50PTeY9wzR8SPPI+bPXSEruIYT7uXSobWSkbd2SM2fOULlyZXv5mTNnaN68udPXmEwmTCaTK8MoEf74N57Eq2aHMof/sK5ehJRrC15J8iHKuWT8eNz8FI9aFzPWMJf+ur9pqDnK4+anOaoi8z9AIVQf67jg3ZzNx5iz+Viu+7+/7D8CTHpmrI9jyt1NaVuzgkvjEaI8cmnNR40aNYiMjGTFihX2sqSkJDZt2kT79u1deaoS77Hvt+Uo61wvS3PUuWsjXQKjwOR89VAhyhcNR+o9wvHeP5CggmigPc6vxpfopt3q7cCYsHgvxy5c4b68VqgWQhRYoWs+kpOTiY29Pi7+yJEj7Nixg7CwMKKjo3nqqad44403qFOnDjVq1OCVV14hKiqKvn37ujLuUin42pwHgDS5CHFN1ubJLx9shUajITl6HeaFQwk6tYWvjO+jOjxNUvsXMBqNrDmY4DS5F0KUHoVOPrZu3cqtt95qfz5mzBgABg8ezIwZM3j++edJSUnh0Ucf5dKlS9x0000sXboUHx8f10VdFshIFyEAUFk6l2qudbgICI+GYb/Dn6/Apmlo1n1A8Klt0P8bx4n6hBClUqGTj06dOuW5iqRGo2HChAlMmDChWIGVeZkjXST5EOVcrl8nOgP0mgxVW8Mvo+HIGviiI8G3fOrR+IQQruf10S7llr3mo7Z34xCipGtyNwz/yzYk/fIp6vx2Hw/p/sDTq+MKIVxHkg9vsJjh4hHbY6n5EOVcgVKISvVtCUjDPmitZiYYvuVDw1R88fzU51fTLfbHiVfMbI27QNy5FCxOJkdTShF3LiXP2mIhyiNJPrzhYhxYM8DgbxvtIkQ5FmAq4LpGPkFwz7dcvOlVMpSWvrr1LDS+Sg3NafcGmE3HKSvtj5tN+JO7P99Ap3dX8ey8nTn2nbb6EJ3eXcWExXs9GaIQJZ4kH27gbHrooR1qXH+Stckl+5TrQpQzdzSNokejCF65o2H+O2s0hHYdw/TaH3NRG0Z97XF+Mb5MD+1m9wd6TcJl55OfLfznZI6yd5YeAGD6ujh3hiREqSNXPjewOKliHdAmy7TxMtJFCDuDTssXD7Zm2E018t/5muEPPkjo0xsguj2Bmqt8YfyQl/Qz0ZMBwP6JPfl6cGt3hQw4/ydDCFEwkny4gbO2X5M+S9WyjHQRovgCI2Hwr9B+FADD9b8x1ziRypxHq9G4fY0WZ/9kCCEKRpIPN3CWfBj1Wd7qzJqPCjLSRYhi0Rmgx5vE9/ofScqPVtqDLDGNQ3doOVqtm5MPqfkQosgk+XCDjLySD6Wk5kMIF0uvfTu3p7/Jbmt1wjTJ6ObcQ42d76HDkv+Li0iSDyGKzqULywmbhMs5h/+ZMpOPlHOQegnQQIVaHo1LiLLsuIrg7vTXeFk/kwf1y4n+dxozDasZbR5JAqEuPVf2xekyPfLtVqxKkZyaQZ2IAIdt32+Io3X1MDYfuUDPxpFEBF2f9dliVczdcpzW1UOpGyFrPYmyT6NK2AD0pKQkgoODSUxMJCgoyNvhFMlNb//FiYtXHcpi3+yFXqeFuHUw4zYIiYGndnkpQiHKlosp6bSYuMz+PG7QVSw/j0aXkUKCCma0eRQbrI28GKGjamG+rH2+s/35j1uP8/xPtu+DuMm3eyssIYqlMNdvaXZxg+yJR78WVWyJB8hIFyHcINTfyGeDWnJnsyimP3wDNLkb7WOruBhQm3BNIrOMk/giegUarN4OFYDjFxy/I3aduOSdQITwEkk+PKB7o8jrT6S/hxBucVuTynw8oAW31qsEgCa8LqGj10LzB9BipcfZr/nOMJlwLno5UiGEJB8eoMva617WdBHCc4x+0Hcq9JkKBj9u1u1hqWkst2r/8XZkDjS4d2SOECWNJB8e4PC1cl5qPoTwuBYPwKOr2WuNoYLmMtONUxiv/w4jZm9HJkS5JMmHJ5lT4eJR22NJPoTwrPC63JX+Ot9k9ARgqH4pC43jqaXJOS26EMK9JPlwoa7vr851CB4AFw4BCnyCwT/cY3EJIWzSMDIh4yGGpj/LeRVII+1RfjW+zL26lRRwfV2XqT52CU/98A/HL1zh+41H7eXnknOuHfPPsYsMnbGF2LPJngxRCLeR5MNFTidezfWLoWa4v+1B1pEubp76WQiRU1SwbW6N1t0H0CttMn9bGuGnSeMdw1d8aviEIFI8Gs+iHad4eu4Oh7IfNh/Lsd9dn63nr/1nGf7dVg9FJoR7ySRjLpLbbIfLx9xCzfBrkw3JSBchvGrZmFs4k5RKzfAAujeMANWbq3u/wmftJO5gI92DT5By+1SWXq6JUvDiwt1uj+nkJcdhtxdScu+HcvzCFXeHI4RHSM2Hi+i1zt/K2pWyzHKYmXzImi5CeIW/SW//Z6B2pUBqRwTje+uzaIb+ASExGJNPEDq3LwMSv2ZgqwjublXV7TFlXwDPYs19LhKpMBVlhSQfniQTjAlRMlVtDY//bRsVg4J1H8JXXYhMPez2U1uzTTItq+WK8kCSDxfJ/gWSgywoJ0TJ5hNkmw/kvpngVwHO7Oapw8MZplvi1plRszfZ5rVgncwHIsoKST5cJN8VLpNOgTkFtHoIq+GZoIQQhdegNzyxAer0QK/MvGKYxSzDW0Rxzi2nS0p17OORkmbBbLHab6nm6yvzZv0nJ+s+WcsKymyxUsKW9hLliHQ4dZHsPdZzyGxyCa0BOoPb4xFCFENgBAycy/yv3qDXyU+4UbeXpdqxvGIews/WDuDCGohUs2PC8MvOU/yy85TTfTOsigyLlfeW/ce0VYfs5S/d1oAqob6Mmr2dD+9vwZ3NovI8Z3JaBje//RctokP5ZsgNxf8hhCgkqflwka1Hc64X8fgtta4/kSYXIUoXjYbNYX3olT6J7dbaBGmu8JHxMz41fEIwtmH1Yf5GXu3dkBbRIR4L6/jFqw6JB8Cbv+1jxKztWBWMnpP/1PF/7T/LxStm/tp/1l1hCpEnqflwo7G96l9/Yp9WXUa6CFGaHFWR3JP+Kod67YdVk7lDt5E22v3MCh/D06P+D4CHOzg2peY52WAx5dvEWwA6GTYjvExqPjxFRroIUepkXqMt6OCW5+GR5cRao6ikucTT58bDgsfgqmdXyXVFPw2t5B7CyyT58BRpdhGi9KvSktvT3+LzjDuwooVdP8DUdnBgqcdCcMVQXI3UfAgvk+TDE9IuQ9K1xatkgjEhSg1n1+g0jEzOGMiLoVOgQh1Ijoc598HCxz1SC5KeUfxhv7osVR8y4kV4g/T5cIF8F3s6H2u79w8HvzD3BySEcLt/tfXh8bWw8k1Y/ynsnAOHV0Hvj9x63rd+25fvPv8cu0iASY9ep+XTv2LpVC8cnVaDv0mPQZt9RlWFXne97HBCMmaLIshXz9mkNJpVC3H1jyCEJB/FpZSi6/ur895JmlyEKJWqhPjmuq16RX8w+EL3N6DBnbDoCds/GrPv5V1DRyaYHyQJf5fHtPHwhXz3ueuz9Q7P528/4fD85joV7Y8zrAq9zvbYalV0fs/x++zPpztSNyKwiNEK4Zw0uxST2VKAKktZ00WIUumRm2sysG000x++PhfGghE3cl/rarzWu+H1Hau1sU3P3n4UoOFu3Rr+ND1PF+02AHo2imTmsLYejj53aw9enzAt68RkGU5G0uw4fskTIYlyRmo+iiktw5L/TjLSRYhSyceg4627mjiUtYwOpWV0aM6dDb7Q401bLcjPI4g8H8vXxvdYbGnHHXd9DwEVGd2lDh+vOOih6AsmI8s/UPkuEyGEi0jNRzEVqPOXNLsIUX5Et4XH/2ZaRm8ylJY7dBvh0xvgn5moPFas9RazNe+aDyHcQZKPYkrPby0Fq+V6h9OKddwfkBDC+wy+vJ0xgD7pb7DbWh1SL8HPI7l77yiiNWe8HZ2DrDUfFmfNyJKPCDeQ5KOY0sz5JB+XjoElDXQmCIn2TFBCiBLhX1WdvukTodtE0PsSk7iFP4wv8KjuV3QUoMnWA7ImHxklsGZGlE3S56MYTl66Sqd3V+W9U9bOplqd22MSQpQsFnTQYTQ0uIO4GcOpnrSVFw1z6K3bwFjzo/yrqns1vo5TVgLwdv8mfLAsZ3+UH7Yc471lB6gc7MuO45eYNqglxy9eITrMj56NK3M2KZXPVh3itiaVaVPD9VMJLPrnJEmpZh5qX93lxxbeIzUfxdBh8l+5bqtewc/2QNZ0EUIAhNXkUM9ZPGd+lEvKnybaOH42vsxY/Wx8SfV2dLwwfzfxSTnj2H7sEmeS0uyjXp6YtZ23ftvP4zO3A/DRioPMWB/HI99ucUtcT83dwfif/+X4hStuOb7wDkk+XKxVTCgd64azePTNtgIZ6SJEubTq2U4MaBPN2udvtZd1bhBBqz5PsujGhaw13oxeY+Vx/WKWm56ju3YLPz7ajtGda3P/DdUI9TN4MfqC23MqCYCk1Ay3nueym48vPEuaXVzs8wdaER5oul6QkJl81PNOQEIIr6he0Z9J/RyH6Wo0Gu5vEw1E86XvR0xfOpvX9d9STZvAl8YPMK/7lzZ3vAuh9Zjcv6lbV8d1FXeuEiNTv5ddUvPhYjlWi7TXfMhIFyHEdRo0/GVtSbf0d5iacSfpSofh0J8wtS2sfQ8y0r0dYoG4c4VcGflbdkny4WIOq0VeuQBXrs0kKLObCiGyyPyqSMXElIz76ZU+GUv0TZBxFVZMgM9vop12r3eDLAB3rpArk56VXZJ8uJhDNWHmSJegqmAK8E5AQogSSZetyuCQqkL6oJ/hri9ti1CeO8APxjd43/AZFUn0UpR5s1qVW5tdJPkouyT5KIJ/TyXm2hbr8KciTS5CiFw4u2hrtBpodh+M2gKth2FVGvrp/maF6RkG6/4oMXODZLrp7b/YevSi/Xn1sUuoPnYJHd9ZyR//xgMwfd0Re3mHyX9xKCGZo+dT6PnhGn7ecZKF/5yg54drOHo+JcfxneUexy9coddHa/lp24mcG0WpIclHETz2/bZct4X4ZumhLiNdhBC50Gap+dBpNQSY9Bh1176SfUPhjvdZ3mEWu63VCdZc4XXDtywxvkh77b+5HvPuVlXdHbaDU4nOhwgfu3CFF+bvAuD1X683HZ28dJVn5+3k5UV72B9/mf/7YQdPz93J/vjLvLRwT47jOKv5eGPJXvadTuLZeTtd9FMIb5DRLkWQdNWcoyzApGfry13R67Lkc/Y1XaTmQwjhKGtfiT2v9UCrdUxIALp3v53EDl24uvM7TGveon7qceYY3ySj/p3csqMLJwmnX4sqjO/dkOS0DKqG+jG+d0MuJKfnPwEitqTH4qZenZeu5PyeBEhJy3DakTQlPedQWmf7XUkvWbU/omik5sNFwvyN+BiyzWCaWfMRLsNshRCOsqYZvkYdJr3zGZCD/X3wvfFRtKO3ww3DQaNFv/8XVpie5f908wk1WgjxM1I11DaxYZCPgeoV/QsUQ51Knu+LpkHjtD3FWTOUs5oPd3ZwFZ4jyYeLqOyrL2WkwcU422NpdhFCZKMt7EXULwxufxceWwsxN+GjMfO0YT6j9g6EvT877yDh6hhcoDCndPYjuXNor/AcST5cJMcfyYXDoCxgCoKACK/EJIQouXRF/faNbAxDFjMyfTQnVQVCzfHw40Pw3Z1wpnBDc/U6byQfGqcZiLMaDWeTjOmk5qNMkOTDRXL8jWQd6SJ/LEKIbDTFGaSq0bDE2o6uaVNYUWmwbdXsI2vg8w7w61OQfLZAh8k+3NfV9l6bej2rCylpJDhZQ0YDXEhJJy3jep+OU5cc9zuTlJprs4vFqki4nFa8gIXHSPLhIicvXXUskJEuQog8+BqLv8r1VXxYH/04jNoMDXqDssK26fBxS0bofsZE3rOkursW4baP1+YoO5OU5nSUTHxSKi0nLqPzu6sB+Hz1IYfXz958lLZvrWD5vjNOzzXwq43c8OZydl5bAE+UbJJ8uIuMdBFC5KFn40g61QvnmW5F+wfl7f5NaFMjjFG31obQ6nDfTHj4d4hqAemXed4wl7/9nmd5twRaR4c4PYZOq6F/S88Oz83NiYu2f+Ay/5Gb/Pt+h+0zNx7L8/WbjlwA4Ictx90QnXA1ST7cRWo+hBB5MOi0zHi4DU92Kdo/KPfdEM2Pj7Un1N94vTDmRnjkL9ssqUFVCLeepfba/+MnwyvEPh6a4xh6nYb37m1G3OTbebV3w6L+KCWKtHKXDpJ8FEG+fcqVylLzIcNshRAepNVemyV1K3R+GQz+cHIb+hm9mGr4kGqa680WWUe76IvcA1aIwpNPmztcPg3pyaDVQ1gNb0cjhCiPjH7Q8TkY/Q+0HAwaLbfrNrPc+Bwv6mcRRDL6LB1ODWVkDGvZ+CnKPkk+iiDfD3dmk0toDdAZ8t5XCCHcKTAC7vwYHv+bNZYmmDQZPKpfwlrTU9yWNA/Mtj4WUvMhPEk+bYUQdy6F/609TFJqzmmAHSRIfw8hRAkT0YiHzGMZkv48B6xVCdZc4Z6LX8InrWD79xhK0KJ1++NzDtF1Zt9p237HL1yxl83bdoKzl22jaeLOpbBg+wmsTuZpX7zrFAfiL9ufbzt6gRd+2lXgc4vikeSjEDq9u4o3luzLf0dZzVYIUSJpWGVtTq/0yTxrfozLpghIOgm/jKL72v50026lAL3a3K7nhzmH6DrT6yPbfje/s9Jelp5h5e5pGwDbd/aYH3fmWAF3few5Rs3+hx4frrGX9Z+2gblbjxf43KJ4XJ58vPbaa2g0Godb/fr1XX2aEiPQR8+YbnX58+mO1wtlpIsQogSaPbwtL9/egF+e7Ej1LsMxPv0PdH8DfEPxvXSQr4zvszlyCuObJvJAu2iH197dqiqju9Tx+Mq5RXEsS00IwMbD5x2e7z6Z6PDcWc2IcC+3rGrbqFEjli9ffv0k+rK7eO4TnWoxolNtx0L7SBdJPoQQJceNtSpyY62KADSuEnyt8Elo8SCs+wg2TqPSpR0MvfQE1O3FJs2tHFS2ZOPde5rZjzO6cx06TlmZ4/gllTlbcpE91bAUYV0cUTxuyQr0ej2RkZHuOHSJk2NhprTLcPmU7bE0uwghSgPfEOj6KrR5FFZPhu3fw3+/s9S4lPmWjnyY0d9hd6O+dLXYZ1isDs+zr5ZrkZoPj3PLJ+jgwYNERUVRs2ZNBg0axLFjec9MV5rlGJ2WWesREGH7gxZCiNIiqDL0/ghGboIGd6LTKO7Vr2alaQwseRaSTgNgKmXJh9mSd3IhyYfnufwT1LZtW2bMmMHSpUuZNm0aR44c4eabb+by5ctO909LSyMpKcnhVprkqPnI7O9RQWo9hBClVMU6cN/39E2bwDpLI0yaDNjyFXzcHP54CWP6BW9HWCgZVseaj+ytLBmSfHicy5tdevXqZX/ctGlT2rZtS0xMDD/++CPDhg3Lsf+kSZN4/fXXXR2Gy1264nyBphxNhWevjYapVHY72QohyocdqjaDzC/R3vIvc2oth+ObYMOn+G2dzjP6bnyVcRtJBHg1xupjl+RbvupAgv15mxphbD5yPXl65NutdGtYKcfr98cnccfHf5NhVbSvWYFne9SlVUxYrnHsPH6JL9ccZmyv+lQL87OX/7zjJGv+O8ekfk1KXXOVO7n9nQgJCaFu3brExsY63T5u3DgSExPtt+PHS+aiQO/+ecBpeY4VFhOuLYYULsmHEKJ0e6h9DAB12t4GQ/+AQfOhcnM05hSe1C/ib9NTPKlbQABX8jlSyZE18QDbd/gL83fn2O/uaRvsNSIbDp/nuXm78jxun6nrWLL7NKNmb3co/78fdjB/+wl+3Foyr23e4vbkIzk5mUOHDlG5cmWn200mE0FBQQ63kig+Mc1peY4Jx+w1Hw3cHJEQQrjX+DsasmDEjbxyR0Pbim11usKjq+C+WZgr1CdIc4VnDD+xM+R5RhqX4IPz78nc3NHU+XWhJEhOc/xuP3wupUCvizvvPBG7kOK89ry8cnny8eyzz7J69Wri4uJYv349d911FzqdjgEDBrj6VB5l0DmfVN2hND0FLl3rXCs1H0KIUk6v09IyOhRD1qnXNRpocAeGkRug/9dQoTa61As8p53FWtNTDNX9TpDeXKDjt6tZwU2Re09uq+rKmjOOXJ58nDhxggEDBlCvXj3uvfdeKlSowMaNGwkPD3f1qTwqt3UPtFmLz/0HKPCrCP4VPRKXEEJ4hVYLTe6GEZug7zTO6iII1yQy3vA9f+lGM1y3GF9S8zyErowsZpdV2fuJ3MPlHU5/+OEHVx+yRNDn8kfiMNrl7LX+HtLkIoQoL3R6aD6QMZuqUe3YQkbofqGaNoGXDLN5XP8r/8u4ne8s3UjBN+dLc6smKMU0ZfBncgfpepuL7NPt5vZ5ckg+Eq7195AmFyFEOWPRGJhj6cKt6e8xzvI4cdYIKmgu84LhB/42/R8jdYsIzNYxVVtCaz5ym/fDalUopbBar98yyzNpsuybVealIvP1WffJWubsnFnPXVaU3XnPi2HErG3sj7/M7/93Mya9jlUHzrJg+0mn+zpUGyZcGxETXs8DUQohRMmTgZ6fNbfyY3oH+mjXMUq/iJraeJ4z/Mij+sV8k9GL6ZYeJBGQc5LGEqLWi785La/54m9UC/Pl+IWr9rJejSP5O/ac/fn5lHRSzRZ6fbSWI046qQ6ZvoUzSam8fHtDnpi1jYl9GvPzjpOcTkxl8ZM3OTTxv7lkLwv/OcWvT3Zg8DebqRbqx9dDbnDhT+o9UvPhxG+74zmckMKGQ7bFiD5acTDXfd+8q/H1JzLSRQhRTk3o04hQPwMv3daArwffgL+PiQXWjnRNf5fR6SOJtUYRrLnC04b5/G36P94M/pkW4db8D5xNdJY5NLwha+IB8PueeC5nG/X498FzORKPzOaY1f8lsD/+Mg98vYnLqRk8NXcHKw/Yyv495TjJ5ldrj3AuOY2Rs7bz35lkVuw/64afyDsk+chDZq1GcvbhtMCRSbdx+K3bqB95bWhwegpcOmp7HC7JhxCifKkTEcj2V7oxvGNN2teqwM5XuwNgRcsv1g7UHL8b7p6OqtSQIM1VBqXNJea7trykn0kk59k5vjuxb/YixM+Q6zkCffSsef5Wjky6zVM/VpFoc7my5tdsklsH3LLT2HKdJB95yOwM5ewXr9FoHNsrM5tc/MPBv+wNHxNCiPxk7WyZveOlVq+Hxv3QPL4O7v0eIpqgNV9huP431piewu+Pp9BfPJxzyYosMjv+l/ROnZpcxrwUdRb3MtTVw06Sj2yydjQqVGcomdlUCCHyp9VCwzvh8bWcvuN7NlnrY9RYMOycCZ+25m3LuzTWHHb60lIzNDeXMLOvpptdbolXGcw9pMNpduYsSy9nftAL9HGX5EMIIQpOoyElujP3petoqfmPeY03oju4lG5spJtpI2ssTZhmuZMN1oZkfguX9BqPTLlFmd/qubk112SllCo170NeymXNx/ELVziWyxS4Z5KuT4qTnJrBkl2nOXg2Of+D2uf4kORDCCEKY7uqi/X+OfDEBpZoOpKhtHTU7WaO8U0WGcfTQ7sFDdZSMy/I+eScU6n/vuc0245ezPN1O45dItVsIfZsMvGJ169FO49fsj/OrfIkr+taSVTuaj7MFis3v7MSgP0Te+Jj0Dlsv/vzDfbHT8zaRqq5gL2x7XN8SGdTIYQACPY1kHjVTOVgH6fbfQzX///VaTQQ0ZBXtKOZlNqf4brF3KdbRXPtIb4wfkCsNYq/fO8FcwcwOD9eSfHMvJ05yvacTGLQ/zbl+bqxC3Yzc9NR9pxMynUfZ7lH1uvavgk98TXqnOxVspS7mo8raRb740tXcq4/kHD5+sJIuSUes4e3dSxIS5Y1XYQQIpsfH2vPHU0r8/2wtk63Vw31Y+SttXihZ32HPnYnVDivZjzMlrvW8GeFB8kwBFJbe4pHEz+EDxvDqrf5eajz79oOtUt3h/+8Eg9w3m/E4bp2tXQsYFfuko/ierBdDDfWyrZuy9m9tvuASBnpIoQQ19SLDOTTgS2pXSkg132e61GfJzrVcrrt5uYN6f7kp+if2Qvd34TgapCSAKveotmPNxLXYRn/jq7p8JpZj7Rz6c9Q0jhLPlSW+pC8RguVJJJ8FJLTztZn9tjuIxs72SiEEKJYfILgxlEweodtJd2oFpCRCtum4/dle74yvEcbzT7K5rgQR876fGTtx1pKco/y1+dDuePDGX8t+Yho5PpjCyGEsNHpbSvpNu4PR9fD+k/Q/Pc73XTb6Kbbxk5rTdidig4jFkp+v4eicFbzkbVMaj5KqKJO8pLJ6cvP/Gu7j2hSvIMLIYTIn0YD1TvAwB9If2IzszK6kKoMNNMehvnDWG16mmG6JQSRc22V0s7ZNSzronSlZUKyclfzkXWcdbtJK/j8gVZ0qF2Br9YeYfeJS/m+Pscv1mrNknxIzYcQQniSLrwuL2UM472Me3hAt5wxwauoeuUcrxhmMUb/E/MtHfnW0p1Dqoq3Q3WJ7u+v5sXbG7Dx8HkOJ6RQOdiXzXHn7dtnbjzK093qArAl7gIfrzhI4yrBjOhUi/WHznMhJZ0BbaK9Fb5duUs+ss+t//jMbQxqG82sTccK9PrEq9lGyCQeg/TLoDNCxTquClMIIcqlno0jmb3pGHXy6KSaVWY/vAsE8bGlH2Oe/pQXXnuFh3VLqa89zkP6ZTykX8YaSxOmW3qyytoMla3S36jTkm5xHN3ob9SRkm6hpDmVmMqo2f/kuv2jFQcZeWttjHot91ybOmLtwXME+uh5Z6ltGZB2NStQo6K/R+LNTblLPixO6qR2ZJnAxRmN5nqNR9OqwY4bM/t7hNcDXe4LIgkhhMjfK7c3pEW1EG6tX6lA+2ed7XNcr/pg8GXwyPGsOzSCs1f/oeXpufgfWUZH3W466nZzNSCanVH3sSWkF7vPKV7oVZ/k1Az+O3OZepGBvDB/N32bRwEw6ff9bvkZ3S3dYsWod0ywDidcb4JKuJwmyYenOWsvy6+DzuG3bqPGuN8ACPUzOm7MHOki/T2EEKLYfI067mldrUivbRgVZL+3Pa4J9IeLcbDlf7D9O3yTj9Huvym0M06D5gNB8yhUq0OzaiEA/P5/NwPw/Ya4PM/Vr0UVFvxzskhxult6hhVMjmVZZ4fNsBZw8kw3Kn8dTp1kH/mNgMmaWedY2EiG2QohRImQa2fL0OrQ/Q0Ysw/u+MA2GWR6Mmz+Ej5tDTP7w39/2vrwXZPfwqIleX2VtIyczUVZw82weL9Xajms+Sjem54j+ZBhtkIIUSLk++1u9IfWQ6HVw3BkNWz6Ag78DrHLbbeQGGj9MLR4EH0+yUdJXmA3PSPvmo2SUPNRDpOPnGWagq1bC+D4gUxLhotHbI8jpOZDCCG8KfuAglxpNFCzk+124YitSeaf7+HSUVj+Gqx8i3aR3WmlacU2VRdn69Tm+Ee0BMkv+TCXgJqPctfs4mxJ490nEwv8eoeqOIdp1Ss6f4EQQgiPKNIlNawG9HgTxuyHPlMhqiVY0ok5uZj5ptf53TiWB3TL8Oeqw8vya5bxpm4frKH62CUOZT9sOW5//Nj321ix74ynw3JQ7pKPAmfG17SIDgEgPNDWe+eG6mHXN56+tnKh9PcQQgivCfGzjTRsca3TaJEY/aDFA/DoShi+kquNB3BVGWmgPc4bhulsMo1kduUfqaexTcug02iY0Kf0NrcP+3arV89f7ppdnA21zU14oIkFT9wIwNrnbyXVbCEk62iX0zts91EtXBihEEKIwtg4rgtpZivBfi6a7qBKS3zv/pxLt07AcGAeum3TCTh/kBsvLuIP0yK2WOsSd+F+7rljFF0aRNBh8l854rmcaiYqxJdGr/7hmpjKmHJX81GYfjZNqwTbezT7GHSOiQfAqR22+8rNXRKbEEKIwvMx6FyXeGQRUqES+htHohm1BR76hfiqPTArHTdo/+OeYxPgvfpEbZxILY3jkNvIYB/qRATib7r+/32Aqdz9r5+ncvduFGa0S55DqdKvwNl9tsdS8yGEEGWXRgM1b2HHlXqMj13O/bqVDPNbTfDVBDQbp7LCBJut9fgh41aWWNs5PYRBV3L7iHhD+av5KETykWd/ojN7QFnAvxIERRU/MCGEECWaUoqzhPKxpR/v1J8HA36Aur2wKA1ttAd43/g5W0wjYMmzEL/b4bU6bbm73Oap3L0bhVnVNs85ZDKbXKJa5LOjEEKIsiDr5cOq0UG9XjDwB25M+4R3zfdw3BpOkOYKbPkKPr8JvryV+3Qr8SM133lDyptyl3zMzTLcKD/+ebXRnbq2sE9U8+IFJIQQolQw6K5fMn0MOvvjM4TxqeUuOqZ/wIPpY6FhH9Dq4dR23jZ8xWbTCMbzBU01hyjigOAyp9z1+chv8pVMjasEMbZn/dx3sCcf0t9DCCHKg071wu2Pn+x8fRXzh9rHsOpAAn5GHQO7DIEmlSE5AXbOJmXDNwQkx3Fb+h/cZvqDvdYY5lhu5WdLB5LwZ/wdDdFpNXy7IY7hN9dk3ILdTs7sekE+3r38a1RhJ75ws6SkJIKDg0lMTCQoKMjlx3/qh39YtOMUL93WgOEdawLYJ2Pp3SyKTwYUIJlIS4bJ1UBZbRPTBFV2eZxCCCHKAKXg6DrY9i3s/RksabZyvS806guthkC1tvbm+8zr0Y21KjCuVwN6f/q3/VCVg33YMK6L/fkri/bw/cajRQqrVUwo869NJeEqhbl+l7uaj4xrnT70TnoeF7hNLn63LfEIiJTEQwghRO40Gqh+k+3W623Y9SNs/9Y2Q/bOObZbeH1oORia3W9/mVI5r1PZn2cUphNjNsV5rSuUuz4fmav5OUs0CjxX//FNtvuqrV0VlhBCiLLOLwzaPQ5PrIdhy6D5A2Dwg4T98Mc4eK8+Hxo+pa1mH0pZcwzPNWQbMZNhKfoCcRYvLy5Xjms+cuZduoKOWjm+2XZfra2rwhJCCFFeaDRQrY3t1vMt2D0Pts2A+N301a2nr249p85WwXfnUMKowgVsTRiGbNet4tReFCNvcYlyVfOx91QSy68tpuOslkNXkElglLpe8yHJhxBCiOLwCYYbHoHH1sLwlczO6Eyy8iHKcpLQdRPZaBrJp4aP6aDdjVHnmGyYS3HNR7lKPu76bJ39sbNmlzqVAvI/yIXDcOUc6EwyzFYIIYRraDRQpSUvZjxCm7TP+LnaC2RUboFRY+EO3UZmGScxI/lxWPseXLb9E127INesXHi7z0e5anZJyzLMNmuzy4+PtWfNfwk80C4m/4Mc22i7j2oBepOrQxRCCFGOLX7yJpbsPk2XW/ugN73In8uXEbJ/Nk0v/kGF9FOwYgKsfAvq9mRE84cw31Kdbo2rkJKWweYjF/hoxUEAKvgbmflIW3p9tDbHOepFBDoMG/aGcpV8ZJW15qNNjTDa1Agr2AvtTS5t3BCVEEKI8qxxlWAaVwm2P+/etRt07QbpKfDvIttImeObYP9ijPsX81xwNfB7CFo+RIfade3Jx7jbGtCgchC3NYnkt93xAMRNvt0bP5JT5abZJft0JkWe6jYz+Yh2vniQEEII4XJGf2gxCIb9CSM2QtsnwCcEEo/Dyjfhg8Yw/xGaa2IByLzC6UvomjIlMyo3sGRr33I2z0e+Us7bhkSBdDYVQgjhHZUaQK/J8Mx+6PeV7XpkNcPueSwyjWeR8RWiT/wKGWlFu9Z5QLlJPrJ3rinSCoNHVtvuKzUC/4ouiEoIIYQoIoMvNL3XVhvy6CpoNpA0pae59hA3/DMWPmhMr4QZhHPR25HmUG6SD2u2ZhdDUZpdMpOPmre4ICIhhBDCRaJawF3TuDHtE6aY7+WqTyVIOUu3hOmsM43mbf2XkHDA21HalZvkI2fNRxGSj8PXko8aknwIIYQoec4TzFRLX04P2Qx3TyexYkuMGgv36VfB1DYwZyAc2+TtMMvPaBeLJXufj0LmXRePwsUjoNFB9Q4ujEwIIYRwjfVjO3M+OZ2akcEQ2Y/gxv3Yt3k5tf77GmPs73Bgie1WrR08MB9MRZ8rpDjKT/JR3NEumU0uVVuDKdBFUQkhhBCuExXiS1SIr0NZgzZdoU1XSPgP1n8Mu+aCzuC1xAPKU/JR3GaXg8ts9zU7uSYgIYQQwpPC60KfT+HWlyA10auhlJvkI3ufj+wL9OTJnAqxK2yP6/Z0YVRCCCGEhwVVtt28qNx0OLUWp+Yj7m8wp0BgZajc3LWBCSGEEOVMuUk+ctZ8FCL5OPCb7b5uTyihs8UJIYQQpUW5uZJmXz64wDUfVsv15KPebS6OSgghhCh/yk3yUaNiAF0bVLI/L/B893Fr4fJp8AmWycWEEEIIFyg3yYdOqyHUz2h/XuD57nf9aLtvdBfoTW6ITAghhChfyk3yAZC110eB5vlIvwJ7f7E9bnq/W2ISQgghyptylXxkXd+lQDOc/rsQ0i9DSLSsYiuEEEK4SLlKPrJOcppvzYdSsOlz2+PWQ2WUixBCCOEi5eqKarZcH/GS72iXo+shfhfofaHlYDdHJoQQQpQf5Sr5MOqv/7h51nwoBasm2R43uw/8wtwcmRBCCFF+lKvko3FUsP2xRpNH8nF4pW2Irc4INz/rgciEEEKI8sNtycfUqVOpXr06Pj4+tG3bls2bN7vrVAVWoHnFzFdhybWEo/VQCKnm1piEEEKI8sYtycfcuXMZM2YMr776Ktu3b6dZs2b06NGDs2fPuuN0BVagWU2Xvw4XDkFAJHQa5/6ghBBCiHLGLcnH+++/z/Dhw3n44Ydp2LAhn3/+OX5+fnzzzTfuOF2BafNLPrZ8DZum2R73/hB8Q9wdkhBCCFHu6F19wPT0dLZt28a4cddrDbRaLV27dmXDhg059k9LSyMtLc3+PCkpydUh2SQncMO+t3lVfw4NCpasBJStc6myQmoi/LvAtm+ncVCvl3viEEIIIco5lycf586dw2KxEBER4VAeERHB/v37c+w/adIkXn/9dVeHkVPqJerGzaJu5k+8JZf9bhwNt7zg/niEEEKIcsrlyUdhjRs3jjFjxtifJyUlUa2aGzp5+obBzc9w4EwywX5GIoN8QaMBNNfvo1pA3e6uP7cQQggh7FyefFSsWBGdTseZM2ccys+cOUNkZGSO/U0mEyaTBxZs868AXcZTz/1nEkIIIUQeXN7h1Gg00qpVK1asWGEvs1qtrFixgvbt27v6dEIIIYQoZdzS7DJmzBgGDx5M69atadOmDR9++CEpKSk8/PDD7jidEEIIIUoRtyQf9913HwkJCYwfP574+HiaN2/O0qVLc3RCFUIIIUT5o1Eq61qv3peUlERwcDCJiYkEBQV5OxwhhBBCFEBhrt/lam0XIYQQQnifJB9CCCGE8ChJPoQQQgjhUZJ8CCGEEMKjJPkQQgghhEdJ8iGEEEIIj5LkQwghhBAeJcmHEEIIITxKkg8hhBBCeJRbplcvjswJV5OSkrwciRBCCCEKKvO6XZCJ00tc8nH58mUAqlWr5uVIhBBCCFFYly9fJjg4OM99StzaLlarlVOnThEYGIhGo3HpsZOSkqhWrRrHjx+XdWO8QN5/75PfgXfJ++9d8v67l1KKy5cvExUVhVabd6+OElfzodVqqVq1qlvPERQUJB88L5L33/vkd+Bd8v57l7z/7pNfjUcm6XAqhBBCCI+S5EMIIYQQHlWukg+TycSrr76KyWTydijlkrz/3ie/A++S99+75P0vOUpch1MhhBBClG3lquZDCCGEEN4nyYcQQgghPEqSDyGEEEJ4lCQfQgghhPCocpN8TJ06lerVq+Pj40Pbtm3ZvHmzt0MqN1577TU0Go3DrX79+t4Oq8xas2YNvXv3JioqCo1Gw6JFixy2K6UYP348lStXxtfXl65du3Lw4EHvBFtG5fc7GDJkSI6/iZ49e3on2DJm0qRJ3HDDDQQGBlKpUiX69u3LgQMHHPZJTU1l5MiRVKhQgYCAAPr378+ZM2e8FHH5VC6Sj7lz5zJmzBheffVVtm/fTrNmzejRowdnz571dmjlRqNGjTh9+rT99vfff3s7pDIrJSWFZs2aMXXqVKfb33nnHT7++GM+//xzNm3ahL+/Pz169CA1NdXDkZZd+f0OAHr27OnwNzFnzhwPRlh2rV69mpEjR7Jx40aWLVuG2Wyme/fupKSk2Pd5+umn+fXXX5k3bx6rV6/m1KlT9OvXz4tRl0OqHGjTpo0aOXKk/bnFYlFRUVFq0qRJXoyq/Hj11VdVs2bNvB1GuQSohQsX2p9brVYVGRmppkyZYi+7dOmSMplMas6cOV6IsOzL/jtQSqnBgwerPn36eCWe8ubs2bMKUKtXr1ZK2T7vBoNBzZs3z77Pvn37FKA2bNjgrTDLnTJf85Gens62bdvo2rWrvUyr1dK1a1c2bNjgxcjKl4MHDxIVFUXNmjUZNGgQx44d83ZI5dKRI0eIj493+HsIDg6mbdu28vfgYatWraJSpUrUq1ePJ554gvPnz3s7pDIpMTERgLCwMAC2bduG2Wx2+BuoX78+0dHR8jfgQWU++Th37hwWi4WIiAiH8oiICOLj470UVfnStm1bZsyYwdKlS5k2bRpHjhzh5ptv5vLly94OrdzJ/MzL34N39ezZk++++44VK1bw9ttvs3r1anr16oXFYvF2aGWK1WrlqaeeokOHDjRu3Biw/Q0YjUZCQkIc9pW/Ac8qcavairKnV69e9sdNmzalbdu2xMTE8OOPPzJs2DAvRiaEd9x///32x02aNKFp06bUqlWLVatW0aVLFy9GVraMHDmSPXv2SB+zEqjM13xUrFgRnU6XoyfzmTNniIyM9FJU5VtISAh169YlNjbW26GUO5mfefl7KFlq1qxJxYoV5W/ChUaNGsXixYtZuXIlVatWtZdHRkaSnp7OpUuXHPaXvwHPKvPJh9FopFWrVqxYscJeZrVaWbFiBe3bt/diZOVXcnIyhw4donLlyt4OpdypUaMGkZGRDn8PSUlJbNq0Sf4evOjEiROcP39e/iZcQCnFqFGjWLhwIX/99Rc1atRw2N6qVSsMBoPD38CBAwc4duyY/A14ULlodhkzZgyDBw+mdevWtGnThg8//JCUlBQefvhhb4dWLjz77LP07t2bmJgYTp06xauvvopOp2PAgAHeDq1MSk5OdvgP+siRI+zYsYOwsDCio6N56qmneOONN6hTpw41atTglVdeISoqir59+3ov6DImr99BWFgYr7/+Ov379ycyMpJDhw7x/PPPU7t2bXr06OHFqMuGkSNHMnv2bH7++WcCAwPt/TiCg4Px9fUlODiYYcOGMWbMGMLCwggKCuLJJ5+kffv2tGvXzsvRlyPeHm7jKZ988omKjo5WRqNRtWnTRm3cuNHbIZUb9913n6pcubIyGo2qSpUq6r777lOxsbHeDqvMWrlypQJy3AYPHqyUsg23feWVV1RERIQymUyqS5cu6sCBA94NuozJ63dw5coV1b17dxUeHq4MBoOKiYlRw4cPV/Hx8d4Ou0xw9r4Davr06fZ9rl69qkaMGKFCQ0OVn5+fuuuuu9Tp06e9F3Q5pFFKKc+nPEIIIYQor8p8nw8hhBBClCySfAghhBDCoyT5EEIIIYRHSfIhhBBCCI+S5EMIIYQQHiXJhxBCCCE8SpIPIYQQQniUJB9CCCGE8ChJPoQQQgjhUZJ8CCGEEMKjJPkQQgghhEdJ8iGEEEIIj/p/w7H+nIc/3N0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "time1, wx, wy, wz = zip(*gyro_noisy.measured_values)\n",
+    "time2, zx, zy, zz = zip(*gyro_clean.measured_values)\n",
+    "\n",
+    "plt.plot(time1, wx, label='Noisy Gyroscope')\n",
+    "plt.plot(time2, zx, label='Clean Gyroscope')\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.plot(time1, wy, label='Noisy Gyroscope')\n",
+    "plt.plot(time2, zy, label='Clean Gyroscope')\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.plot(time1, wz, label='Noisy Gyroscope')\n",
+    "plt.plot(time2, zz, label='Clean Gyroscope')\n",
+    "plt.legend()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "getting_started.ipynb",
+   "provenance": [],
+   "toc_visible": true
+  },
+  "hide_input": false,
+  "kernelspec": {
+   "display_name": "Python 3.10.0 ('rocketpy_dev')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.0"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "18e93d5347af13ace37d47ea4e2a2ad720f0331bd9cb28f9983f5585f4dfaa5c"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 1dd5781f3b1303a7c8b8cbd750bdf9d1a36127d5 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 2 Apr 2024 15:18:14 +0200
Subject: [PATCH 010/120] ENH: add option to add noise to each axis seperatly

---
 rocketpy/mathutils/vector_matrix.py        | 23 +++++++++
 rocketpy/sensors/accelerometer.py          | 39 +++++++++-----
 rocketpy/sensors/gyroscope.py              | 51 ++++++++++++------
 rocketpy/sensors/sensors.py                | 60 +++++++++++++++-------
 tests/fixtures/sensors/sensors_fixtures.py | 26 +++++-----
 5 files changed, 136 insertions(+), 63 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 8263da2bf..b8640ddea 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -242,6 +242,29 @@ def __xor__(self, other):
             ]
         )
 
+    def __and__(self, other):
+        """Element wise multiplication between two R3 vectors.
+
+        Parameters
+        ----------
+        other : Vector
+            R3 vector to be multiplied with self.
+
+        Returns
+        -------
+        Vector
+            R3 vector resulting from the element wise multiplication between
+            self and other.
+
+        Examples
+        --------
+        >>> v = Vector([1, 7, 3])
+        >>> u = Vector([2, 5, 6])
+        >>> (v & u)
+        Vector(2, 35, 18)
+        """
+        return Vector([self.x * other[0], self.y * other[1], self.z * other[2]])
+
     def __matmul__(self, other):
         """Dot product between two R3 vectors."""
         return self.x * other.x + self.y * other.y + self.z * other.z
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 1774fde76..1b8dd8680 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -59,27 +59,38 @@ def __init__(
         resolution : float, optional
             The resolution of the sensor in m/s^2/LSB. Default is 0, meaning no
             quantization is applied.
-        noise_density : float, optional
+        noise_density : float, list, optional
             The noise density of the sensor in m/s^2/√Hz. Sometimes called
             "white noise drift", "angular random walk" for gyroscopes, "velocity
-            random walk" for the accelerometers or "(rate) noise density".
-            Default is 0, meaning no noise is applied.
-        random_walk : float, optional
+            random walk" for the accelerometers or "(rate) noise density". If a
+            float or int is given, the same noise density is applied to all
+            axes. The values of each axis can be set individually by passing a
+            list of length 3.
+        random_walk : float, list, optional
             The random walk of the sensor in m/s^2/√Hz. Sometimes called "bias
             (in)stability" or "bias drift"". Default is 0, meaning no random
-            walk is applied.
-        constant_bias : float, optional
+            walk is applied. If a float or int is given, the same random walk is
+            applied to all axes. The values of each axis can be set individually
+            by passing a list of length 3.
+        constant_bias : float, list, optional
             The constant bias of the sensor in m/s^2. Default is 0, meaning no
-            constant bias is applied.
+            constant bias is applied. If a float or int is given, the same bias
+            is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
         operating_temperature : float, optional
             The operating temperature of the sensor in degrees Celsius. At 25°C,
             the temperature bias and scale factor are 0. Default is 25.
-        temperature_bias : float, optional
+        temperature_bias : float, list, optional
             The temperature bias of the sensor in m/s^2/°C. Default is 0,
-            meaning no temperature bias is applied.
-        temperature_scale_factor : float, optional
+            meaning no temperature bias is applied. If a float or int is given,
+            the same temperature bias is applied to all axes. The values of each
+            axis can be set individually by passing a list of length 3.
+        temperature_scale_factor : float, list, optional
             The temperature scale factor of the sensor in %/°C. Default is 0,
-            meaning no temperature scale factor is applied.
+            meaning no temperature scale factor is applied. If a float or int is
+            given, the same temperature scale factor is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
         cross_axis_sensitivity : float, optional
             Skewness of the sensor's axes in percentage. Default is 0, meaning
             no cross-axis sensitivity is applied.
@@ -93,9 +104,6 @@ def __init__(
         -------
         None
         """
-        self.type = "Accelerometer"
-        self.consider_gravity = consider_gravity
-        self.prints = _AccelerometerPrints(self)
         super().__init__(
             sampling_rate,
             orientation,
@@ -110,6 +118,9 @@ def __init__(
             cross_axis_sensitivity=cross_axis_sensitivity,
             name=name,
         )
+        self.type = "Accelerometer"
+        self.consider_gravity = consider_gravity
+        self.prints = _AccelerometerPrints(self)
 
     def measure(self, t, u, u_dot, relative_position, gravity, *args):
         """
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 21543e99c..be96c83d2 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -57,41 +57,53 @@ def __init__(
         resolution : float, optional
             The resolution of the sensor in rad/s/LSB. Default is 0, meaning no
             quantization is applied.
-        noise_density : float, optional
+        noise_density : float, list, optional
             The noise density of the sensor in rad/s/√Hz. Sometimes called
             "white noise drift", "angular random walk" for gyroscopes, "velocity
             random walk" for the accelerometers or "(rate) noise density".
-            Default is 0, meaning no noise is applied.
-        random_walk : float, optional
+            Default is 0, meaning no noise is applied. If a float or int is
+            given, the same noise density is applied to all axes. The values of
+            each axis can be set individually by passing a list of length 3.
+        random_walk : float, list, optional
             The random walk of the sensor in rad/s/√Hz. Sometimes called "bias
             (in)stability" or "bias drift"". Default is 0, meaning no random
-            walk is applied.
-        constant_bias : float, optional
+            walk is applied. If a float or int is given, the same random walk is
+            applied to all axes. The values of each axis can be set individually
+            by passing a list of length 3.
+        constant_bias : float, list, optional
             The constant bias of the sensor in rad/s. Default is 0, meaning no
-            constant bias is applied.
+            constant bias is applied. If a float or int is given, the same bias
+            is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
         operating_temperature : float, optional
             The operating temperature of the sensor in degrees Celsius. At 25°C,
             the temperature bias and scale factor are 0. Default is 25.
-        temperature_sensitivity : float, optional
+        temperature_sensitivity : float, list, optional
             The temperature bias of the sensor in rad/s/°C. Default is 0,
-            meaning no temperature bias is applied.
-        temperature_scale_factor : float, optional
+            meaning no temperature bias is applied. If a float or int is given,
+            the same temperature bias is applied to all axes. The values of each
+            axis can be set individually by passing a list of length 3.
+        temperature_scale_factor : float, list, optional
             The temperature scale factor of the sensor in %/°C. Default is 0,
-            meaning no temperature scale factor is applied.
+            meaning no temperature scale factor is applied. If a float or int is
+            given, the same temperature scale factor is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
         cross_axis_sensitivity : float, optional
             Skewness of the sensor's axes in percentage. Default is 0, meaning
             no cross-axis sensitivity is applied.
-        acceleration_sensitivity : float, optional
+            of each axis can be set individually by passing a list of length 3.
+        acceleration_sensitivity : float, list, optional
             Sensitivity of the sensor to linear acceleration in rad/s/g. Default
-            is 0, meaning no sensitivity to linear acceleration is applied.
+            is 0, meaning no sensitivity to linear acceleration is applied. If a
+            float or int is given, the same sensitivity is applied to all axes.
+            The values of each axis can be set individually by passing a list of
+            length 3.
 
         Returns
         -------
         None
         """
-        self.type = "Gyroscope"
-        self.acceleration_sensitivity = acceleration_sensitivity
-        self.prints = _GyroscopePrints(self)
         super().__init__(
             sampling_rate,
             orientation,
@@ -106,6 +118,11 @@ def __init__(
             cross_axis_sensitivity=cross_axis_sensitivity,
             name=name,
         )
+        self.type = "Gyroscope"
+        self.acceleration_sensitivity = self._vectorize_input(
+            acceleration_sensitivity, "acceleration_sensitivity"
+        )
+        self.prints = _GyroscopePrints(self)
 
     def measure(self, t, u, u_dot, relative_position, *args):
         """
@@ -126,7 +143,7 @@ def measure(self, t, u, u_dot, relative_position, *args):
         W = self.apply_temperature_drift(W)
 
         # Apply acceleration sensitivity
-        if self.acceleration_sensitivity != 0 and self.acceleration_sensitivity != None:
+        if self.acceleration_sensitivity != Vector.zeros():
             W += self.apply_acceleration_sensitivity(
                 omega, u_dot, relative_position, inertial_to_sensor
             )
@@ -174,7 +191,7 @@ def apply_acceleration_sensitivity(
         # Transform to sensor frame
         A = rotation_matrix @ A
 
-        return self.acceleration_sensitivity * A
+        return self.acceleration_sensitivity & A
 
     def export_measured_values(self, filename, format="csv"):
         """
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 8ba08317b..2813acbd8 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -55,27 +55,39 @@ def __init__(
         resolution : float, optional
             The resolution of the sensor in sensor units/LSB. Default is 0,
             meaning no quantization is applied.
-        noise_density : float, optional
+        noise_density : float, list, optional
             The noise density of the sensor in sensor units/√Hz. Sometimes
             called "white noise drift", "angular random walk" for gyroscopes,
             "velocity random walk" for the accelerometers or
             "(rate) noise density". Default is 0, meaning no noise is applied.
-        random_walk : float, optional
+            If a float or int is given, the same noise density is applied to all
+            axes. The values of each axis can be set individually by passing a
+            list of length 3.
+        random_walk : float, list, optional
             The random walk of the sensor in sensor units/√Hz. Sometimes called
             "bias (in)stability" or "bias drift"". Default is 0, meaning no
-            random walk is applied.
-        constant_bias : float, optional
+            random walk is applied. If a float or int is given, the same random
+            walk is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        constant_bias : float, list, optional
             The constant bias of the sensor in sensor units. Default is 0,
-            meaning no constant bias is applied.
+            meaning no constant bias is applied. If a float or int is given, the
+            same constant bias is applied to all axes. The values of each axis
+            can be set individually by passing a list of length 3.
         operating_temperature : float, optional
             The operating temperature of the sensor in degrees Celsius. At 25°C,
             the temperature bias and scale factor are 0. Default is 25.
-        temperature_bias : float, optional
+        temperature_bias : float, list, optional
             The temperature bias of the sensor in sensor units/°C. Default is 0,
-            meaning no temperature bias is applied.
-        temperature_scale_factor : float, optional
+            meaning no temperature bias is applied. If a float or int is given,
+            the same temperature bias is applied to all axes. The values of each
+            axis can be set individually by passing a list of length 3.
+        temperature_scale_factor : float, list, optional
             The temperature scale factor of the sensor in %/°C. Default is 0,
-            meaning no temperature scale factor is applied.
+            meaning no temperature scale factor is applied. If a float or int is
+            given, the same temperature scale factor is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
         cross_axis_sensitivity : float, optional
             Skewness of the sensor's axes in percentage. Default is 0, meaning
             no cross-axis sensitivity is applied.
@@ -89,12 +101,16 @@ def __init__(
         self.sampling_rate = sampling_rate
         self.orientation = orientation
         self.resolution = resolution
-        self.noise_density = noise_density * Vector([1, 1, 1])
-        self.random_walk = random_walk * Vector([1, 1, 1])
-        self.constant_bias = constant_bias * Vector([1, 1, 1])
         self.operating_temperature = operating_temperature
-        self.temperature_bias = temperature_bias * Vector([1, 1, 1])
-        self.temperature_scale_factor = temperature_scale_factor * Vector([1, 1, 1])
+        self.noise_density = self._vectorize_input(noise_density, "noise_density")
+        self.random_walk = self._vectorize_input(random_walk, "random_walk")
+        self.constant_bias = self._vectorize_input(constant_bias, "constant_bias")
+        self.temperature_bias = self._vectorize_input(
+            temperature_bias, "temperature_bias"
+        )
+        self.temperature_scale_factor = self._vectorize_input(
+            temperature_scale_factor, "temperature_scale_factor"
+        )
         self.cross_axis_sensitivity = cross_axis_sensitivity
         self.name = name
         self._random_walk_drift = Vector([0, 0, 0])
@@ -138,11 +154,19 @@ def __init__(
         # compute total rotation matrix given cross axis sensitivity
         self._total_rotation_matrix = self.rotation_matrix @ _cross_axis_matrix
 
+    def _vectorize_input(self, value, name):
+        if isinstance(value, (int, float)):
+            return Vector([value, value, value])
+        elif isinstance(value, (tuple, list)):
+            return Vector(value)
+        else:
+            raise ValueError(f"Invalid {name} format")
+
     def __repr__(self):
         return f"{self.type} sensor, orientation: {self.orientation}"
 
-    def __call__(self, *args, **kwds):
-        return self.measure(*args, **kwds)
+    def __call__(self, *args, **kwargs):
+        return self.measure(*args, **kwargs)
 
     @abstractmethod
     def measure(self, *args, **kwargs):
@@ -226,8 +250,6 @@ def apply_temperature_drift(self, value):
             Vector([1, 1, 1])
             + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
         )
-        value.x *= scale_factor.x
-        value.y *= scale_factor.y
-        value.z *= scale_factor.z
+        value = value & scale_factor
 
         return value
diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
index d334a0a46..bbb83b805 100644
--- a/tests/fixtures/sensors/sensors_fixtures.py
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -6,16 +6,16 @@
 def noisy_rotated_accelerometer():
     """Returns an accelerometer with all parameters set to non-default values,
     i.e. with noise and rotation."""
-    # mpu6050 values
+    # mpu6050 approx values
     return Accelerometer(
         sampling_rate=100,
         orientation=(60, 60, 60),
-        noise_density=0.05,
-        random_walk=0.02,
-        constant_bias=0.5,
+        noise_density=[0, 0.03, 0.05],
+        random_walk=[0, 0.01, 0.02],
+        constant_bias=[0, 0.3, 0.5],
         operating_temperature=25,
-        temperature_bias=0.02,
-        temperature_scale_factor=0.02,
+        temperature_bias=[0, 0.01, 0.02],
+        temperature_scale_factor=[0, 0.01, 0.02],
         cross_axis_sensitivity=0.5,
         consider_gravity=True,
         name="Accelerometer",
@@ -26,18 +26,18 @@ def noisy_rotated_accelerometer():
 def noisy_rotated_gyroscope():
     """Returns a gyroscope with all parameters set to non-default values,
     i.e. with noise and rotation."""
-    # mpu6050 values
+    # mpu6050 approx values
     return Gyroscope(
         sampling_rate=100,
         orientation=(-60, -60, -60),
-        noise_density=0.05,
-        random_walk=0.02,
-        constant_bias=0.5,
+        noise_density=[0, 0.03, 0.05],
+        random_walk=[0, 0.01, 0.02],
+        constant_bias=[0, 0.3, 0.5],
         operating_temperature=25,
-        temperature_bias=0.02,
-        temperature_scale_factor=0.02,
+        temperature_bias=[0, 0.01, 0.02],
+        temperature_scale_factor=[0, 0.01, 0.02],
         cross_axis_sensitivity=0.5,
-        acceleration_sensitivity=0.0017,
+        acceleration_sensitivity=[0, 0.0008, 0.0017],
         name="Gyroscope",
     )
 

From 943542a3af83ec7ee1885aac46b982fd2cb2db48 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 2 Apr 2024 15:40:46 +0200
Subject: [PATCH 011/120] MNT: run isort

---
 rocketpy/control/controller.py             | 1 +
 rocketpy/prints/sensors_prints.py          | 1 -
 rocketpy/rocket/parachute.py               | 3 ++-
 rocketpy/sensors/__init__.py               | 4 ++--
 rocketpy/sensors/accelerometer.py          | 3 ++-
 rocketpy/sensors/gyroscope.py              | 3 ++-
 rocketpy/sensors/sensors.py                | 4 +++-
 tests/fixtures/sensors/sensors_fixtures.py | 1 +
 tests/unit/test_sensors.py                 | 2 ++
 9 files changed, 15 insertions(+), 7 deletions(-)

diff --git a/rocketpy/control/controller.py b/rocketpy/control/controller.py
index 497161c22..c2617f8eb 100644
--- a/rocketpy/control/controller.py
+++ b/rocketpy/control/controller.py
@@ -1,4 +1,5 @@
 from inspect import signature
+
 from ..prints.controller_prints import _ControllerPrints
 
 
diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index d41227de7..8c073190f 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -1,6 +1,5 @@
 from abc import ABC, abstractmethod
 
-
 UNITS = {
     "Gyroscope": "rad/s",
     "Accelerometer": "m/s^2",
diff --git a/rocketpy/rocket/parachute.py b/rocketpy/rocket/parachute.py
index 4c5e5d7f3..c1bff2638 100644
--- a/rocketpy/rocket/parachute.py
+++ b/rocketpy/rocket/parachute.py
@@ -1,6 +1,7 @@
-import numpy as np
 from inspect import signature
 
+import numpy as np
+
 from ..mathutils.function import Function
 from ..prints.parachute_prints import _ParachutePrints
 
diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 044deec43..5bfe07805 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1,3 +1,3 @@
-from .sensors import Sensors
-from .gyroscope import Gyroscope
 from .accelerometer import Accelerometer
+from .gyroscope import Gyroscope
+from .sensors import Sensors
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 1b8dd8680..8e9e028d4 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -1,7 +1,8 @@
 import numpy as np
+
 from ..mathutils.vector_matrix import Matrix, Vector
-from ..sensors.sensors import Sensors
 from ..prints.sensors_prints import _AccelerometerPrints
+from ..sensors.sensors import Sensors
 
 
 class Accelerometer(Sensors):
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index be96c83d2..47e53333f 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -1,7 +1,8 @@
 import numpy as np
+
 from ..mathutils.vector_matrix import Matrix, Vector
-from ..sensors.sensors import Sensors
 from ..prints.sensors_prints import _GyroscopePrints
+from ..sensors.sensors import Sensors
 
 
 class Gyroscope(Sensors):
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 2813acbd8..74cebeb4a 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -1,7 +1,9 @@
 from abc import ABC, abstractmethod
-from rocketpy.mathutils.vector_matrix import Matrix, Vector
+
 import numpy as np
 
+from rocketpy.mathutils.vector_matrix import Matrix, Vector
+
 
 class Sensors(ABC):
     """
diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
index bbb83b805..a4ea781c8 100644
--- a/tests/fixtures/sensors/sensors_fixtures.py
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -1,4 +1,5 @@
 import pytest
+
 from rocketpy import Accelerometer, Gyroscope
 
 
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index c7ee8175b..b15e1b0a2 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -1,7 +1,9 @@
 import json
 import os
+
 import numpy as np
 from pytest import approx
+
 from rocketpy.mathutils.vector_matrix import Matrix, Vector
 from rocketpy.tools import euler_to_quaternions
 

From 28ebc46e3f5e3640d4cf993093c978a5a5b3fec3 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 2 Apr 2024 15:55:16 +0200
Subject: [PATCH 012/120] ENH: calculate u_dot only once for all sensors

---
 rocketpy/simulation/flight.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index dc922dba2..f82b63b1c 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -709,13 +709,12 @@ def __init__(
                 for callback in node.callbacks:
                     callback(self)
 
+                # calculate u_dot for sensors
+                u_dot = phase.derivative(self.t, self.y_sol)
                 for sensor, position in node._component_sensors:
                     relative_position = position - self.rocket._csys * Vector(
                         [0, 0, self.rocket.center_of_dry_mass_position]
                     )
-                    u_dot = phase.derivative(
-                        self.t, self.y_sol
-                    )  # calling udot for each sensor. Not optimal
                     sensor.measure(
                         self.t,
                         self.y_sol,

From 378bb54ea4b857157bce088ec2bb861ee1118761 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 2 Apr 2024 16:12:24 +0200
Subject: [PATCH 013/120] MNT: change `measured_values` to `measured_data`

---
 docs/notebooks/sensors_testing.ipynb | 10 +++---
 rocketpy/sensors/accelerometer.py    |  8 ++---
 rocketpy/sensors/gyroscope.py        |  8 ++---
 rocketpy/sensors/sensors.py          |  4 +--
 tests/test_sensors.py                |  4 +--
 tests/unit/test_sensors.py           | 48 ++++++++++++++--------------
 6 files changed, 41 insertions(+), 41 deletions(-)

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors_testing.ipynb
index 76a0815a9..797dcb232 100644
--- a/docs/notebooks/sensors_testing.ipynb
+++ b/docs/notebooks/sensors_testing.ipynb
@@ -533,9 +533,9 @@
     }
    ],
    "source": [
-    "# get first column of every row as time from [(time,(ax,ay,az)),...] = a.measured_values\n",
-    "time1, ax, ay, az = zip(*accel_noisy_nosecone.measured_values)\n",
-    "time2, bx, by, bz = zip(*accel_clean_cdm.measured_values)\n",
+    "# get first column of every row as time from [(time,(ax,ay,az)),...] = a.measured_data\n",
+    "time1, ax, ay, az = zip(*accel_noisy_nosecone.measured_data)\n",
+    "time2, bx, by, bz = zip(*accel_clean_cdm.measured_data)\n",
     "\n",
     "\n",
     "import matplotlib.pyplot as plt\n",
@@ -628,8 +628,8 @@
     }
    ],
    "source": [
-    "time1, wx, wy, wz = zip(*gyro_noisy.measured_values)\n",
-    "time2, zx, zy, zz = zip(*gyro_clean.measured_values)\n",
+    "time1, wx, wy, wz = zip(*gyro_noisy.measured_data)\n",
+    "time2, zx, zy, zz = zip(*gyro_clean.measured_data)\n",
     "\n",
     "plt.plot(time1, wx, label='Noisy Gyroscope')\n",
     "plt.plot(time2, zx, label='Clean Gyroscope')\n",
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 8e9e028d4..8599816bb 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -158,9 +158,9 @@ def measure(self, t, u, u_dot, relative_position, gravity, *args):
         A = self.quantize(A)
 
         self.measurement = tuple([*A])
-        self.measured_values.append((t, *A))
+        self.measured_data.append((t, *A))
 
-    def export_measured_values(self, filename, format="csv"):
+    def export_measured_data(self, filename, format="csv"):
         """
         Export the measured values to a file
 
@@ -179,13 +179,13 @@ def export_measured_values(self, filename, format="csv"):
         if format == "csv":
             with open(filename, "w") as f:
                 f.write("t,ax,ay,az\n")
-                for t, ax, ay, az in self.measured_values:
+                for t, ax, ay, az in self.measured_data:
                     f.write(f"{t},{ax},{ay},{az}\n")
         elif format == "json":
             import json
 
             data = {"t": [], "ax": [], "ay": [], "az": []}
-            for t, ax, ay, az in self.measured_values:
+            for t, ax, ay, az in self.measured_data:
                 data["t"].append(t)
                 data["ax"].append(ax)
                 data["ay"].append(ay)
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 47e53333f..de26ed7ff 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -152,7 +152,7 @@ def measure(self, t, u, u_dot, relative_position, *args):
         W = self.quantize(W)
 
         self.measurement = tuple([*W])
-        self.measured_values.append((t, *W))
+        self.measured_data.append((t, *W))
 
     def apply_acceleration_sensitivity(
         self, omega, u_dot, relative_position, rotation_matrix
@@ -194,7 +194,7 @@ def apply_acceleration_sensitivity(
 
         return self.acceleration_sensitivity & A
 
-    def export_measured_values(self, filename, format="csv"):
+    def export_measured_data(self, filename, format="csv"):
         """
         Export the measured values to a file
 
@@ -213,13 +213,13 @@ def export_measured_values(self, filename, format="csv"):
         if format == "csv":
             with open(filename, "w") as f:
                 f.write("t,wx,wy,wz\n")
-                for t, wx, wy, wz in self.measured_values:
+                for t, wx, wy, wz in self.measured_data:
                     f.write(f"{t},{wx},{wy},{wz}\n")
         elif format == "json":
             import json
 
             data = {"t": [], "wx": [], "wy": [], "wz": []}
-            for t, wx, wy, wz in self.measured_values:
+            for t, wx, wy, wz in self.measured_data:
                 data["t"].append(t)
                 data["wx"].append(wx)
                 data["wy"].append(wy)
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 74cebeb4a..8a626b941 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -117,7 +117,7 @@ def __init__(
         self.name = name
         self._random_walk_drift = Vector([0, 0, 0])
         self.measurement = None
-        self.measured_values = []  # change to data
+        self.measured_data = []  # change to data
 
         # handle measurement range
         if isinstance(measurement_range, (tuple, list)):
@@ -175,7 +175,7 @@ def measure(self, *args, **kwargs):
         pass
 
     @abstractmethod
-    def export_measured_values(self):
+    def export_measured_data(self):
         pass
 
     def quantize(self, value):
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 666e5f8e3..ddca685a4 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -31,7 +31,7 @@ def test_ideal_accelerometer(flight_calisto_accel_gyro):
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
     accelerometer = flight_calisto_accel_gyro.rocket.sensors[0].component
-    time, ax, ay, az = zip(*accelerometer.measured_values)
+    time, ax, ay, az = zip(*accelerometer.measured_data)
     ax = np.array(ax)
     ay = np.array(ay)
     az = np.array(az)
@@ -51,7 +51,7 @@ def test_ideal_gyroscope(flight_calisto_accel_gyro):
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
     gyroscope = flight_calisto_accel_gyro.rocket.sensors[1].component
-    time, wx, wy, wz = zip(*gyroscope.measured_values)
+    time, wx, wy, wz = zip(*gyroscope.measured_data)
     wx = np.array(wx)
     wy = np.array(wy)
     wz = np.array(wz)
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index b15e1b0a2..3dbce1d34 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -76,7 +76,7 @@ def test_rotation_matrix(noisy_rotated_accelerometer):
 
 def test_ideal_accelerometer_measure(ideal_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
-    measurement is (ax,ay,az) and if measured_values is [(t, (ax,ay,az)), ...]
+    measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
     t = SOLUTION[0]
     u = SOLUTION[1:]
@@ -100,18 +100,18 @@ def test_ideal_accelerometer_measure(ideal_accelerometer):
     assert ideal_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
 
     # check measured values
-    assert len(ideal_accelerometer.measured_values) == 1
+    assert len(ideal_accelerometer.measured_data) == 1
     ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
-    assert len(ideal_accelerometer.measured_values) == 2
+    assert len(ideal_accelerometer.measured_data) == 2
 
-    assert all(isinstance(i, tuple) for i in ideal_accelerometer.measured_values)
-    assert ideal_accelerometer.measured_values[0][0] == t
-    assert ideal_accelerometer.measured_values[0][1:] == approx([ax, ay, az], abs=1e-10)
+    assert all(isinstance(i, tuple) for i in ideal_accelerometer.measured_data)
+    assert ideal_accelerometer.measured_data[0][0] == t
+    assert ideal_accelerometer.measured_data[0][1:] == approx([ax, ay, az], abs=1e-10)
 
 
 def test_ideal_gyroscope_measure(ideal_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
-    measurement is (wx,wy,wz) and if measured_values is [(t, (wx,wy,wz)), ...]
+    measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
     t = SOLUTION[0]
     u = SOLUTION[1:]
@@ -130,18 +130,18 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
     assert ideal_gyroscope.measurement == approx([ax, ay, az], abs=1e-10)
 
     # check measured values
-    assert len(ideal_gyroscope.measured_values) == 1
+    assert len(ideal_gyroscope.measured_data) == 1
     ideal_gyroscope.measure(t, u, UDOT, relative_position)
-    assert len(ideal_gyroscope.measured_values) == 2
+    assert len(ideal_gyroscope.measured_data) == 2
 
-    assert all(isinstance(i, tuple) for i in ideal_gyroscope.measured_values)
-    assert ideal_gyroscope.measured_values[0][0] == t
-    assert ideal_gyroscope.measured_values[0][1:] == approx([ax, ay, az], abs=1e-10)
+    assert all(isinstance(i, tuple) for i in ideal_gyroscope.measured_data)
+    assert ideal_gyroscope.measured_data[0][0] == t
+    assert ideal_gyroscope.measured_data[0][1:] == approx([ax, ay, az], abs=1e-10)
 
 
 def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
-    measurement is (ax,ay,az) and if measured_values is [(t, (ax,ay,az)), ...]
+    measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
     t = SOLUTION[0]
     u = SOLUTION[1:]
@@ -183,7 +183,7 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
 
 def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
-    measurement is (wx,wy,wz) and if measured_values is [(t, (wx,wy,wz)), ...]
+    measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
     t = SOLUTION[0]
     u = SOLUTION[1:]
@@ -216,7 +216,7 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
 
 def test_quatization_accelerometer(quantized_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
-    measurement is (ax,ay,az) and if measured_values is [(t, (ax,ay,az)), ...]
+    measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
     t = SOLUTION[0]
     u = SOLUTION[1:]
@@ -249,7 +249,7 @@ def test_quatization_accelerometer(quantized_accelerometer):
 
 def test_quatization_gyroscope(quantized_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
-    measurement is (wx,wy,wz) and if measured_values is [(t, (wx,wy,wz)), ...]
+    measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
     t = SOLUTION[0]
     u = SOLUTION[1:]
@@ -290,13 +290,13 @@ def test_export_accel_data_csv(ideal_accelerometer):
 
     file_name = "sensors.csv"
 
-    ideal_accelerometer.export_measured_values(file_name, format="csv")
+    ideal_accelerometer.export_measured_data(file_name, format="csv")
 
     with open(file_name, "r") as file:
         contents = file.read()
 
     expected_data = "t,ax,ay,az\n"
-    for t, ax, ay, az in ideal_accelerometer.measured_values:
+    for t, ax, ay, az in ideal_accelerometer.measured_data:
         expected_data += f"{t},{ax},{ay},{az}\n"
 
     assert contents == expected_data
@@ -322,12 +322,12 @@ def test_export_accel_data_json(ideal_accelerometer):
 
     file_name = "sensors.json"
 
-    ideal_accelerometer.export_measured_values(file_name, format="json")
+    ideal_accelerometer.export_measured_data(file_name, format="json")
 
     contents = json.load(open(file_name, "r"))
 
     expected_data = {"t": [], "ax": [], "ay": [], "az": []}
-    for t, ax, ay, az in ideal_accelerometer.measured_values:
+    for t, ax, ay, az in ideal_accelerometer.measured_data:
         expected_data["t"].append(t)
         expected_data["ax"].append(ax)
         expected_data["ay"].append(ay)
@@ -355,13 +355,13 @@ def test_export_gyro_data_csv(ideal_gyroscope):
 
     file_name = "sensors.csv"
 
-    ideal_gyroscope.export_measured_values(file_name, format="csv")
+    ideal_gyroscope.export_measured_data(file_name, format="csv")
 
     with open(file_name, "r") as file:
         contents = file.read()
 
     expected_data = "t,wx,wy,wz\n"
-    for t, wx, wy, wz in ideal_gyroscope.measured_values:
+    for t, wx, wy, wz in ideal_gyroscope.measured_data:
         expected_data += f"{t},{wx},{wy},{wz}\n"
 
     assert contents == expected_data
@@ -385,12 +385,12 @@ def test_export_gyro_data_json(ideal_gyroscope):
 
     file_name = "sensors.json"
 
-    ideal_gyroscope.export_measured_values(file_name, format="json")
+    ideal_gyroscope.export_measured_data(file_name, format="json")
 
     contents = json.load(open(file_name, "r"))
 
     expected_data = {"t": [], "wx": [], "wy": [], "wz": []}
-    for t, wx, wy, wz in ideal_gyroscope.measured_values:
+    for t, wx, wy, wz in ideal_gyroscope.measured_data:
         expected_data["t"].append(t)
         expected_data["wx"].append(wx)
         expected_data["wy"].append(wy)

From d8440f2e8eda80ad4047be1ea02d616e7b49bd11 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 2 Apr 2024 18:44:38 +0200
Subject: [PATCH 014/120] TST: unite gyro and accel tests

---
 tests/test_sensors.py | 14 +++-----------
 1 file changed, 3 insertions(+), 11 deletions(-)

diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index ddca685a4..43a42942c 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -22,8 +22,9 @@ def test_sensor_on_rocket(calisto_accel_gyro):
     assert isinstance(sensors[1].position, Vector)
 
 
-def test_ideal_accelerometer(flight_calisto_accel_gyro):
-    """Test the ideal accelerometer.
+def test_ideal_sensors(flight_calisto_accel_gyro):
+    """Test the ideal sensors. All types of sensors are here to reduvce
+    testing time.
 
     Parameters
     ----------
@@ -41,15 +42,6 @@ def test_ideal_accelerometer(flight_calisto_accel_gyro):
     # tolerance is bounded to numerical errors in the transformation matrixes
     assert np.allclose(a, sim_accel, atol=1e-2)
 
-
-def test_ideal_gyroscope(flight_calisto_accel_gyro):
-    """Test the ideal gyroscope.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
-    """
     gyroscope = flight_calisto_accel_gyro.rocket.sensors[1].component
     time, wx, wy, wz = zip(*gyroscope.measured_data)
     wx = np.array(wx)

From 99f445f4b35a9b2cd5af36f53a04d64054be0eba Mon Sep 17 00:00:00 2001
From: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date: Thu, 11 Apr 2024 16:05:08 -0300
Subject: [PATCH 015/120] Update rocketpy/plots/rocket_plots.py

Co-authored-by: Pedro Henrique Marinho Bressan <87212571+phmbressan@users.noreply.github.com>
---
 rocketpy/plots/rocket_plots.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/rocketpy/plots/rocket_plots.py b/rocketpy/plots/rocket_plots.py
index 50b24e0e9..e801da3c7 100644
--- a/rocketpy/plots/rocket_plots.py
+++ b/rocketpy/plots/rocket_plots.py
@@ -566,7 +566,7 @@ def _draw_sensor(self, ax, sensors, plane, vis_args):
             else:
                 raise ValueError("Plane must be 'xz' or 'yz'.")
 
-            # line length is 1/10 of the rocket radius
+            # line length is 2/5 of the rocket radius
             line_length = self.rocket.radius / 2.5
 
             ax.plot(

From 4db26f00beb6f225c0d3dec76bde5658160bd1bf Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 12 Apr 2024 14:11:58 +0200
Subject: [PATCH 016/120] ENH: normalize quaternions for transform matrix

---
 rocketpy/mathutils/vector_matrix.py | 38 +++++++++++++++++++++--------
 1 file changed, 28 insertions(+), 10 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index b8640ddea..6e93b3151 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -982,7 +982,6 @@ def transformation(quaternion):
             The quaternion representing the rotation from frame A to frame B.
             Example: (cos(phi/2), 0, 0, sin(phi/2)) represents a rotation of
             phi around the z-axis.
-            Note: the quaternion must be normalized.
 
         Returns
         -------
@@ -990,22 +989,41 @@ def transformation(quaternion):
             The transformation matrix from frame B to frame A.
         """
         q_w, q_x, q_y, q_z = quaternion
+        # #normalize quaternion
+        q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
+        try:
+            q_w /= q_norm
+            q_x /= q_norm
+            q_y /= q_norm
+            q_z /= q_norm
+        except ZeroDivisionError:
+            return Matrix.identity()
+        # precompute common terms
+        q_x2 = q_x**2
+        q_y2 = q_y**2
+        q_z2 = q_z**2
+        q_wx = q_w * q_x
+        q_wy = q_w * q_y
+        q_wz = q_w * q_z
+        q_xy = q_x * q_y
+        q_xz = q_x * q_z
+        q_yz = q_y * q_z
         return Matrix(
             [
                 [
-                    1 - 2 * (q_y**2 + q_z**2),
-                    2 * (q_x * q_y - q_w * q_z),
-                    2 * (q_x * q_z + q_w * q_y),
+                    1 - 2 * (q_y2 + q_z2),
+                    2 * (q_xy - q_wz),
+                    2 * (q_xz + q_wy),
                 ],
                 [
-                    2 * (q_x * q_y + q_w * q_z),
-                    1 - 2 * (q_x**2 + q_z**2),
-                    2 * (q_y * q_z - q_w * q_x),
+                    2 * (q_xy + q_wz),
+                    1 - 2 * (q_x2 + q_z2),
+                    2 * (q_yz - q_wx),
                 ],
                 [
-                    2 * (q_x * q_z - q_w * q_y),
-                    2 * (q_y * q_z + q_w * q_x),
-                    1 - 2 * (q_x**2 + q_y**2),
+                    2 * (q_xz - q_wy),
+                    2 * (q_yz + q_wx),
+                    1 - 2 * (q_x2 + q_y2),
                 ],
             ]
         )

From 4356af799d17b436455fb412006d322d4649e926 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 12 Apr 2024 14:12:40 +0200
Subject: [PATCH 017/120] TST: lower tolerances

---
 tests/fixtures/rockets/rocket_fixtures.py | 17 +++++++++++++----
 tests/test_sensors.py                     |  4 ++--
 2 files changed, 15 insertions(+), 6 deletions(-)

diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index c461a78f4..e6231209a 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -244,7 +244,14 @@ def calisto_air_brakes_clamp_off(calisto_robust, controller_function):
 
 
 @pytest.fixture
-def calisto_accel_gyro(calisto_robust, ideal_accelerometer, ideal_gyroscope):
+def calisto_accel_gyro(
+    calisto,
+    calisto_nose_cone,
+    calisto_tail,
+    calisto_trapezoidal_fins,
+    ideal_accelerometer,
+    ideal_gyroscope,
+):
     """Create an object class of the Rocket class to be used in the tests. This
     is the same Calisto rocket that was defined in the calisto fixture, but with
     an ideal accelerometer and a gyroscope added at the center of dry mass.
@@ -264,9 +271,11 @@ def calisto_accel_gyro(calisto_robust, ideal_accelerometer, ideal_gyroscope):
     rocketpy.Rocket
         An object of the Rocket class
     """
-    calisto = calisto_robust
-    calisto.add_sensor(ideal_accelerometer, -0.10482544178314143)
-    calisto.add_sensor(ideal_gyroscope, -0.10482544178314143)
+    calisto.add_surfaces(calisto_nose_cone, 1.160)
+    calisto.add_surfaces(calisto_tail, -1.313)
+    calisto.add_surfaces(calisto_trapezoidal_fins, -1.168)
+    calisto.add_sensor(ideal_accelerometer, -0.1180124376577797)
+    calisto.add_sensor(ideal_gyroscope, -0.1180124376577797)
     return calisto
 
 
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 43a42942c..b94d2bc7f 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -40,7 +40,7 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
     sim_accel = flight_calisto_accel_gyro.acceleration(time)
 
     # tolerance is bounded to numerical errors in the transformation matrixes
-    assert np.allclose(a, sim_accel, atol=1e-2)
+    assert np.allclose(a, sim_accel, atol=1e-12)
 
     gyroscope = flight_calisto_accel_gyro.rocket.sensors[1].component
     time, wx, wy, wz = zip(*gyroscope.measured_data)
@@ -52,4 +52,4 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
     flight_wy = np.array(flight_calisto_accel_gyro.w2(time))
     flight_wz = np.array(flight_calisto_accel_gyro.w3(time))
     sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
-    assert np.allclose(w, sim_w, atol=1e-8)
+    assert np.allclose(w, sim_w, atol=1e-12)

From 5c37f06332c1caf98d8b1efd46dd74a01bcd9d57 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 15 Apr 2024 16:51:34 +0200
Subject: [PATCH 018/120] BUG: handle zero norm differently due to
 numpy.float64

---
 rocketpy/mathutils/vector_matrix.py | 13 ++++++-------
 1 file changed, 6 insertions(+), 7 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 6e93b3151..7900f30cc 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -989,15 +989,14 @@ def transformation(quaternion):
             The transformation matrix from frame B to frame A.
         """
         q_w, q_x, q_y, q_z = quaternion
-        # #normalize quaternion
+        # normalize quaternion
         q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
-        try:
-            q_w /= q_norm
-            q_x /= q_norm
-            q_y /= q_norm
-            q_z /= q_norm
-        except ZeroDivisionError:
+        if q_norm == 0:
             return Matrix.identity()
+        q_w /= q_norm
+        q_x /= q_norm
+        q_y /= q_norm
+        q_z /= q_norm
         # precompute common terms
         q_x2 = q_x**2
         q_y2 = q_y**2

From 8d649980c0e9e5a8355932957f866dcd4c51f84a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 15 Apr 2024 17:02:27 +0200
Subject: [PATCH 019/120] MNT: quantization typos

---
 tests/unit/test_sensors.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 3dbce1d34..81448c2a4 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -214,7 +214,7 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.5)
 
 
-def test_quatization_accelerometer(quantized_accelerometer):
+def test_quantization_accelerometer(quantized_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
@@ -247,7 +247,7 @@ def test_quatization_accelerometer(quantized_accelerometer):
     assert quantized_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
 
 
-def test_quatization_gyroscope(quantized_gyroscope):
+def test_quantization_gyroscope(quantized_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
     measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """

From 28da8f3a2872302785830fc7ac8eb77ba026aea9 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 15 Apr 2024 17:08:52 +0200
Subject: [PATCH 020/120] DOCS: mention Hadamard product

---
 rocketpy/mathutils/vector_matrix.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 7900f30cc..7a658de04 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -243,7 +243,8 @@ def __xor__(self, other):
         )
 
     def __and__(self, other):
-        """Element wise multiplication between two R3 vectors.
+        """Element wise multiplication between two R3 vectors. Also known as
+        Hadamard product.
 
         Parameters
         ----------

From cef72a0cb398a4b3471c9682f44bc5be019ab417 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 15 Apr 2024 17:34:23 +0200
Subject: [PATCH 021/120] DOC: complete sensors class docstrings

---
 rocketpy/sensors/accelerometer.py | 67 +++++++++++++++++++++++++--
 rocketpy/sensors/gyroscope.py     | 76 ++++++++++++++++++++++++++-----
 rocketpy/sensors/sensors.py       | 45 +++++++++++++++++-
 3 files changed, 170 insertions(+), 18 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 8599816bb..38e423439 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -6,8 +6,53 @@
 
 
 class Accelerometer(Sensors):
-    """
-    Class for the accelerometer sensor
+    """Class for the accelerometer sensor
+
+    Attributes
+    ----------
+    type : str
+        Type of the sensor, in this case "Accelerometer".
+    consider_gravity : bool
+        Whether the sensor considers the effect of gravity on the acceleration.
+    prints : _AccelerometerPrints
+        Object that contains the print functions for the sensor.
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    orientation : tuple, list
+        Orientation of the sensor in the rocket.
+    measurement_range : float, tuple
+        The measurement range of the sensor in m/s^2.
+    resolution : float
+        The resolution of the sensor in m/s^2/LSB.
+    noise_density : float, list
+        The noise density of the sensor in m/s^2/√Hz.
+    random_walk : float, list
+        The random walk of the sensor in m/s^2/√Hz.
+    constant_bias : float, list
+        The constant bias of the sensor in m/s^2.
+    operating_temperature : float
+        The operating temperature of the sensor in degrees Celsius.
+    temperature_bias : float, list
+        The temperature bias of the sensor in m/s^2/°C.
+    temperature_scale_factor : float, list
+        The temperature scale factor of the sensor in %/°C.
+    cross_axis_sensitivity : float
+        The cross axis sensitivity of the sensor in percentage.
+    name : str
+        The name of the sensor.
+    rotation_matrix : Matrix
+        The rotation matrix of the sensor from the sensor frame to the rocket
+        frame of reference.
+    normal_vector : Vector
+        The normal vector of the sensor in the rocket frame of reference.
+    _random_walk_drift : Vector
+        The random walk drift of the sensor in m/s^2.
+    measurement : float
+        The measurement of the sensor after quantization, noise and temperature
+        drift.
+    measured_data : list
+        The stored measured data of the sensor after quantization, noise and
+        temperature drift.
     """
 
     def __init__(
@@ -32,7 +77,7 @@ def __init__(
         Parameters
         ----------
         sampling_rate : float
-            Sample rate of the sensor
+            Sample rate of the sensor in Hz.
         orientation : tuple, list, optional
             Orientation of the sensor in the rocket. The orientation can be
             given as:
@@ -124,8 +169,20 @@ def __init__(
         self.prints = _AccelerometerPrints(self)
 
     def measure(self, t, u, u_dot, relative_position, gravity, *args):
-        """
-        Measure the acceleration of the rocket
+        """Measure the acceleration of the rocket
+
+        Parameters
+        ----------
+        t : float
+            Current time
+        u : list
+            State vector of the rocket
+        u_dot : list
+            Derivative of the state vector of the rocket
+        relative_position : Vector
+            Position of the sensor relative to the rocket cdm
+        gravity : float
+            Acceleration due to gravity
         """
         # Linear acceleration of rocket cdm in inertial frame
         gravity = (
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index de26ed7ff..21053edbe 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -6,8 +6,53 @@
 
 
 class Gyroscope(Sensors):
-    """
-    Class for the gyroscope sensor
+    """Class for the gyroscope sensor
+
+    Attributes
+    ----------
+    type : str
+        Type of the sensor, in this case "Gyroscope".
+    acceleration_sensitivity : float, list
+        Sensitivity of the sensor to linear acceleration in rad/s/g.
+    prints : _GyroscopePrints
+        Object that contains the print functions for the sensor.
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    orientation : tuple, list
+        Orientation of the sensor in the rocket.
+    measurement_range : float, tuple
+        The measurement range of the sensor in the rad/s.
+    resolution : float
+        The resolution of the sensor in rad/s/LSB.
+    noise_density : float, list
+        The noise density of the sensor in rad/s/√Hz.
+    random_walk : float, list
+        The random walk of the sensor in rad/s/√Hz.
+    constant_bias : float, list
+        The constant bias of the sensor in rad/s.
+    operating_temperature : float
+        The operating temperature of the sensor in degrees Celsius.
+    temperature_bias : float, list
+        The temperature bias of the sensor in rad/s/°C.
+    temperature_scale_factor : float, list
+        The temperature scale factor of the sensor in %/°C.
+    cross_axis_sensitivity : float
+        The cross axis sensitivity of the sensor in percentage.
+    name : str
+        The name of the sensor.
+    rotation_matrix : Matrix
+        The rotation matrix of the sensor from the sensor frame to the rocket
+        frame of reference.
+    normal_vector : Vector
+        The normal vector of the sensor in the rocket frame of reference.
+    _random_walk_drift : Vector
+        The random walk drift of the sensor in rad/s.
+    measurement : float
+        The measurement of the sensor after quantization, noise and temperature
+        drift.
+    measured_data : list
+        The stored measured data of the sensor after quantization, noise and
+        temperature drift.
     """
 
     def __init__(
@@ -32,7 +77,7 @@ def __init__(
         Parameters
         ----------
         sampling_rate : float
-            Sample rate of the sensor
+            Sample rate of the sensor in Hz.
         orientation : tuple, list, optional
             Orientation of the sensor in the rocket. The orientation can be
             given as:
@@ -126,8 +171,18 @@ def __init__(
         self.prints = _GyroscopePrints(self)
 
     def measure(self, t, u, u_dot, relative_position, *args):
-        """
-        Measure the angular velocity of the rocket
+        """Measure the angular velocity of the rocket
+
+        Parameters
+        ----------
+        t : float
+            Time at which the measurement is taken
+        u : list
+            State vector of the rocket
+        u_dot : list
+            Time derivative of the state vector of the rocket
+        relative_position : Vector
+            Vector from the rocket's center of mass to the sensor
         """
         # Angular velocity of the rocket in the rocket frame
         omega = Vector(u[10:13])
@@ -164,18 +219,17 @@ def apply_acceleration_sensitivity(
         ----------
         omega : Vector
             The angular velocity to apply acceleration sensitivity to
-        cache : tuple
-            The cache of the rocket state
+        u_dot : list
+            The time derivative of the state vector
         relative_position : Vector
-            The vector from the rocket's center of mass to the sensor in the
-            rocket frame
+            The vector from the rocket's center of mass to the sensor
         rotation_matrix : Matrix
-            The rotation matrix from the inertial frame to the sensor frame
+            The rotation matrix from the rocket frame to the sensor frame
 
         Returns
         -------
         Vector
-            The angular velocity with applied acceleration sensitivity
+            The angular velocity with the acceleration sensitivity applied
         """
         # Linear acceleration of rocket cdm in inertial frame
         a_I = Vector(u_dot[3:6])
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 8a626b941..fadb9ae73 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -6,8 +6,49 @@
 
 
 class Sensors(ABC):
-    """
-    Abstract class for sensors
+    """Abstract class for sensors
+
+    Attributes
+    ----------
+    type : str
+        Type of the sensor (e.g. Accelerometer, Gyroscope).
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    orientation : tuple, list
+        Orientation of the sensor in the rocket.
+    measurement_range : float, tuple
+        The measurement range of the sensor in the sensor units.
+    resolution : float
+        The resolution of the sensor in sensor units/LSB.
+    noise_density : float, list
+        The noise density of the sensor in sensor units/√Hz.
+    random_walk : float, list
+        The random walk of the sensor in sensor units/√Hz.
+    constant_bias : float, list
+        The constant bias of the sensor in sensor units.
+    operating_temperature : float
+        The operating temperature of the sensor in degrees Celsius.
+    temperature_bias : float, list
+        The temperature bias of the sensor in sensor units/°C.
+    temperature_scale_factor : float, list
+        The temperature scale factor of the sensor in %/°C.
+    cross_axis_sensitivity : float
+        The cross axis sensitivity of the sensor in percentage.
+    name : str
+        The name of the sensor.
+    rotation_matrix : Matrix
+        The rotation matrix of the sensor from the sensor frame to the rocket
+        frame of reference.
+    normal_vector : Vector
+        The normal vector of the sensor in the rocket frame of reference.
+    _random_walk_drift : Vector
+        The random walk drift of the sensor in sensor units.
+    measurement : float
+        The measurement of the sensor after quantization, noise and temperature
+        drift.
+    measured_data : list
+        The stored measured data of the sensor after quantization, noise and
+        temperature drift.
     """
 
     def __init__(

From 5f8f1f453331d091b11ae362f7a3404c478c2f77 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 29 Apr 2024 17:32:54 +0200
Subject: [PATCH 022/120] Squashed commit of the following:

commit b18ae9cc04e5460ca07c8c3be50f60ef44204603
Merge: 67515f6 9a8e0c1
Author: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
Date:   Thu Apr 25 18:15:24 2024 -0400

    Merge branch 'develop' into bug/airbrakes-postprocess

commit 67515f64be6f1702d6497055fbb071f888ac5c09
Author: MateusStano <mateusstano@usp.br>
Date:   Thu Apr 25 23:02:11 2024 +0200

    ENH: automatically disable time overshoot for controllers

commit f60c53bfb138abbb0b19c1438daddb8c9777a2ad
Merge: 4974e8d 3df7586
Author: MateusStano <mateusstano@usp.br>
Date:   Thu Apr 25 22:53:10 2024 +0200

    Merge branch 'bug/airbrakes-postprocess' of https://github.com/RocketPy-Team/RocketPy into bug/airbrakes-postprocess

commit 4974e8d7417e0d102088d40007b3c429aed1b896
Author: MateusStano <mateusstano@usp.br>
Date:   Thu Apr 25 22:52:48 2024 +0200

    BUG: initialize state derivatives for controllers

commit a49baf4d0160ca01282b101daa9444b3872b44f7
Author: MateusStano <mateusstano@usp.br>
Date:   Thu Apr 25 22:52:13 2024 +0200

    MNT: move controller initialization to private method

commit 9a8e0c1920914c3f916ea8c8f7e4c8373487af2d
Merge: 14375ed 2cbaa77
Author: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date:   Thu Apr 25 15:37:05 2024 -0300

    Merge pull request #580 from RocketPy-Team/mnt/modularize-rocket-draw

    MNT: Modularize Rocket Draw

commit 2cbaa77e91f23a6f32386082a079d9852021917b
Merge: 822a89e 14375ed
Author: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date:   Thu Apr 25 11:44:22 2024 -0300

    Merge branch 'develop' into mnt/modularize-rocket-draw

commit 3df758642662b808664d76783e2d6a53081dd39a
Merge: bf8c68b 14375ed
Author: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
Date:   Thu Apr 25 06:49:58 2024 -0400

    Merge branch 'develop' into bug/airbrakes-postprocess

commit 14375ed9aad490e97603cf3ff551b198e06343ca
Merge: c31c6f8 b899064
Author: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
Date:   Thu Apr 25 06:47:36 2024 -0400

    Merge pull request #588 from RocketPy-Team/enh/exponential-backoff-decorator

    ENH: Exponential backoff decorator (fix #449)

commit c31c6f87b6fb210501f80e90d251419374c8b431
Merge: a011c5a 684b997
Author: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
Date:   Thu Apr 25 06:45:26 2024 -0400

    Merge pull request #587 from RocketPy-Team/mnt/delete-cached-property

    DEP: delete deprecated rocketpy.tools.cached_property

commit b8990644616801a9c25e91ae141f2cacf8d7501c
Author: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date:   Fri Apr 19 12:13:23 2024 -0400

    DEV: adds PR 588 to the CHANGELOG

commit a8a185eca86883a71580a68e6030c760e5cbd8d5
Author: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date:   Fri Apr 19 12:08:58 2024 -0400

    TST: Fix tests with Environment class after exponential_backoff decorator was used

commit d0fbcd72e049618ed14f21a9355d88eee98c3792
Author: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date:   Fri Apr 19 12:07:45 2024 -0400

    MNT: Refactor code to use the exponential_backoff decorator

commit ccd78af7d29e4036d92ffb731e2fca4c38212377
Author: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date:   Fri Apr 19 12:07:17 2024 -0400

    ENH: Add exponential backoff decorator to tools.py

commit 684b9979b1d194fcb94e5c4da9bcf006f3c831ad
Author: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date:   Thu Apr 18 21:47:19 2024 -0400

    DEV: Adds PR 587 to the CHANGELOG.md

commit bb0f46a267a79787f4af32b2c7e5cf9fcaf1c90d
Author: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date:   Thu Apr 18 21:41:38 2024 -0400

    MNT: refactors cached_property imports

commit afb3b3227262c33bd49579db87fc85a482f41204
Author: dyu056 <yudaniel888@hotmail.com>
Date:   Fri Jan 26 00:35:36 2024 +1300

    Completed changes

commit bf8c68bdaa477580e45f44bf5df31ba647bb1dc9
Merge: aaa3f7b a011c5a
Author: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
Date:   Thu Apr 18 21:17:06 2024 -0400

    Merge branch 'develop' into bug/airbrakes-postprocess

commit a011c5af1b2840186ebb6ecb89760a79f242addd
Merge: 624cc15 6b26f61
Author: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
Date:   Thu Apr 18 15:12:40 2024 -0400

    Merge pull request #585 from RocketPy-Team/enh/swap-diff-for-flow-rate

    BUG: Swap `rocket.total_mass.differentiate` for `motor.total_mass_flow rate`

commit 6b26f6153d070d269a872314f85d70f7a6d25443
Author: MateusStano <mateusstano@usp.br>
Date:   Wed Apr 17 22:19:16 2024 +0200

    DEV: changelog

commit 8ee2c95f6961e94f93ef569303588c643647778f
Author: MateusStano <mateusstano@usp.br>
Date:   Wed Apr 17 22:16:59 2024 +0200

    ENH: create rocket total_mass_flow_rate attribute

commit aaa3f7b953d7450eec6056c723f83afa82a67bbb
Author: MateusStano <mateusstano@usp.br>
Date:   Mon Apr 15 16:52:49 2024 +0200

    DOCS: change accelerations names in docs

commit 7fe3d0ba3b805f4a134eb399be796f7cb2e20425
Author: MateusStano <mateusstano@usp.br>
Date:   Mon Apr 15 16:12:39 2024 +0200

    ENH: optmize post process loop

commit a66fc53323248c74db32874f8dff8ee8e5cd4289
Author: MateusStano <mateusstano@usp.br>
Date:   Mon Apr 15 15:18:37 2024 +0200

    ENH: add reset function

commit b9a97a454880a3ffbb7194c9807304dfbea0899e
Author: MateusStano <mateusstano@usp.br>
Date:   Mon Apr 15 15:06:01 2024 +0200

    ENH: add warning for improper time_overshoot

commit 830ea15445d9f30cf520981388e07557fe2f8da3
Author: MateusStano <mateusstano@usp.br>
Date:   Mon Apr 15 15:05:31 2024 +0200

    ENH: refactor retrieve arrays cached properties and controller sim post processing

commit e2a94c8577bf2f2bcfe19a167793cac6ea3b5f2b
Author: MateusStano <mateusstano@usp.br>
Date:   Tue Apr 9 18:03:08 2024 +0200

    TST: fix tests

commit e5c75334b08313de1a2bfbeda15dd22571120187
Author: MateusStano <mateusstano@usp.br>
Date:   Tue Apr 9 17:59:22 2024 +0200

    ENH: use mass_flow_rate instead of differentiate

commit 822a89ea4b5eebede774ba8341819e99cef735fd
Merge: e3e1a59 624cc15
Author: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date:   Sun Apr 7 13:52:02 2024 +0200

    Merge branch 'develop' into mnt/modularize-rocket-draw

commit e3e1a59df277151fa41bb53659b41ef1fc197990
Author: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date:   Thu Apr 4 14:53:37 2024 +0200

    DEV: fix changelog order

commit 624cc15cdee1806f8d08516c367a4455a9a37fd2
Merge: 0a4d89b 61bf4d7
Author: Pedro Henrique Marinho Bressan <87212571+phmbressan@users.noreply.github.com>
Date:   Tue Apr 2 14:23:05 2024 -0300

    Merge pull request #565 from RocketPy-Team/doc/environment-docstring

    DOC: Improvements of Environment docstring phrasing.

commit 61bf4d7aa3961d4e6d3a2911379027a4401345c4
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Mon Apr 1 15:00:10 2024 -0300

    MNT: add docs change to CHANGELOG.

commit 9c1a4619ee2beb273d81f63fa78343dfa84ca790
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Mon Apr 1 14:47:03 2024 -0300

    DOC: fix typing issues regarding Environment docs.

commit 477620890952571071623f14bf8cdd7a03838bad
Author: Pedro Henrique Marinho Bressan <87212571+phmbressan@users.noreply.github.com>
Date:   Fri Mar 29 08:47:18 2024 -0300

    DOC: Update Longitude value ranges.

    Co-authored-by: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>

commit 32a28c12276521bbacd60a6a80f75a136ddb07f9
Merge: 27dd73d 0a4d89b
Author: Pedro Henrique Marinho Bressan <87212571+phmbressan@users.noreply.github.com>
Date:   Thu Mar 28 18:26:46 2024 -0300

    Merge branch 'develop' into doc/environment-docstring

commit 27dd73d24fa82f3cbf066d6edb5aa3063b102099
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Thu Mar 28 18:24:23 2024 -0300

    DOC: standardize grammar on time zones.

commit 4b42c9ec173188fa0022fe17a198b6982534ffe3
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Thu Mar 28 18:20:01 2024 -0300

    DOC: clarify timezones and dates Environment docs.

commit 95b61efc8070f59373e81e049eba7dd83c5f7520
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Thu Mar 28 16:38:17 2024 -0300

    DOC: specify latitude and longitude defaults.

commit 6b84c03bdaafd96c140067cfbf0a00fe05556d1e
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Mon Mar 25 19:53:37 2024 -0300

    DOC: improve wording of Environment init.

    Co-authored-by: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>

commit 826efcc3125a0cf1d9a24ce1039135a6877e742a
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Sun Mar 24 16:47:14 2024 -0300

    DOC: specify datum as optional.

commit a2aa71467b3be87c8124343cd49768c1ac4d6a9d
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Sun Mar 24 16:41:39 2024 -0300

    DOC: add examples and improvements to Environment gravity docstring.

commit 51bdd918b8143a419f34ef7b74847b6d3b359914
Author: MateusStano <mateusstano@usp.br>
Date:   Sun Mar 24 15:14:45 2024 +0100

    MNT: changelog

commit 6805e3277f3b576e813605a5508397e060e9f927
Author: MateusStano <mateusstano@usp.br>
Date:   Sun Mar 24 14:05:00 2024 +0100

    MNT: refactor rocket drawing plot methods

commit 3cc91e7523348fee4fc48b80174cd6229607a55e
Merge: f637a9d 65b3315
Author: Pedro Henrique Marinho Bressan <87212571+phmbressan@users.noreply.github.com>
Date:   Thu Feb 29 20:06:09 2024 -0300

    Merge branch 'develop' into doc/environment-docstring

commit f637a9dc80fd7424e9defc68397c96ef73218297
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Thu Feb 29 17:49:38 2024 -0300

    STY: run black for code linting.

commit 9198ac704f2d5cd1c1448da05c44b9a129a3b83c
Author: Pedro Bressan <phmbressan@usp.br>
Date:   Thu Feb 29 17:46:23 2024 -0300

    DOC: phrasing improvements of Environment docstring.
---
 CHANGELOG.md                                  |   5 +
 rocketpy/environment/environment.py           | 369 ++++++++++++------
 rocketpy/environment/environment_analysis.py  |   8 +-
 rocketpy/mathutils/function.py                |   6 +-
 rocketpy/mathutils/vector_matrix.py           |   3 +-
 rocketpy/motors/hybrid_motor.py               |   7 +-
 rocketpy/motors/liquid_motor.py               |   7 +-
 rocketpy/motors/motor.py                      |   6 +-
 rocketpy/motors/solid_motor.py                |   7 +-
 rocketpy/motors/tank_geometry.py              |   5 +-
 rocketpy/plots/flight_plots.py                |   7 +-
 rocketpy/plots/rocket_plots.py                |  46 ++-
 rocketpy/rocket/aero_surface.py               |  13 +-
 rocketpy/rocket/rocket.py                     |   4 +
 rocketpy/simulation/flight.py                 | 285 +++++++++-----
 rocketpy/tools.py                             |  49 ++-
 .../environment/environment_fixtures.py       |   5 +-
 tests/test_environment.py                     |  10 +-
 tests/test_flight.py                          |  14 +-
 tests/unit/test_environment.py                |   2 +-
 20 files changed, 534 insertions(+), 324 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 87e3c50a4..4d2509adf 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -32,11 +32,15 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
 
 ### Added
 
+- ENH: Exponential backoff decorator (fix #449) [#588](https://github.com/RocketPy-Team/RocketPy/pull/588)
 - ENH: Add new stability margin properties to Flight class [#572](https://github.com/RocketPy-Team/RocketPy/pull/572)
 - ENH: adds `Function.remove_outliers` method [#554](https://github.com/RocketPy-Team/RocketPy/pull/554)
 
 ### Changed
 
+- DEP: delete deprecated rocketpy.tools.cached_property [#587](https://github.com/RocketPy-Team/RocketPy/pull/587) 
+- MNT: Modularize Rocket Draw [#580](https://github.com/RocketPy-Team/RocketPy/pull/580)
+- DOC: Improvements of Environment docstring phrasing [#565](https://github.com/RocketPy-Team/RocketPy/pull/565)
 - MNT: Refactor flight prints module [#579](https://github.com/RocketPy-Team/RocketPy/pull/579)
 - DOC: Convert CompareFlights example notebooks to .rst files [#576](https://github.com/RocketPy-Team/RocketPy/pull/576)
 - MNT: Refactor inertia calculations using parallel axis theorem [#573] (https://github.com/RocketPy-Team/RocketPy/pull/573)
@@ -44,6 +48,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
 
 ### Fixed
 
+- BUG: Swap rocket.total_mass.differentiate for motor.total_mass_flow rate [#585](https://github.com/RocketPy-Team/RocketPy/pull/585)
 - BUG: export_eng 'Motor' method would not work for liquid motors. [#559](https://github.com/RocketPy-Team/RocketPy/pull/559) 
 
 ## [v1.2.2] - 2024-03-22
diff --git a/rocketpy/environment/environment.py b/rocketpy/environment/environment.py
index 546d446e8..5a845a173 100644
--- a/rocketpy/environment/environment.py
+++ b/rocketpy/environment/environment.py
@@ -3,7 +3,7 @@
 import re
 import warnings
 from collections import namedtuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 
 import numpy as np
 import numpy.ma as ma
@@ -13,6 +13,7 @@
 from ..mathutils.function import Function, funcify_method
 from ..plots.environment_plots import _EnvironmentPlots
 from ..prints.environment_prints import _EnvironmentPrints
+from ..tools import exponential_backoff
 
 try:
     import netCDF4
@@ -57,8 +58,7 @@ class Environment:
     Environment.datum : string
         The desired reference ellipsoid model, the following options are
         available: "SAD69", "WGS84", "NAD83", and "SIRGAS2000". The default
-        is "SIRGAS2000", then this model will be used if the user make some
-        typing mistake
+        is "SIRGAS2000".
     Environment.initial_east : float
         Launch site East UTM coordinate
     Environment.initial_north :  float
@@ -74,7 +74,7 @@ class Environment:
         Launch site E/W hemisphere
     Environment.elevation : float
         Launch site elevation.
-    Environment.date : datetime
+    Environment.datetime_date : datetime
         Date time of launch in UTC.
     Environment.local_date : datetime
         Date time of launch in the local time zone, defined by
@@ -276,49 +276,70 @@ def __init__(
         timezone="UTC",
         max_expected_height=80000.0,
     ):
-        """Initialize Environment class, saving launch rail length,
-        launch date, location coordinates and elevation. Note that
-        by default the standard atmosphere is loaded until another
+        """Initializes the Environment class, capturing essential parameters of
+        the launch site, including the launch date, geographical coordinates,
+        and elevation. This class is designed to calculate crucial variables
+        for the Flight simulation, such as atmospheric air pressure, density,
+        and gravitational acceleration.
+
+        Note that the default atmospheric model is the International Standard
+        Atmosphere as defined by ISO 2533 unless specified otherwise in
+        :meth:`Environment.set_atmospheric_model`.
 
         Parameters
         ----------
         gravity : int, float, callable, string, array, optional
             Surface gravitational acceleration. Positive values point the
-            acceleration down. If None, the Somigliana formula is used to
-        date : array, optional
-            Array of length 4, stating (year, month, day, hour (UTC))
-            of rocket launch. Must be given if a Forecast, Reanalysis
+            acceleration down. If None, the Somigliana formula is used.
+            See :meth:`Environment.set_gravity_model` for more information.
+        date : list or tuple, optional
+            List or tuple of length 4, stating (year, month, day, hour) in the
+            time zone of the parameter ``timezone``.
+            Alternatively, can be a ``datetime`` object specifying launch
+            date and time. The dates are stored as follows:
+
+            - :attr:`Environment.local_date`: Local time of launch in
+              the time zone specified by the parameter ``timezone``.
+
+            - :attr:`Environment.datetime_date`: UTC time of launch.
+
+            Must be given if a Forecast, Reanalysis
             or Ensemble, will be set as an atmospheric model.
+            Default is None.
+            See :meth:`Environment.set_date` for more information.
         latitude : float, optional
             Latitude in degrees (ranging from -90 to 90) of rocket
             launch location. Must be given if a Forecast, Reanalysis
             or Ensemble will be used as an atmospheric model or if
-            Open-Elevation will be used to compute elevation.
+            Open-Elevation will be used to compute elevation. Positive
+            values correspond to the North. Default value is 0, which
+            corresponds to the equator.
         longitude : float, optional
-            Longitude in degrees (ranging from -180 to 360) of rocket
+            Longitude in degrees (ranging from -180 to 180) of rocket
             launch location. Must be given if a Forecast, Reanalysis
             or Ensemble will be used as an atmospheric model or if
-            Open-Elevation will be used to compute elevation.
+            Open-Elevation will be used to compute elevation. Positive
+            values correspond to the East. Default value is 0, which
+            corresponds to the Greenwich Meridian.
         elevation : float, optional
             Elevation of launch site measured as height above sea
             level in meters. Alternatively, can be set as
             'Open-Elevation' which uses the Open-Elevation API to
             find elevation data. For this option, latitude and
             longitude must also be specified. Default value is 0.
-        datum : string
+        datum : string, optional
             The desired reference ellipsoidal model, the following options are
             available: "SAD69", "WGS84", "NAD83", and "SIRGAS2000". The default
-            is "SIRGAS2000", then this model will be used if the user make some
-            typing mistake.
+            is "SIRGAS2000".
         timezone : string, optional
             Name of the time zone. To see all time zones, import pytz and run
-            print(pytz.all_timezones). Default time zone is "UTC".
+            ``print(pytz.all_timezones)``. Default time zone is "UTC".
         max_expected_height : float, optional
             Maximum altitude in meters to keep weather data. The altitude must
             be above sea level (ASL). Especially useful for visualization.
             Can be altered as desired by doing `max_expected_height = number`.
             Depending on the atmospheric model, this value may be automatically
-            mofified.
+            modified.
 
         Returns
         -------
@@ -396,15 +417,57 @@ def set_date(self, date, timezone="UTC"):
 
         Parameters
         ----------
-        date : Datetime
-            Datetime object specifying launch date and time.
+        date : list, tuple, datetime
+            List or tuple of length 4, stating (year, month, day, hour) in the
+            time zone of the parameter ``timezone``. See Notes for more
+            information.
+            Alternatively, can be a ``datetime`` object specifying launch
+            date and time.
         timezone : string, optional
             Name of the time zone. To see all time zones, import pytz and run
-            print(pytz.all_timezones). Default time zone is "UTC".
+            ``print(pytz.all_timezones)``. Default time zone is "UTC".
 
         Returns
         -------
         None
+
+        Notes
+        -----
+        - If the ``date`` is given as a list or tuple, it should be in the same
+          time zone as specified by the ``timezone`` parameter. This local
+          time will be available in the attribute :attr:`Environment.local_date`
+          while the UTC time will be available in the attribute
+          :attr:`Environment.datetime_date`.
+
+        - If the ``date`` is given as a ``datetime`` object without a time zone,
+          it will be assumed to be in the same time zone as specified by the
+          ``timezone`` parameter. However, if the ``datetime`` object has a time
+          zone specified in its ``tzinfo`` attribute, the ``timezone``
+          parameter will be ignored.
+
+        Examples
+        --------
+
+        Let's set the launch date as an list:
+
+        >>> date = [2000, 1, 1, 13] # January 1st, 2000 at 13:00 UTC+1
+        >>> env = Environment()
+        >>> env.set_date(date, timezone="Europe/Rome")
+        >>> print(env.datetime_date) # Get UTC time
+        2000-01-01 12:00:00+00:00
+        >>> print(env.local_date)
+        2000-01-01 13:00:00+01:00
+
+        Now let's set the launch date as a ``datetime`` object:
+
+        >>> from datetime import datetime
+        >>> date = datetime(2000, 1, 1, 13, 0, 0)
+        >>> env = Environment()
+        >>> env.set_date(date, timezone="Europe/Rome")
+        >>> print(env.datetime_date) # Get UTC time
+        2000-01-01 12:00:00+00:00
+        >>> print(env.local_date)
+        2000-01-01 13:00:00+01:00
         """
         # Store date and configure time zone
         self.timezone = timezone
@@ -458,23 +521,66 @@ def set_location(self, latitude, longitude):
                 self.atmospheric_model_file, self.atmospheric_model_dict
             )
 
-        # Return None
-
-    def set_gravity_model(self, gravity):
-        """Sets the gravity model to be used in the simulation based on the
-        given user input to the gravity parameter.
+    def set_gravity_model(self, gravity=None):
+        """Defines the gravity model based on the given user input to the
+        gravity parameter. The gravity model is responsible for computing the
+        gravity acceleration at a given height above sea level in meters.
 
         Parameters
         ----------
-        gravity : None or Function source
-            If None, the Somigliana formula is used to compute the gravity
-            acceleration. Otherwise, the user can provide a Function object
-            representing the gravity model.
+        gravity : int, float, callable, string, list, optional
+            The gravitational acceleration in m/s² to be used in the
+            simulation, this value is positive when pointing downwards.
+            The input type can be one of the following:
+
+            - ``int`` or ``float``: The gravity acceleration is set as a\
+              constant function with respect to height;
+
+            - ``callable``: This callable should receive the height above\
+              sea level in meters and return the gravity acceleration;
+
+            - ``list``: The datapoints should be structured as\
+              ``[(h_i,g_i), ...]`` where ``h_i`` is the height above sea\
+              level in meters and ``g_i`` is the gravity acceleration in m/s²;
+
+            - ``string``: The string should correspond to a path to a CSV file\
+              containing the gravity acceleration data;
+
+            - ``None``: The Somigliana formula is used to compute the gravity\
+              acceleration.
+
+            This parameter is used as a :class:`Function` object source, check\
+            out the available input types for a more detailed explanation.
 
         Returns
         -------
         Function
             Function object representing the gravity model.
+
+        Notes
+        -----
+        This method **does not** set the gravity acceleration, it only returns
+        a :class:`Function` object representing the gravity model.
+
+        Examples
+        --------
+        Let's prepare a `Environment` object with a constant gravity
+        acceleration:
+
+        >>> g_0 = 9.80665
+        >>> env_cte_g = Environment(gravity=g_0)
+        >>> env_cte_g.gravity([0, 100, 1000])
+        [9.80665, 9.80665, 9.80665]
+
+        It's also possible to variate the gravity acceleration by defining
+        its function of height:
+
+        >>> R_t = 6371000
+        >>> g_func = lambda h : g_0 * (R_t / (R_t + h))**2
+        >>> env_var_g = Environment(gravity=g_func)
+        >>> g = env_var_g.gravity(1000)
+        >>> print(f"{g:.6f}")
+        9.803572
         """
         if gravity is None:
             return self.somigliana_gravity.set_discrete(
@@ -500,7 +606,7 @@ def max_expected_height(self, value):
 
     @funcify_method("height (m)", "gravity (m/s²)")
     def somigliana_gravity(self, height):
-        """Computes the gravity acceleration with the Somigliana formula.
+        """Computes the gravity acceleration with the Somigliana formula [1]_.
         An height correction is applied to the normal gravity that is
         accurate for heights used in aviation. The formula is based on the
         WGS84 ellipsoid, but is accurate for other reference ellipsoids.
@@ -514,6 +620,10 @@ def somigliana_gravity(self, height):
         -------
         Function
             Function object representing the gravity model.
+
+        References
+        ----------
+        .. [1] https://en.wikipedia.org/wiki/Theoretical_gravity#Somigliana_equation
         """
         a = 6378137.0  # semi_major_axis
         f = 1 / 298.257223563  # flattening_factor
@@ -571,18 +681,9 @@ def set_elevation(self, elevation="Open-Elevation"):
 
         #     self.elevation = elev
 
-        elif self.latitude != None and self.longitude != None:
-            try:
-                print("Fetching elevation from open-elevation.com...")
-                request_url = "https://api.open-elevation.com/api/v1/lookup?locations={:f},{:f}".format(
-                    self.latitude, self.longitude
-                )
-                response = requests.get(request_url)
-                results = response.json()["results"]
-                self.elevation = results[0]["elevation"]
-                print("Elevation received:", self.elevation)
-            except:
-                raise RuntimeError("Unable to reach Open-Elevation API servers.")
+        elif self.latitude is not None and self.longitude is not None:
+            self.elevation = self.__fetch_open_elevation()
+            print("Elevation received: ", self.elevation)
         else:
             raise ValueError(
                 "Latitude and longitude must be set to use"
@@ -1194,26 +1295,8 @@ def set_atmospheric_model(
                     "v_wind": "vgrdprs",
                 }
                 # Attempt to get latest forecast
-                time_attempt = datetime.utcnow()
-                success = False
-                attempt_count = 0
-                while not success and attempt_count < 10:
-                    time_attempt -= timedelta(hours=6 * attempt_count)
-                    file = "https://nomads.ncep.noaa.gov/dods/gens_bc/gens{:04d}{:02d}{:02d}/gep_all_{:02d}z".format(
-                        time_attempt.year,
-                        time_attempt.month,
-                        time_attempt.day,
-                        6 * (time_attempt.hour // 6),
-                    )
-                    try:
-                        self.process_ensemble(file, dictionary)
-                        success = True
-                    except OSError:
-                        attempt_count += 1
-                if not success:
-                    raise RuntimeError(
-                        "Unable to load latest weather data for GEFS through " + file
-                    )
+                self.__fetch_gefs_ensemble(dictionary)
+
             elif file == "CMC":
                 # Define dictionary
                 dictionary = {
@@ -1229,27 +1312,7 @@ def set_atmospheric_model(
                     "u_wind": "ugrdprs",
                     "v_wind": "vgrdprs",
                 }
-                # Attempt to get latest forecast
-                time_attempt = datetime.utcnow()
-                success = False
-                attempt_count = 0
-                while not success and attempt_count < 10:
-                    time_attempt -= timedelta(hours=12 * attempt_count)
-                    file = "https://nomads.ncep.noaa.gov/dods/cmcens/cmcens{:04d}{:02d}{:02d}/cmcens_all_{:02d}z".format(
-                        time_attempt.year,
-                        time_attempt.month,
-                        time_attempt.day,
-                        12 * (time_attempt.hour // 12),
-                    )
-                    try:
-                        self.process_ensemble(file, dictionary)
-                        success = True
-                    except OSError:
-                        attempt_count += 1
-                if not success:
-                    raise RuntimeError(
-                        "Unable to load latest weather data for CMC through " + file
-                    )
+                self.__fetch_cmc_ensemble(dictionary)
             # Process other forecasts or reanalysis
             else:
                 # Check if default dictionary was requested
@@ -1541,20 +1604,7 @@ def process_windy_atmosphere(self, model="ECMWF"):
             model.
         """
 
-        # Process the model string
-        model = model.lower()
-        if model[-1] == "u":  # case iconEu
-            model = "".join([model[:4], model[4].upper(), model[4 + 1 :]])
-        # Load data from Windy.com: json file
-        url = f"https://node.windy.com/forecast/meteogram/{model}/{self.latitude}/{self.longitude}/?step=undefined"
-        try:
-            response = requests.get(url).json()
-        except:
-            if model == "iconEu":
-                raise ValueError(
-                    "Could not get a valid response for Icon-EU from Windy. Check if the latitude and longitude coordinates set are inside Europe.",
-                )
-            raise
+        response = self.__fetch_atmospheric_data_from_windy(model)
 
         # Determine time index from model
         time_array = np.array(response["data"]["hours"])
@@ -1715,18 +1765,7 @@ def process_wyoming_sounding(self, file):
         None
         """
         # Request Wyoming Sounding from file url
-        response = requests.get(file)
-        if response.status_code != 200:
-            raise ImportError("Unable to load " + file + ".")
-        if len(re.findall("Can't get .+ Observations at", response.text)):
-            raise ValueError(
-                re.findall("Can't get .+ Observations at .+", response.text)[0]
-                + " Check station number and date."
-            )
-        if response.text == "Invalid OUTPUT: specified\n":
-            raise ValueError(
-                "Invalid OUTPUT: specified. Make sure the output is Text: List."
-            )
+        response = self.__fetch_wyoming_sounding(file)
 
         # Process Wyoming Sounding by finding data table and station info
         response_split_text = re.split("(<.{0,1}PRE>)", response.text)
@@ -1852,9 +1891,7 @@ def process_noaaruc_sounding(self, file):
         None
         """
         # Request NOAA Ruc Sounding from file url
-        response = requests.get(file)
-        if response.status_code != 200 or len(response.text) < 10:
-            raise ImportError("Unable to load " + file + ".")
+        response = self.__fetch_noaaruc_sounding(file)
 
         # Split response into lines
         lines = response.text.split("\n")
@@ -3429,6 +3466,110 @@ def set_earth_geometry(self, datum):
                 f"The reference system {datum} for Earth geometry " "is not recognized."
             )
 
+    # Auxiliary functions - Fetching Data from 3rd party APIs
+
+    @exponential_backoff(max_attempts=3, base_delay=1, max_delay=60)
+    def __fetch_open_elevation(self):
+        print("Fetching elevation from open-elevation.com...")
+        request_url = (
+            "https://api.open-elevation.com/api/v1/lookup?locations"
+            f"={self.latitude},{self.longitude}"
+        )
+        try:
+            response = requests.get(request_url)
+        except Exception as e:
+            raise RuntimeError("Unable to reach Open-Elevation API servers.")
+        results = response.json()["results"]
+        return results[0]["elevation"]
+
+    @exponential_backoff(max_attempts=5, base_delay=2, max_delay=60)
+    def __fetch_atmospheric_data_from_windy(self, model):
+        model = model.lower()
+        if model[-1] == "u":  # case iconEu
+            model = "".join([model[:4], model[4].upper(), model[4 + 1 :]])
+        url = (
+            f"https://node.windy.com/forecast/meteogram/{model}/"
+            f"{self.latitude}/{self.longitude}/?step=undefined"
+        )
+        try:
+            response = requests.get(url).json()
+        except Exception as e:
+            if model == "iconEu":
+                raise ValueError(
+                    "Could not get a valid response for Icon-EU from Windy. "
+                    "Check if the coordinates are set inside Europe."
+                )
+        return response
+
+    @exponential_backoff(max_attempts=5, base_delay=2, max_delay=60)
+    def __fetch_wyoming_sounding(self, file):
+        response = requests.get(file)
+        if response.status_code != 200:
+            raise ImportError(f"Unable to load {file}.")
+        if len(re.findall("Can't get .+ Observations at", response.text)):
+            raise ValueError(
+                re.findall("Can't get .+ Observations at .+", response.text)[0]
+                + " Check station number and date."
+            )
+        if response.text == "Invalid OUTPUT: specified\n":
+            raise ValueError(
+                "Invalid OUTPUT: specified. Make sure the output is Text: List."
+            )
+        return response
+
+    @exponential_backoff(max_attempts=5, base_delay=2, max_delay=60)
+    def __fetch_noaaruc_sounding(self, file):
+        response = requests.get(file)
+        if response.status_code != 200 or len(response.text) < 10:
+            raise ImportError("Unable to load " + file + ".")
+
+    @exponential_backoff(max_attempts=5, base_delay=2, max_delay=60)
+    def __fetch_gefs_ensemble(self, dictionary):
+        time_attempt = datetime.now(tz=timezone.utc)
+        success = False
+        attempt_count = 0
+        while not success and attempt_count < 10:
+            time_attempt -= timedelta(hours=6 * attempt_count)
+            file = (
+                f"https://nomads.ncep.noaa.gov/dods/gens_bc/gens"
+                f"{time_attempt.year:04d}{time_attempt.month:02d}"
+                f"{time_attempt.day:02d}/"
+                f"gep_all_{6 * (time_attempt.hour // 6):02d}z"
+            )
+            try:
+                self.process_ensemble(file, dictionary)
+                success = True
+            except OSError:
+                attempt_count += 1
+        if not success:
+            raise RuntimeError(
+                "Unable to load latest weather data for GEFS through " + file
+            )
+
+    @exponential_backoff(max_attempts=5, base_delay=2, max_delay=60)
+    def __fetch_cmc_ensemble(self, dictionary):
+        # Attempt to get latest forecast
+        time_attempt = datetime.now(tz=timezone.utc)
+        success = False
+        attempt_count = 0
+        while not success and attempt_count < 10:
+            time_attempt -= timedelta(hours=12 * attempt_count)
+            file = (
+                f"https://nomads.ncep.noaa.gov/dods/cmcens/"
+                f"cmcens{time_attempt.year:04d}{time_attempt.month:02d}"
+                f"{time_attempt.day:02d}/"
+                f"cmcens_all_{12 * (time_attempt.hour // 12):02d}z"
+            )
+            try:
+                self.process_ensemble(file, dictionary)
+                success = True
+            except OSError:
+                attempt_count += 1
+        if not success:
+            raise RuntimeError(
+                "Unable to load latest weather data for CMC through " + file
+            )
+
     # Auxiliary functions - Geodesic Coordinates
 
     @staticmethod
diff --git a/rocketpy/environment/environment_analysis.py b/rocketpy/environment/environment_analysis.py
index c15b32551..da6fde364 100644
--- a/rocketpy/environment/environment_analysis.py
+++ b/rocketpy/environment/environment_analysis.py
@@ -3,6 +3,7 @@
 import datetime
 import json
 from collections import defaultdict
+from functools import cached_property
 
 import netCDF4
 import numpy as np
@@ -22,11 +23,6 @@
 from ..units import convert_units
 from .environment import Environment
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 # TODO: the average_wind_speed_profile_by_hour and similar methods could be more abstract than currently are
 
 
@@ -441,7 +437,7 @@ def __localize_input_dates(self):
 
     def __find_preferred_timezone(self):
         if self.preferred_timezone is None:
-            # Use local timezone based on lat lon pair
+            # Use local time zone based on lat lon pair
             try:
                 timezonefinder = import_optional_dependency("timezonefinder")
                 tf = timezonefinder.TimezoneFinder()
diff --git a/rocketpy/mathutils/function.py b/rocketpy/mathutils/function.py
index cefed044d..eda903bcc 100644
--- a/rocketpy/mathutils/function.py
+++ b/rocketpy/mathutils/function.py
@@ -7,6 +7,7 @@
 import warnings
 from collections.abc import Iterable
 from copy import deepcopy
+from functools import cached_property
 from inspect import signature
 from pathlib import Path
 
@@ -14,11 +15,6 @@
 import numpy as np
 from scipy import integrate, linalg, optimize
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 NUMERICAL_TYPES = (float, int, complex, np.ndarray, np.integer, np.floating)
 
 
diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 7a658de04..9c3efe616 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1,7 +1,8 @@
 from cmath import isclose
+from functools import cached_property
 from itertools import product
 
-from rocketpy.tools import cached_property, euler_to_quaternions
+from rocketpy.tools import euler_to_quaternions
 
 
 class Vector:
diff --git a/rocketpy/motors/hybrid_motor.py b/rocketpy/motors/hybrid_motor.py
index 6f0849cd0..557333fe7 100644
--- a/rocketpy/motors/hybrid_motor.py
+++ b/rocketpy/motors/hybrid_motor.py
@@ -1,3 +1,5 @@
+from functools import cached_property
+
 from rocketpy.tools import parallel_axis_theorem_from_com
 
 from ..mathutils.function import Function, funcify_method, reset_funcified_methods
@@ -7,11 +9,6 @@
 from .motor import Motor
 from .solid_motor import SolidMotor
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 
 class HybridMotor(Motor):
     """Class to specify characteristics and useful operations for Hybrid
diff --git a/rocketpy/motors/liquid_motor.py b/rocketpy/motors/liquid_motor.py
index 01f728473..7314e11ba 100644
--- a/rocketpy/motors/liquid_motor.py
+++ b/rocketpy/motors/liquid_motor.py
@@ -1,4 +1,4 @@
-import warnings
+from functools import cached_property
 
 import numpy as np
 
@@ -13,11 +13,6 @@
 from ..prints.liquid_motor_prints import _LiquidMotorPrints
 from .motor import Motor
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 
 class LiquidMotor(Motor):
     """Class to specify characteristics and useful operations for Liquid
diff --git a/rocketpy/motors/motor.py b/rocketpy/motors/motor.py
index 3834f4a15..9429da88e 100644
--- a/rocketpy/motors/motor.py
+++ b/rocketpy/motors/motor.py
@@ -1,6 +1,7 @@
 import re
 import warnings
 from abc import ABC, abstractmethod
+from functools import cached_property
 
 import numpy as np
 
@@ -9,11 +10,6 @@
 from ..prints.motor_prints import _MotorPrints
 from ..tools import parallel_axis_theorem_from_com, tuple_handler
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 
 class Motor(ABC):
     """Abstract class to specify characteristics and useful operations for
diff --git a/rocketpy/motors/solid_motor.py b/rocketpy/motors/solid_motor.py
index 8b1c2362e..db3527a95 100644
--- a/rocketpy/motors/solid_motor.py
+++ b/rocketpy/motors/solid_motor.py
@@ -1,3 +1,5 @@
+from functools import cached_property
+
 import numpy as np
 from scipy import integrate
 
@@ -6,11 +8,6 @@
 from ..prints.solid_motor_prints import _SolidMotorPrints
 from .motor import Motor
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 
 class SolidMotor(Motor):
     """Class to specify characteristics and useful operations for solid motors.
diff --git a/rocketpy/motors/tank_geometry.py b/rocketpy/motors/tank_geometry.py
index f1940cbea..2eb7bd27e 100644
--- a/rocketpy/motors/tank_geometry.py
+++ b/rocketpy/motors/tank_geometry.py
@@ -11,10 +11,7 @@
 
     cache = lru_cache(maxsize=None)
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
+from functools import cached_property
 
 
 class TankGeometry:
diff --git a/rocketpy/plots/flight_plots.py b/rocketpy/plots/flight_plots.py
index 4ae5141c9..21266a1f3 100644
--- a/rocketpy/plots/flight_plots.py
+++ b/rocketpy/plots/flight_plots.py
@@ -1,11 +1,8 @@
+from functools import cached_property
+
 import matplotlib.pyplot as plt
 import numpy as np
 
-try:
-    from functools import cached_property
-except ImportError:
-    from ..tools import cached_property
-
 
 class _FlightPlots:
     """Class that holds plot methods for Flight class.
diff --git a/rocketpy/plots/rocket_plots.py b/rocketpy/plots/rocket_plots.py
index e801da3c7..0d7b5b130 100644
--- a/rocketpy/plots/rocket_plots.py
+++ b/rocketpy/plots/rocket_plots.py
@@ -230,6 +230,8 @@ def draw(self, vis_args=None, plane="xz"):
         plt.show()
 
     def _draw_aerodynamic_surfaces(self, ax, vis_args):
+        """Draws the aerodynamic surfaces and saves the position of the points
+        of interest for the tubes."""
         # List of drawn surfaces with the position of points of interest
         # and the radius of the rocket at that point
         drawn_surfaces = []
@@ -250,6 +252,8 @@ def _draw_aerodynamic_surfaces(self, ax, vis_args):
         return drawn_surfaces
 
     def _draw_nose_cone(self, ax, surface, position, drawn_surfaces, vis_args):
+        """Draws the nosecone and saves the position of the points of interest
+        for the tubes."""
         x_nosecone = -self.rocket._csys * surface.shape_vec[0] + position
         y_nosecone = surface.shape_vec[1]
         ax.plot(
@@ -277,6 +281,8 @@ def _draw_nose_cone(self, ax, surface, position, drawn_surfaces, vis_args):
         )
 
     def _draw_tail(self, ax, surface, position, drawn_surfaces, vis_args):
+        """Draws the tail and saves the position of the points of interest
+        for the tubes."""
         x_tail = -self.rocket._csys * surface.shape_vec[0] + position
         y_tail = surface.shape_vec[1]
         ax.plot(
@@ -302,13 +308,30 @@ def _draw_tail(self, ax, surface, position, drawn_surfaces, vis_args):
         drawn_surfaces.append((surface, position, surface.bottom_radius, x_tail[-1]))
 
     def _draw_fins(self, ax, surface, position, drawn_surfaces, vis_args):
+        """Draws the fins and saves the position of the points of interest
+        for the tubes."""
         num_fins = surface.n
         x_fin = -self.rocket._csys * surface.shape_vec[0] + position
         y_fin = surface.shape_vec[1] + surface.rocket_radius
         rotation_angles = [2 * np.pi * i / num_fins for i in range(num_fins)]
 
         for angle in rotation_angles:
-            x_rotated, y_rotated = self._rotate_points(x_fin, y_fin, angle)
+            # Create a rotation matrix for the current angle around the x-axis
+            rotation_matrix = np.array([[1, 0], [0, np.cos(angle)]])
+
+            # Apply the rotation to the original fin points
+            rotated_points_2d = np.dot(rotation_matrix, np.vstack((x_fin, y_fin)))
+
+            # Extract x and y coordinates of the rotated points
+            x_rotated, y_rotated = rotated_points_2d
+
+            # Project points above the XY plane back into the XY plane (set z-coordinate to 0)
+            x_rotated = np.where(
+                rotated_points_2d[1] > 0, rotated_points_2d[0], x_rotated
+            )
+            y_rotated = np.where(
+                rotated_points_2d[1] > 0, rotated_points_2d[1], y_rotated
+            )
             ax.plot(
                 x_rotated,
                 y_rotated,
@@ -318,22 +341,8 @@ def _draw_fins(self, ax, surface, position, drawn_surfaces, vis_args):
 
         drawn_surfaces.append((surface, position, surface.rocket_radius, x_rotated[-1]))
 
-    def _rotate_points(self, x_fin, y_fin, angle):
-        # Create a rotation matrix for the current angle around the x-axis
-        rotation_matrix = np.array([[1, 0], [0, np.cos(angle)]])
-
-        # Apply the rotation to the original fin points
-        rotated_points_2d = np.dot(rotation_matrix, np.vstack((x_fin, y_fin)))
-
-        # Extract x and y coordinates of the rotated points
-        x_rotated, y_rotated = rotated_points_2d
-
-        # Project points above the XY plane back into the XY plane (set z-coordinate to 0)
-        x_rotated = np.where(rotated_points_2d[1] > 0, rotated_points_2d[0], x_rotated)
-        y_rotated = np.where(rotated_points_2d[1] > 0, rotated_points_2d[1], y_rotated)
-        return x_rotated, y_rotated
-
     def _draw_tubes(self, ax, drawn_surfaces, vis_args):
+        """Draws the tubes between the aerodynamic surfaces."""
         for i, d_surface in enumerate(drawn_surfaces):
             # Draw the tubes, from the end of the first surface to the beginning
             # of the next surface, with the radius of the rocket at that point
@@ -373,6 +382,7 @@ def _draw_tubes(self, ax, drawn_surfaces, vis_args):
         return radius, last_x
 
     def _draw_motor(self, last_radius, last_x, ax, vis_args):
+        """Draws the motor from motor patches"""
         total_csys = self.rocket._csys * self.rocket.motor._csys
         nozzle_position = (
             self.rocket.motor_position + self.rocket.motor.nozzle_position * total_csys
@@ -400,6 +410,7 @@ def _draw_motor(self, last_radius, last_x, ax, vis_args):
         self._draw_nozzle_tube(last_radius, last_x, nozzle_position, ax, vis_args)
 
     def _generate_motor_patches(self, total_csys, ax, vis_args):
+        """Generates motor patches for drawing"""
         motor_patches = []
 
         if isinstance(self.rocket.motor, SolidMotor):
@@ -478,6 +489,7 @@ def _generate_motor_patches(self, total_csys, ax, vis_args):
         return motor_patches
 
     def _draw_nozzle_tube(self, last_radius, last_x, nozzle_position, ax, vis_args):
+        """Draws the tube from the last surface to the nozzle position."""
         # Check if nozzle is beyond the last surface, if so draw a tube
         # to it, with the radius of the last surface
         if self.rocket._csys == 1:
@@ -518,6 +530,7 @@ def _draw_nozzle_tube(self, last_radius, last_x, nozzle_position, ax, vis_args):
                 )
 
     def _draw_rail_buttons(self, ax, vis_args):
+        """Draws the rail buttons of the rocket."""
         try:
             buttons, pos = self.rocket.rail_buttons[0]
             lower = pos
@@ -532,6 +545,7 @@ def _draw_rail_buttons(self, ax, vis_args):
             pass
 
     def _draw_center_of_mass_and_pressure(self, ax):
+        """Draws the center of mass and center of pressure of the rocket."""
         # Draw center of mass and center of pressure
         cm = self.rocket.center_of_mass(0)
         ax.scatter(cm, 0, color="#1565c0", label="Center of Mass", s=10)
diff --git a/rocketpy/rocket/aero_surface.py b/rocketpy/rocket/aero_surface.py
index c5d154f3e..9649d1bf0 100644
--- a/rocketpy/rocket/aero_surface.py
+++ b/rocketpy/rocket/aero_surface.py
@@ -1,6 +1,5 @@
 import warnings
 from abc import ABC, abstractmethod
-from functools import cached_property
 
 import numpy as np
 from scipy.optimize import fsolve
@@ -1978,8 +1977,9 @@ def __init__(
             brakes drag coefficient will be used for the entire rocket instead.
             Default is False.
         deployment_level : float, optional
-            Current deployment level, ranging from 0 to 1. Deployment level is the
-            fraction of the total airbrake area that is Deployment. Default is 0.
+            Initial deployment level, ranging from 0 to 1. Deployment level is
+            the fraction of the total airbrake area that is Deployment. Default
+            is 0.
         name : str, optional
             Name of the air brakes. Default is "AirBrakes".
 
@@ -1997,6 +1997,7 @@ def __init__(
         self.reference_area = reference_area
         self.clamp = clamp
         self.override_rocket_drag = override_rocket_drag
+        self.initial_deployment_level = deployment_level
         self.deployment_level = deployment_level
         self.prints = _AirBrakesPrints(self)
         self.plots = _AirBrakesPlots(self)
@@ -2023,6 +2024,12 @@ def deployment_level(self, value):
                 )
         self._deployment_level = value
 
+    def _reset(self):
+        """Resets the air brakes to their initial state. This is ran at the
+        beginning of each simulation to ensure the air brakes are in the correct
+        state."""
+        self.deployment_level = self.initial_deployment_level
+
     def evaluate_center_of_pressure(self):
         """Evaluates the center of pressure of the aerodynamic surface in local
         coordinates.
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index 9c179557e..45fce0cd5 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -82,6 +82,9 @@ class Rocket:
         Function of time expressing the total mass of the rocket,
         defined as the sum of the propellant mass and the rocket
         mass without propellant.
+    Rocket.total_mass_flow_rate : Function
+        Time derivative of rocket's total mass in kg/s as a function
+        of time as obtained by the thrust source of the added motor.
     Rocket.thrust_to_weight : Function
         Function of time expressing the motor thrust force divided by rocket
         weight. The gravitational acceleration is assumed as 9.80665 m/s^2.
@@ -760,6 +763,7 @@ def add_motor(self, motor, position):
             self.motor.center_of_dry_mass_position * _ + self.motor_position
         )
         self.nozzle_position = self.motor.nozzle_position * _ + self.motor_position
+        self.total_mass_flow_rate = self.motor.total_mass_flow_rate
         self.evaluate_dry_mass()
         self.evaluate_total_mass()
         self.evaluate_center_of_dry_mass()
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index f82b63b1c..8aa3f4cd6 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -611,6 +611,9 @@ def __init__(
         self.name = name
         self.equations_of_motion = equations_of_motion
 
+        # Controller initialization
+        self.__init_controllers()
+
         # Flight initialization
         self.__init_post_process_variables()
         self.__init_solution_monitors()
@@ -1107,8 +1110,14 @@ def __init__(
                                             [self.t, parachute]
                                         )
 
+                    # If controlled flight, post process must be done on sim time
+                    if self._controllers:
+                        phase.derivative(self.t, self.y_sol, post_processing=True)
+
         self.t_final = self.t
         self._calculate_pressure_signal()
+        if self._controllers:
+            self.__cache_post_process_variables()
         if verbose:
             print("Simulation Completed at Time: {:3.4f} s".format(self.t))
 
@@ -1120,6 +1129,25 @@ def __init_post_process_variables(self):
         self._bearing = Function(0)
         self._latitude = Function(0)
         self._longitude = Function(0)
+        # Initialize state derivatives, force and atmospheric arrays
+        self.ax_list = []
+        self.ay_list = []
+        self.az_list = []
+        self.alpha1_list = []
+        self.alpha2_list = []
+        self.alpha3_list = []
+        self.R1_list = []
+        self.R2_list = []
+        self.R3_list = []
+        self.M1_list = []
+        self.M2_list = []
+        self.M3_list = []
+        self.pressure_list = []
+        self.density_list = []
+        self.dynamic_viscosity_list = []
+        self.speed_of_sound_list = []
+        self.wind_velocity_x_list = []
+        self.wind_velocity_y_list = []
 
     def __init_solution_monitors(self):
         # Initialize solution monitors
@@ -1192,6 +1220,11 @@ def __init_flight_state(self):
             self.out_of_rail_time = self.initial_solution[0]
             self.out_of_rail_time_index = 0
             self.initial_derivative = self.u_dot_generalized
+        if self._controllers:
+            # Handle post process during simulation, get initial accel/forces
+            self.initial_derivative(
+                self.t_initial, self.initial_solution[1:], post_processing=True
+            )
 
     def __init_solver_monitors(self):
         # Initialize solver monitors
@@ -1212,10 +1245,41 @@ def __init_equations_of_motion(self):
         if self.equations_of_motion == "solid_propulsion":
             self.u_dot_generalized = self.u_dot
 
-    def __init_equations_of_motion(self):
-        """Initialize equations of motion."""
-        if self.equations_of_motion == "solid_propulsion":
-            self.u_dot_generalized = self.u_dot
+    def __init_controllers(self):
+        """Initialize controllers"""
+        self._controllers = self.rocket._controllers[:]
+        if self._controllers:
+            if self.time_overshoot == True:
+                self.time_overshoot = False
+                warnings.warn(
+                    "time_overshoot has been set to False due to the presence of controllers. "
+                )
+            # reset controllable object to initial state (only airbrakes for now)
+            for air_brakes in self.rocket.air_brakes:
+                air_brakes._reset()
+
+    def __cache_post_process_variables(self):
+        """Cache post-process variables for simulations with controllers."""
+        self.__retrieve_arrays = [
+            self.ax_list,
+            self.ay_list,
+            self.az_list,
+            self.alpha1_list,
+            self.alpha2_list,
+            self.alpha3_list,
+            self.R1_list,
+            self.R2_list,
+            self.R3_list,
+            self.M1_list,
+            self.M2_list,
+            self.M3_list,
+            self.pressure_list,
+            self.density_list,
+            self.dynamic_viscosity_list,
+            self.speed_of_sound_list,
+            self.wind_velocity_x_list,
+            self.wind_velocity_y_list,
+        ]
 
     @cached_property
     def effective_1rl(self):
@@ -1292,11 +1356,6 @@ def udot_rail1(self, t, u, post_processing=False):
             e0dot, e1dot, e2dot, e3dot, alpha1, alpha2, alpha3].
 
         """
-        # Check if post processing mode is on
-        if post_processing:
-            # Use u_dot post processing code
-            return self.u_dot_generalized(t, u, True)
-
         # Retrieve integration data
         x, y, z, vx, vy, vz, e0, e1, e2, e3, omega1, omega2, omega3 = u
 
@@ -1327,6 +1386,17 @@ def udot_rail1(self, t, u, post_processing=False):
         else:
             ax, ay, az = 0, 0, 0
 
+        if post_processing:
+            # Use u_dot post processing code for forces, moments and env data
+            self.u_dot_generalized(t, u, post_processing=True)
+            # Save feasible accelerations
+            self.ax_list[-1] = [t, ax]
+            self.ay_list[-1] = [t, ay]
+            self.az_list[-1] = [t, az]
+            self.alpha1_list[-1] = [t, 0]
+            self.alpha2_list[-1] = [t, 0]
+            self.alpha3_list[-1] = [t, 0]
+
         return [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
 
     def udot_rail2(self, t, u, post_processing=False):
@@ -1616,6 +1686,13 @@ def u_dot(self, t, u, post_processing=False):
         ]
 
         if post_processing:
+            # Accelerations
+            self.ax_list.append([t, ax])
+            self.ay_list.append([t, ay])
+            self.az_list.append([t, az])
+            self.alpha1_list.append([t, alpha1])
+            self.alpha2_list.append([t, alpha2])
+            self.alpha3_list.append([t, alpha3])
             # Dynamics variables
             self.R1_list.append([t, R1])
             self.R2_list.append([t, R2])
@@ -1676,8 +1753,8 @@ def u_dot_generalized(self, t, u, post_processing=False):
         # Retrieve necessary quantities
         rho = self.env.density.get_value_opt(z)
         total_mass = self.rocket.total_mass.get_value_opt(t)
-        total_mass_dot = self.rocket.total_mass.differentiate(t)
-        total_mass_ddot = self.rocket.total_mass.differentiate(t, order=2)
+        total_mass_dot = self.rocket.total_mass_flow_rate.get_value_opt(t)
+        total_mass_ddot = self.rocket.total_mass_flow_rate.differentiate(t)
         ## CM position vector and time derivatives relative to CDM in body frame
         r_CM_z = (
             -1
@@ -1891,6 +1968,13 @@ def u_dot_generalized(self, t, u, post_processing=False):
         u_dot = [*r_dot, *v_dot, *e_dot, *w_dot]
 
         if post_processing:
+            # Accelerations
+            self.ax_list.append([t, v_dot[0]])
+            self.ay_list.append([t, v_dot[1]])
+            self.az_list.append([t, v_dot[2]])
+            self.alpha1_list.append([t, w_dot[0]])
+            self.alpha2_list.append([t, w_dot[1]])
+            self.alpha3_list.append([t, w_dot[2]])
             # Dynamics variables
             self.R1_list.append([t, R1])
             self.R2_list.append([t, R2])
@@ -1977,6 +2061,13 @@ def u_dot_parachute(self, t, u, post_processing=False):
         u_dot = [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
 
         if post_processing:
+            # Accelerations
+            self.ax_list.append([t, ax])
+            self.ay_list.append([t, ay])
+            self.az_list.append([t, az])
+            self.alpha1_list.append([t, 0])
+            self.alpha2_list.append([t, 0])
+            self.alpha3_list.append([t, 0])
             # Dynamics variables
             self.R1_list.append([t, Dx])
             self.R2_list.append([t, Dy])
@@ -1985,13 +2076,20 @@ def u_dot_parachute(self, t, u, post_processing=False):
             self.M2_list.append([t, 0])
             self.M3_list.append([t, 0])
             # Atmospheric Conditions
-            self.wind_velocity_x_list.append([t, self.env.wind_velocity_x(z)])
-            self.wind_velocity_y_list.append([t, self.env.wind_velocity_y(z)])
-            self.density_list.append([t, self.env.density(z)])
-            self.dynamic_viscosity_list.append([t, self.env.dynamic_viscosity(z)])
-            self.pressure_list.append([t, self.env.pressure(z)])
-            self.speed_of_sound_list.append([t, self.env.speed_of_sound(z)])
-
+            self.wind_velocity_x_list.append(
+                [t, self.env.wind_velocity_x.get_value_opt(z)]
+            )
+            self.wind_velocity_y_list.append(
+                [t, self.env.wind_velocity_y.get_value_opt(z)]
+            )
+            self.density_list.append([t, self.env.density.get_value_opt(z)])
+            self.dynamic_viscosity_list.append(
+                [t, self.env.dynamic_viscosity.get_value_opt(z)]
+            )
+            self.pressure_list.append([t, self.env.pressure.get_value_opt(z)])
+            self.speed_of_sound_list.append(
+                [t, self.env.speed_of_sound.get_value_opt(z)]
+            )
         return [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
 
     @cached_property
@@ -2824,31 +2922,20 @@ def longitude(self):
         return np.column_stack((self.time, longitude))
 
     @cached_property
-    def retrieve_acceleration_arrays(self):
-        """Retrieve acceleration arrays from the integration scheme
-
-        Parameters
-        ----------
+    def __retrieve_arrays(self):
+        """post processing function to retrieve arrays from the integration
+        scheme and store them in lists for further analysis.
 
         Returns
         -------
-        ax: list
-            acceleration in x direction
-        ay: list
-            acceleration in y direction
-        az: list
-            acceleration in z direction
-        alpha1: list
-            angular acceleration in x direction
-        alpha2: list
-            angular acceleration in y direction
-        alpha3: list
-            angular acceleration in z direction
+        temp_values: list
+            List containing the following arrays: ``ax`` , ``ay`` , ``az`` ,
+            ``alpha1`` , ``alpha2`` , ``alpha3`` , ``R1`` , ``R2`` , ``R3`` ,
+            ``M1`` , ``M2`` , ``M3`` , ``pressure`` , ``density`` ,
+            ``dynamic_viscosity`` , ``speed_of_sound`` , ``wind_velocity_x`` ,
+            ``wind_velocity_y``.
         """
-        # Initialize acceleration arrays
-        ax, ay, az = [[0, 0]], [[0, 0]], [[0, 0]]
-        alpha1, alpha2, alpha3 = [[0, 0]], [[0, 0]], [[0, 0]]
-        # Go through each time step and calculate accelerations
+        # Go through each time step and calculate forces and atmospheric values
         # Get flight phases
         for phase_index, phase in self.time_iterator(self.FlightPhases):
             init_time = phase.t
@@ -2857,23 +2944,60 @@ def retrieve_acceleration_arrays(self):
             # Call callback functions
             for callback in phase.callbacks:
                 callback(self)
-            # Loop through time steps in flight phase
-            for step in self.solution:  # Can be optimized
-                if init_time < step[0] <= final_time:
-                    # Get derivatives
-                    u_dot = current_derivative(step[0], step[1:])
-                    # Get accelerations
-                    ax_value, ay_value, az_value = u_dot[3:6]
-                    alpha1_value, alpha2_value, alpha3_value = u_dot[10:]
-                    # Save accelerations
-                    ax.append([step[0], ax_value])
-                    ay.append([step[0], ay_value])
-                    az.append([step[0], az_value])
-                    alpha1.append([step[0], alpha1_value])
-                    alpha2.append([step[0], alpha2_value])
-                    alpha3.append([step[0], alpha3_value])
-
-        return ax, ay, az, alpha1, alpha2, alpha3
+            # find index of initial and final time of phase in solution array
+            init_time_index = find_closest(self.time, init_time)
+            final_time_index = find_closest(self.time, final_time) + 1
+            # Loop through time steps solution array
+            for step in self.solution[init_time_index:final_time_index]:
+                if init_time != step[0] or (
+                    init_time == self.t_initial and step[0] == self.t_initial
+                ):
+                    # Call derivatives in post processing mode
+                    current_derivative(step[0], step[1:], post_processing=True)
+
+        temp_values = [
+            self.ax_list,
+            self.ay_list,
+            self.az_list,
+            self.alpha1_list,
+            self.alpha2_list,
+            self.alpha3_list,
+            self.R1_list,
+            self.R2_list,
+            self.R3_list,
+            self.M1_list,
+            self.M2_list,
+            self.M3_list,
+            self.pressure_list,
+            self.density_list,
+            self.dynamic_viscosity_list,
+            self.speed_of_sound_list,
+            self.wind_velocity_x_list,
+            self.wind_velocity_y_list,
+        ]
+
+        return temp_values
+
+    @cached_property
+    def retrieve_acceleration_arrays(self):
+        """Retrieve acceleration arrays from the integration scheme
+
+        Returns
+        -------
+        ax_list: list
+            acceleration in x direction
+        ay_list: list
+            acceleration in y direction
+        az_list: list
+            acceleration in z direction
+        alpha1_list: list
+            angular acceleration in x direction
+        alpha2_list: list
+            angular acceleration in y direction
+        alpha3_list: list
+            angular acceleration in z direction
+        """
+        return self.__retrieve_arrays[:6]
 
     @cached_property
     def retrieve_temporary_values_arrays(self):
@@ -2910,54 +3034,7 @@ def retrieve_temporary_values_arrays(self):
         self.wind_velocity_y_list: list
             Wind velocity in y direction at each time step.
         """
-
-        # Initialize force and atmospheric arrays
-        self.R1_list = []
-        self.R2_list = []
-        self.R3_list = []
-        self.M1_list = []
-        self.M2_list = []
-        self.M3_list = []
-        self.pressure_list = []
-        self.density_list = []
-        self.dynamic_viscosity_list = []
-        self.speed_of_sound_list = []
-        self.wind_velocity_x_list = []
-        self.wind_velocity_y_list = []
-
-        # Go through each time step and calculate forces and atmospheric values
-        # Get flight phases
-        for phase_index, phase in self.time_iterator(self.FlightPhases):
-            init_time = phase.t
-            final_time = self.FlightPhases[phase_index + 1].t
-            current_derivative = phase.derivative
-            # Call callback functions
-            for callback in phase.callbacks:
-                callback(self)
-            # Loop through time steps in flight phase
-            for step in self.solution:  # Can be optimized
-                if init_time < step[0] <= final_time or (
-                    init_time == self.t_initial and step[0] == self.t_initial
-                ):
-                    # Call derivatives in post processing mode
-                    u_dot = current_derivative(step[0], step[1:], post_processing=True)
-
-        temporary_values = [
-            self.R1_list,
-            self.R2_list,
-            self.R3_list,
-            self.M1_list,
-            self.M2_list,
-            self.M3_list,
-            self.pressure_list,
-            self.density_list,
-            self.dynamic_viscosity_list,
-            self.speed_of_sound_list,
-            self.wind_velocity_x_list,
-            self.wind_velocity_y_list,
-        ]
-
-        return temporary_values
+        return self.__retrieve_arrays[6:]
 
     def get_controller_observed_variables(self):
         """Retrieve the observed variables related to air brakes from the
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 5666fdbdf..edea8aada 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -1,6 +1,8 @@
+import functools
 import importlib
 import importlib.metadata
 import re
+import time
 from bisect import bisect_left
 
 import numpy as np
@@ -8,36 +10,10 @@
 from cftime import num2pydate
 from packaging import version as packaging_version
 
-_NOT_FOUND = object()
-
 # Mapping of module name and the name of the package that should be installed
 INSTALL_MAPPING = {"IPython": "ipython"}
 
 
-class cached_property:
-    def __init__(self, func):
-        self.func = func
-        self.attrname = None
-        self.__doc__ = func.__doc__
-
-    def __set_name__(self, owner, name):
-        self.attrname = name
-
-    def __get__(self, instance, owner=None):
-        if instance is None:
-            return self
-        if self.attrname is None:
-            raise TypeError(
-                "Cannot use cached_property instance without calling __set_name__ on it."
-            )
-        cache = instance.__dict__
-        val = cache.get(self.attrname, _NOT_FOUND)
-        if val is _NOT_FOUND:
-            val = self.func(instance)
-            cache[self.attrname] = val
-        return val
-
-
 def tuple_handler(value):
     """Transforms the input value into a tuple that
     represents a range. If the input is an int or float,
@@ -153,7 +129,7 @@ def time_num_to_date_string(time_num, units, timezone, calendar="gregorian"):
     """Convert time number (usually hours before a certain date) into two
     strings: one for the date (example: 2022.04.31) and one for the hour
     (example: 14). See cftime.num2date for details on units and calendar.
-    Automatically converts time number from UTC to local timezone based on
+    Automatically converts time number from UTC to local time zone based on
     lat, lon coordinates. This function was created originally for the
     EnvironmentAnalysis class.
 
@@ -382,6 +358,25 @@ def check_requirement_version(module_name, version):
     return True
 
 
+def exponential_backoff(max_attempts, base_delay=1, max_delay=60):
+    def decorator(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            delay = base_delay
+            for i in range(max_attempts):
+                try:
+                    return func(*args, **kwargs)
+                except Exception as e:
+                    if i == max_attempts - 1:
+                        raise e from None
+                    delay = min(delay * 2, max_delay)
+                    time.sleep(delay)
+
+        return wrapper
+
+    return decorator
+
+
 def parallel_axis_theorem_from_com(com_inertia_moment, mass, distance):
     """Calculates the moment of inertia of a object relative to a new axis using
     the parallel axis theorem. The new axis is parallel to and at a distance
diff --git a/tests/fixtures/environment/environment_fixtures.py b/tests/fixtures/environment/environment_fixtures.py
index 8949f9973..851be3203 100644
--- a/tests/fixtures/environment/environment_fixtures.py
+++ b/tests/fixtures/environment/environment_fixtures.py
@@ -1,6 +1,7 @@
 from datetime import datetime, timedelta
 
 import pytest
+
 from rocketpy import Environment, EnvironmentAnalysis
 
 
@@ -54,8 +55,8 @@ def env_analysis():
     EnvironmentAnalysis
     """
     env_analysis = EnvironmentAnalysis(
-        start_date=datetime.datetime(2019, 10, 23),
-        end_date=datetime.datetime(2021, 10, 23),
+        start_date=datetime(2019, 10, 23),
+        end_date=datetime(2021, 10, 23),
         latitude=39.3897,
         longitude=-8.28896388889,
         start_hour=6,
diff --git a/tests/test_environment.py b/tests/test_environment.py
index 5fa0e2c45..7349d512b 100644
--- a/tests/test_environment.py
+++ b/tests/test_environment.py
@@ -1,5 +1,4 @@
 import datetime
-import time
 from unittest.mock import patch
 
 import pytest
@@ -64,13 +63,8 @@ def test_wyoming_sounding_atmosphere(mock_show, example_plain_env):
     #        "file" option, instead of receiving the URL as a string.
     URL = "http://weather.uwyo.edu/cgi-bin/sounding?region=samer&TYPE=TEXT%3ALIST&YEAR=2019&MONTH=02&FROM=0500&TO=0512&STNM=83779"
     # give it at least 5 times to try to download the file
-    for i in range(5):
-        try:
-            example_plain_env.set_atmospheric_model(type="wyoming_sounding", file=URL)
-            break
-        except:
-            time.sleep(1)  # wait 1 second before trying again
-            pass
+    example_plain_env.set_atmospheric_model(type="wyoming_sounding", file=URL)
+
     assert example_plain_env.all_info() == None
     assert abs(example_plain_env.pressure(0) - 93600.0) < 1e-8
     assert (
diff --git a/tests/test_flight.py b/tests/test_flight.py
index db882e185..4fb4036eb 100644
--- a/tests/test_flight.py
+++ b/tests/test_flight.py
@@ -604,12 +604,12 @@ def test_max_values(flight_calisto_robust):
     calculated by hand, it was just copied from the test results. This is
     because the expected values are not easy to calculate by hand, and the
     results are not expected to change. If the results change, the test will
-    fail, and the expected values must be updated. If if want to update the
-    values, always double check if the results are really correct. Acceptable
-    reasons for changes in the results are: 1) changes in the code that
-    improve the accuracy of the simulation, 2) a bug was found and fixed. Keep
-    in mind that other tests may be more accurate than this one, for example,
-    the acceptance tests, which are based on the results of real flights.
+    fail, and the expected values must be updated. If the values are updated,
+    always double check if the results are really correct. Acceptable reasons
+    for changes in the results are: 1) changes in the code that improve the
+    accuracy of the simulation, 2) a bug was found and fixed. Keep in mind that
+    other tests may be more accurate than this one, for example, the acceptance
+    tests, which are based on the results of real flights.
 
     Parameters
     ----------
@@ -622,7 +622,7 @@ def test_max_values(flight_calisto_robust):
     assert pytest.approx(105.2774, abs=atol) == test.max_acceleration_power_on
     assert pytest.approx(105.2774, abs=atol) == test.max_acceleration
     assert pytest.approx(0.85999, abs=atol) == test.max_mach_number
-    assert pytest.approx(285.90240, abs=atol) == test.max_speed
+    assert pytest.approx(285.94948, abs=atol) == test.max_speed
 
 
 def test_rail_buttons_forces(flight_calisto_custom_wind):
diff --git a/tests/unit/test_environment.py b/tests/unit/test_environment.py
index ac25533eb..8d676f426 100644
--- a/tests/unit/test_environment.py
+++ b/tests/unit/test_environment.py
@@ -1,10 +1,10 @@
+import json
 import os
 
 import numpy as np
 import numpy.ma as ma
 import pytest
 import pytz
-import json
 
 from rocketpy import Environment
 

From 9a6b052a3bab349e0359157cdb870f43215611a0 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 14:32:11 +0200
Subject: [PATCH 023/120] MNT: fix component repr for sensors

---
 rocketpy/rocket/components.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/rocketpy/rocket/components.py b/rocketpy/rocket/components.py
index 4a033507c..f97d54cab 100644
--- a/rocketpy/rocket/components.py
+++ b/rocketpy/rocket/components.py
@@ -32,7 +32,7 @@ def __repr__(self):
         """Return a string representation of the Components instance."""
         components_str = "\n".join(
             [
-                f"\tComponent: {str(c.component):80} Position: {c.position:>6.3f}"
+                f"\tComponent: {str(c.component):80} Position: {c.position}"
                 for c in self._components
             ]
         )

From 7953cb08eea37565528f8c8f7a625457074e0861 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:40:44 +0200
Subject: [PATCH 024/120] ENH: add _attatched_rockets to sensors

---
 rocketpy/rocket/rocket.py   | 4 ++++
 rocketpy/sensors/sensors.py | 3 +++
 2 files changed, 7 insertions(+)

diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index 45fce0cd5..073c9c60a 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -1192,6 +1192,10 @@ def add_sensor(self, sensor, position, x_position=0, y_position=0):
         None
         """
         self.sensors.add(sensor, Vector([x_position, y_position, position]))
+        try:
+            sensor._attached_rockets[self] += 1
+        except:
+            sensor._attached_rockets[self] = 1
 
     def add_air_brakes(
         self,
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index fadb9ae73..1cc624f52 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -197,6 +197,9 @@ def __init__(
         # compute total rotation matrix given cross axis sensitivity
         self._total_rotation_matrix = self.rotation_matrix @ _cross_axis_matrix
 
+        # map which rocket(s) the sensor is attached to and how many times
+        self._attached_rockets = {}
+
     def _vectorize_input(self, value, name):
         if isinstance(value, (int, float)):
             return Vector([value, value, value])

From 5a375532abfb063477d968df26a273136d91a74a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:42:34 +0200
Subject: [PATCH 025/120] ENH: add sensors saving methods

---
 rocketpy/sensors/sensors.py | 29 ++++++++++++++++++++++++++++-
 1 file changed, 28 insertions(+), 1 deletion(-)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 1cc624f52..d7ebed8d2 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -158,7 +158,8 @@ def __init__(
         self.name = name
         self._random_walk_drift = Vector([0, 0, 0])
         self.measurement = None
-        self.measured_data = []  # change to data
+        self.measured_data = []
+        self._counter = 0
 
         # handle measurement range
         if isinstance(measurement_range, (tuple, list)):
@@ -208,6 +209,32 @@ def _vectorize_input(self, value, name):
         else:
             raise ValueError(f"Invalid {name} format")
 
+    def _reset(self, simulated_rocket):
+        """Reset the sensor data for a new simulation."""
+        self._random_walk_drift = Vector([0, 0, 0])
+        self.measured_data = []
+        if self._attached_rockets[simulated_rocket] > 1:
+            self.measured_data = [
+                [] for _ in range(self._attached_rockets[simulated_rocket])
+            ]
+            self._save_data = self._save_data_multiple
+        else:
+            self._save_data = self._save_data_single
+
+    def _save_data_single(self, data, index=0):
+        """Save the measured data to the sensor data list for a sensor that is
+        added only once to the simulated rocket."""
+        self.measured_data.append(data)
+
+    def _save_data_multiple(self, data):
+        """Save the measured data to the sensor data list for a sensor that is
+        added multiple times to the simulated rocket."""
+        self.measured_data[self._counter].append(data)
+        # counter for cases where the sensor is added multiple times in a rocket
+        self._counter += 1
+        if self._counter == len(self.measured_data):
+            self._counter = 0
+
     def __repr__(self):
         return f"{self.type} sensor, orientation: {self.orientation}"
 

From 09ea25202fc0fac43ca2cecba0760f94e1d10e0e Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:42:52 +0200
Subject: [PATCH 026/120] MNT: simplify sensors repr

---
 rocketpy/sensors/sensors.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index d7ebed8d2..8ecf20c2c 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -236,7 +236,7 @@ def _save_data_multiple(self, data):
             self._counter = 0
 
     def __repr__(self):
-        return f"{self.type} sensor, orientation: {self.orientation}"
+        return f"{self.name}"
 
     def __call__(self, *args, **kwargs):
         return self.measure(*args, **kwargs)

From 9851392d69b833c08fa19988cc9711a350af0cc3 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:44:23 +0200
Subject: [PATCH 027/120] ENH: use _save_data in accel and gyro

---
 rocketpy/sensors/accelerometer.py | 2 +-
 rocketpy/sensors/gyroscope.py     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 38e423439..96cadffce 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -215,7 +215,7 @@ def measure(self, t, u, u_dot, relative_position, gravity, *args):
         A = self.quantize(A)
 
         self.measurement = tuple([*A])
-        self.measured_data.append((t, *A))
+        self._save_data((t, *A))
 
     def export_measured_data(self, filename, format="csv"):
         """
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 21053edbe..d7c34088d 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -207,7 +207,7 @@ def measure(self, t, u, u_dot, relative_position, *args):
         W = self.quantize(W)
 
         self.measurement = tuple([*W])
-        self.measured_data.append((t, *W))
+        self._save_data((t, *W))
 
     def apply_acceleration_sensitivity(
         self, omega, u_dot, relative_position, rotation_matrix

From 0f81bc31951267800e34d5603a9c95e11923f462 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:44:49 +0200
Subject: [PATCH 028/120] ENH: improve accelerometer export

---
 rocketpy/sensors/accelerometer.py | 52 ++++++++++++++++++++++---------
 1 file changed, 38 insertions(+), 14 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 96cadffce..0028b9aa1 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -1,4 +1,5 @@
 import numpy as np
+import json
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _AccelerometerPrints
@@ -234,20 +235,43 @@ def export_measured_data(self, filename, format="csv"):
         None
         """
         if format == "csv":
-            with open(filename, "w") as f:
-                f.write("t,ax,ay,az\n")
-                for t, ax, ay, az in self.measured_data:
-                    f.write(f"{t},{ax},{ay},{az}\n")
+            # if sensor has been added multiple times to the simulated rocket
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    with open(filename + f"_{i+1}", "w") as f:
+                        f.write("t,ax,ay,az\n")
+                        for t, ax, ay, az in data:
+                            f.write(f"{t},{ax},{ay},{az}\n")
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                with open(filename, "w") as f:
+                    f.write("t,ax,ay,az\n")
+                    for t, ax, ay, az in self.measured_data:
+                        f.write(f"{t},{ax},{ay},{az}\n")
+                print(f"Data saved to {filename}")
         elif format == "json":
-            import json
-
-            data = {"t": [], "ax": [], "ay": [], "az": []}
-            for t, ax, ay, az in self.measured_data:
-                data["t"].append(t)
-                data["ax"].append(ax)
-                data["ay"].append(ay)
-                data["az"].append(az)
-            with open(filename, "w") as f:
-                json.dump(data, f)
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    dict = {"t": [], "ax": [], "ay": [], "az": []}
+                    for t, ax, ay, az in data:
+                        dict["t"].append(t)
+                        dict["ax"].append(ax)
+                        dict["ay"].append(ay)
+                        dict["az"].append(az)
+                    with open(filename + f"_{i+1}", "w") as f:
+                        json.dump(dict, f)
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                dict = {"t": [], "ax": [], "ay": [], "az": []}
+                for t, ax, ay, az in self.measured_data:
+                    dict["t"].append(t)
+                    dict["ax"].append(ax)
+                    dict["ay"].append(ay)
+                    dict["az"].append(az)
+                with open(filename, "w") as f:
+                    json.dump(dict, f)
+                print(f"Data saved to {filename}")
         else:
             raise ValueError("Invalid format")

From a740fc2b4820efc7c02d8456a3849f468807dcbb Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:45:03 +0200
Subject: [PATCH 029/120] ENH: imrpove gyroscope export

---
 rocketpy/sensors/gyroscope.py | 52 +++++++++++++++++++++++++----------
 1 file changed, 38 insertions(+), 14 deletions(-)

diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index d7c34088d..5275ed600 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -1,4 +1,5 @@
 import numpy as np
+import json
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
@@ -265,20 +266,43 @@ def export_measured_data(self, filename, format="csv"):
         None
         """
         if format == "csv":
-            with open(filename, "w") as f:
-                f.write("t,wx,wy,wz\n")
-                for t, wx, wy, wz in self.measured_data:
-                    f.write(f"{t},{wx},{wy},{wz}\n")
+            # if sensor has been added multiple times to the simulated rocket
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    with open(filename + f"_{i+1}", "w") as f:
+                        f.write("t,wx,wy,wz\n")
+                        for t, wx, wy, wz in data:
+                            f.write(f"{t},{wx},{wy},{wz}\n")
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                with open(filename, "w") as f:
+                    f.write("t,wx,wy,wz\n")
+                    for t, wx, wy, wz in self.measured_data:
+                        f.write(f"{t},{wx},{wy},{wz}\n")
+                print(f"Data saved to {filename}")
         elif format == "json":
-            import json
-
-            data = {"t": [], "wx": [], "wy": [], "wz": []}
-            for t, wx, wy, wz in self.measured_data:
-                data["t"].append(t)
-                data["wx"].append(wx)
-                data["wy"].append(wy)
-                data["wz"].append(wz)
-            with open(filename, "w") as f:
-                json.dump(data, f)
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    dict = {"t": [], "wx": [], "wy": [], "wz": []}
+                    for t, wx, wy, wz in data:
+                        dict["t"].append(t)
+                        dict["wx"].append(wx)
+                        dict["wy"].append(wy)
+                        dict["wz"].append(wz)
+                    with open(filename + f"_{i+1}", "w") as f:
+                        json.dump(dict, f)
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                dict = {"t": [], "wx": [], "wy": [], "wz": []}
+                for t, wx, wy, wz in self.measured_data:
+                    dict["t"].append(t)
+                    dict["wx"].append(wx)
+                    dict["wy"].append(wy)
+                    dict["wz"].append(wz)
+                with open(filename, "w") as f:
+                    json.dump(dict, f)
+                print(f"Data saved to {filename}")
         else:
             raise ValueError("Invalid format")

From cf6c26d772de0137c2c1ba0b9f45a259f94564d8 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:48:03 +0200
Subject: [PATCH 030/120] ENH: add sensor initialization

---
 rocketpy/simulation/flight.py | 20 ++++++++++++--------
 1 file changed, 12 insertions(+), 8 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 8aa3f4cd6..928bf63d4 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -595,9 +595,6 @@ def __init__(
         if self.rail_length <= 0:
             raise ValueError("Rail length must be a positive value.")
         self.parachutes = self.rocket.parachutes[:]
-        self._controllers = self.rocket._controllers[:]
-        self._component_sensors = self.rocket.sensors
-        self._sensors_list = self.rocket.sensors.get_components()
         self.inclination = inclination
         self.heading = heading
         self.max_time = max_time
@@ -676,7 +673,7 @@ def __init__(
                     self.parachutes, phase.t, phase.time_bound
                 )
                 phase.TimeNodes.add_sensors(
-                    self._component_sensors, phase.t, phase.time_bound
+                    self.rocket.sensors, phase.t, phase.time_bound
                 )
                 phase.TimeNodes.add_controllers(
                     self._controllers, phase.t, phase.time_bound
@@ -1060,7 +1057,7 @@ def __init__(
                                         pressure + noise,
                                         hAGL,
                                         overshootable_node.y,
-                                        self._sensors_list,
+                                        self.sensors,
                                     ):
                                         # print('\nEVENT DETECTED')
                                         # print('Parachute Triggered')
@@ -1246,18 +1243,25 @@ def __init_equations_of_motion(self):
             self.u_dot_generalized = self.u_dot
 
     def __init_controllers(self):
-        """Initialize controllers"""
+        """Initialize controllers and sensors"""
         self._controllers = self.rocket._controllers[:]
-        if self._controllers:
+        if self._controllers or self.sensors:
             if self.time_overshoot == True:
                 self.time_overshoot = False
                 warnings.warn(
-                    "time_overshoot has been set to False due to the presence of controllers. "
+                    "time_overshoot has been set to False due to the presence "
+                    "of controllers or sensors. "
                 )
             # reset controllable object to initial state (only airbrakes for now)
             for air_brakes in self.rocket.air_brakes:
                 air_brakes._reset()
 
+        self.sensors = self.rocket.sensors.get_components()
+        self.sensor_data = {}
+        for sensor in self.sensors:
+            sensor._reset(self.rocket)  # resets noise and measurement list
+            self.sensor_data[sensor] = []
+
     def __cache_post_process_variables(self):
         """Cache post-process variables for simulations with controllers."""
         self.__retrieve_arrays = [

From 2a14f1de247659b3a51a3cf4fd3e142c64873692 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:48:55 +0200
Subject: [PATCH 031/120] ENH: speed up measure call

---
 rocketpy/simulation/flight.py | 33 ++++++++++++++++-----------------
 1 file changed, 16 insertions(+), 17 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 928bf63d4..46de2dbc7 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -57,8 +57,6 @@ class Flight:
         Name of the flight.
     Flight._controllers : list
         List of controllers to be used during simulation.
-    Flight._component_sensors : list
-        List of sensors to be used during simulation.
     Flight.max_time : int, float
         Maximum simulation time allowed. Refers to physical time
         being simulated, not time taken to run simulation.
@@ -709,26 +707,27 @@ def __init__(
                 for callback in node.callbacks:
                     callback(self)
 
-                # calculate u_dot for sensors
-                u_dot = phase.derivative(self.t, self.y_sol)
-                for sensor, position in node._component_sensors:
-                    relative_position = position - self.rocket._csys * Vector(
-                        [0, 0, self.rocket.center_of_dry_mass_position]
-                    )
-                    sensor.measure(
-                        self.t,
-                        self.y_sol,
-                        u_dot,
-                        relative_position,
-                        self.env.gravity(self.solution[-1][3]),
-                    )
+                if self.sensors:
+                    # u_dot for all sensors
+                    u_dot = phase.derivative(self.t, self.y_sol)
+                    for sensor, position in node._component_sensors:
+                        relative_position = position - self.rocket._csys * Vector(
+                            [0, 0, self.rocket.center_of_dry_mass_position]
+                        )
+                        sensor.measure(
+                            self.t,
+                            self.y_sol,
+                            u_dot,
+                            relative_position,
+                            self.env.gravity(self.solution[-1][3]),
+                        )
 
                 for controller in node._controllers:
                     controller(
                         self.t,
                         self.y_sol,
                         self.solution,
-                        self._sensors_list,
+                        self.sensors,
                     )
 
                 for parachute in node.parachutes:
@@ -745,7 +744,7 @@ def __init__(
                         - self.env.elevation
                     )
                     if parachute.triggerfunc(
-                        pressure + noise, hAGL, self.y_sol, self._sensors_list
+                        pressure + noise, hAGL, self.y_sol, self.sensors
                     ):
                         # print('\nEVENT DETECTED')
                         # print('Parachute Triggered')

From 216523c1252a57a829435584152f276d62ca4fe6 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:49:41 +0200
Subject: [PATCH 032/120] ENH: add final sensor cache

---
 rocketpy/simulation/flight.py | 23 ++++++++++++++++++++++-
 1 file changed, 22 insertions(+), 1 deletion(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 46de2dbc7..eb25283c1 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -1114,6 +1114,8 @@ def __init__(
         self._calculate_pressure_signal()
         if self._controllers:
             self.__cache_post_process_variables()
+        if self.sensors:
+            self.__cache_sensor_data()
         if verbose:
             print("Simulation Completed at Time: {:3.4f} s".format(self.t))
 
@@ -1284,6 +1286,25 @@ def __cache_post_process_variables(self):
             self.wind_velocity_y_list,
         ]
 
+    def __cache_sensor_data(self):
+        sensor_data = {}
+        sensors = []
+        for sensor in self.sensors:
+            # skip sensors that are used more then once in the rocket
+            if sensor not in sensors:
+                sensors.append(sensor)
+                num_instances = sensor._attached_rockets[self.rocket]
+                # sensor added only once
+                if num_instances == 1:
+                    sensor_data[sensor] = sensor.measured_data[:]
+                # sensor added more then once
+                if num_instances > 1:
+                    sensor_data[sensor] = {}
+                    # iterate through each of the same sensor instances
+                    for index in range(num_instances):
+                        sensor_data[sensor][index + 1] = sensor.measured_data[index][:]
+        self.sensor_data = sensor_data
+
     @cached_property
     def effective_1rl(self):
         """Original rail length minus the distance measured from nozzle exit
@@ -3796,6 +3817,6 @@ def __repr__(self):
                     + " | Controllers: "
                     + str(len(self._controllers))
                     + " | Sensors: "
-                    + str(len(self._sensors_list))
+                    + str(len(self._component_sensors))
                     + "}"
                 )

From 09288d4478685a39d17b18f20ecfed19c1d9a208 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 15:49:53 +0200
Subject: [PATCH 033/120] ENH: add export sensor data

---
 rocketpy/simulation/flight.py | 27 ++++++++++++++++++++++++++-
 1 file changed, 26 insertions(+), 1 deletion(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index eb25283c1..a1edc497f 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -1,3 +1,4 @@
+import json
 import math
 import warnings
 from copy import deepcopy
@@ -3394,7 +3395,31 @@ class attributes which are instances of the Function class. Usage
             encoding="utf-8",
         )
 
-        return
+    def export_sensor_data(self, file_name, sensor=None):
+        """Exports sensors data to a file. The file format can be either .csv or
+        .json.
+
+        Parameters
+        ----------
+        file_name : str
+            The file name or path of the exported file. Example: flight_data.csv
+            Do not use forbidden characters, such as / in Linux/Unix and
+            `<, >, :, ", /, \\, | ?, *` in Windows.
+        sensor : Sensor, optional
+            The sensor to export data. If None, all sensors data will be exported.
+            Default is None.
+        """
+        if sensor is None:
+            data_dict = {}
+            for key, value in self.sensor_data.items():
+                data_dict[key.name] = value
+        else:
+            # export data of only that sensor
+            data_dict = {}
+            data_dict[sensor.name] = self.sensor_data[sensor]
+        with open(file_name, "w") as file:
+                json.dump(data_dict, file)
+        print("Sensor data exported to", file_name)
 
     def export_kml(
         self,

From aa6fcdf18553e22df8da8c7f9ab486ee5d77e627 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 22:53:10 +0200
Subject: [PATCH 034/120] BUG: wrong initialization order

---
 rocketpy/sensors/sensors.py   | 3 ++-
 rocketpy/simulation/flight.py | 4 ++--
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 8ecf20c2c..a377bb7c9 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -160,6 +160,7 @@ def __init__(
         self.measurement = None
         self.measured_data = []
         self._counter = 0
+        self._save_data = self._save_data_single
 
         # handle measurement range
         if isinstance(measurement_range, (tuple, list)):
@@ -221,7 +222,7 @@ def _reset(self, simulated_rocket):
         else:
             self._save_data = self._save_data_single
 
-    def _save_data_single(self, data, index=0):
+    def _save_data_single(self, data):
         """Save the measured data to the sensor data list for a sensor that is
         added only once to the simulated rocket."""
         self.measured_data.append(data)
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index a1edc497f..6386157d3 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -1247,6 +1247,7 @@ def __init_equations_of_motion(self):
     def __init_controllers(self):
         """Initialize controllers and sensors"""
         self._controllers = self.rocket._controllers[:]
+        self.sensors = self.rocket.sensors.get_components()
         if self._controllers or self.sensors:
             if self.time_overshoot == True:
                 self.time_overshoot = False
@@ -1258,7 +1259,6 @@ def __init_controllers(self):
             for air_brakes in self.rocket.air_brakes:
                 air_brakes._reset()
 
-        self.sensors = self.rocket.sensors.get_components()
         self.sensor_data = {}
         for sensor in self.sensors:
             sensor._reset(self.rocket)  # resets noise and measurement list
@@ -3418,7 +3418,7 @@ def export_sensor_data(self, file_name, sensor=None):
             data_dict = {}
             data_dict[sensor.name] = self.sensor_data[sensor]
         with open(file_name, "w") as file:
-                json.dump(data_dict, file)
+            json.dump(data_dict, file)
         print("Sensor data exported to", file_name)
 
     def export_kml(

From bf6b083270940454f3caa23b284616b49ed1f773 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 23:19:28 +0200
Subject: [PATCH 035/120] TST: test for new measured_data and exports

---
 tests/fixtures/rockets/rocket_fixtures.py |  2 +
 tests/test_sensors.py                     | 56 ++++++++++++++++++--
 tests/unit/test_sensors.py                | 64 +++++++++++++++++++++++
 3 files changed, 118 insertions(+), 4 deletions(-)

diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index e6231209a..0161f3950 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -274,6 +274,8 @@ def calisto_accel_gyro(
     calisto.add_surfaces(calisto_nose_cone, 1.160)
     calisto.add_surfaces(calisto_tail, -1.313)
     calisto.add_surfaces(calisto_trapezoidal_fins, -1.168)
+    # double sensors to test using same instance twice
+    calisto.add_sensor(ideal_accelerometer, -0.1180124376577797)
     calisto.add_sensor(ideal_accelerometer, -0.1180124376577797)
     calisto.add_sensor(ideal_gyroscope, -0.1180124376577797)
     return calisto
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index b94d2bc7f..92960732e 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -1,3 +1,5 @@
+import json
+import os
 import numpy as np
 
 from rocketpy.mathutils.vector_matrix import Vector
@@ -18,8 +20,8 @@ def test_sensor_on_rocket(calisto_accel_gyro):
     assert isinstance(sensors, Components)
     assert isinstance(sensors[0].component, Accelerometer)
     assert isinstance(sensors[1].position, Vector)
-    assert isinstance(sensors[1].component, Gyroscope)
-    assert isinstance(sensors[1].position, Vector)
+    assert isinstance(sensors[2].component, Gyroscope)
+    assert isinstance(sensors[2].position, Vector)
 
 
 def test_ideal_sensors(flight_calisto_accel_gyro):
@@ -32,7 +34,7 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
     accelerometer = flight_calisto_accel_gyro.rocket.sensors[0].component
-    time, ax, ay, az = zip(*accelerometer.measured_data)
+    time, ax, ay, az = zip(*accelerometer.measured_data[0])
     ax = np.array(ax)
     ay = np.array(ay)
     az = np.array(az)
@@ -41,8 +43,13 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
 
     # tolerance is bounded to numerical errors in the transformation matrixes
     assert np.allclose(a, sim_accel, atol=1e-12)
+    # check if both added accelerometer instances saved the same data
+    assert (
+        flight_calisto_accel_gyro.sensors[0].measured_data[0]
+        == flight_calisto_accel_gyro.sensors[0].measured_data[1]
+    )
 
-    gyroscope = flight_calisto_accel_gyro.rocket.sensors[1].component
+    gyroscope = flight_calisto_accel_gyro.rocket.sensors[2].component
     time, wx, wy, wz = zip(*gyroscope.measured_data)
     wx = np.array(wx)
     wy = np.array(wy)
@@ -53,3 +60,44 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
     flight_wz = np.array(flight_calisto_accel_gyro.w3(time))
     sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
     assert np.allclose(w, sim_w, atol=1e-12)
+
+
+def test_export_sensor_data(flight_calisto_accel_gyro):
+    """Test the export of sensor data.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    """
+    flight_calisto_accel_gyro.export_sensor_data("test_sensor_data.json")
+    # read the json and parse as dict
+    filename = "test_sensor_data.json"
+    with open(filename, "r") as f:
+        data = f.read()
+        sensor_data = json.loads(data)
+    # convert list of tuples into list of lists to compare with the json
+    flight_calisto_accel_gyro.sensors[0].measured_data[0] = [
+        list(measurement)
+        for measurement in flight_calisto_accel_gyro.sensors[0].measured_data[0]
+    ]
+    flight_calisto_accel_gyro.sensors[1].measured_data[1] = [
+        list(measurement)
+        for measurement in flight_calisto_accel_gyro.sensors[1].measured_data[1]
+    ]
+    flight_calisto_accel_gyro.sensors[2].measured_data = [
+        list(measurement)
+        for measurement in flight_calisto_accel_gyro.sensors[2].measured_data
+    ]
+    assert (
+        sensor_data["Accelerometer"]["1"]
+        == flight_calisto_accel_gyro.sensors[0].measured_data[0]
+    )
+    assert (
+        sensor_data["Accelerometer"]["2"]
+        == flight_calisto_accel_gyro.sensors[1].measured_data[1]
+    )
+    assert (
+        sensor_data["Gyroscope"] == flight_calisto_accel_gyro.sensors[2].measured_data
+    )
+    os.remove(filename)
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 81448c2a4..ebb0c5b60 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -300,7 +300,24 @@ def test_export_accel_data_csv(ideal_accelerometer):
         expected_data += f"{t},{ax},{ay},{az}\n"
 
     assert contents == expected_data
+
+    # check exports for accelerometers added more than once to the rocket
+    ideal_accelerometer.measured_data = [
+        ideal_accelerometer.measured_data[:],
+        ideal_accelerometer.measured_data[:],
+    ]
+    ideal_accelerometer.export_measured_data(file_name, format="csv")
+    with open(file_name + "_1", "r") as file:
+        contents = file.read()
+    assert contents == expected_data
+
+    with open(file_name + "_2", "r") as file:
+        contents = file.read()
+    assert contents == expected_data
+
     os.remove(file_name)
+    os.remove(file_name + "_1")
+    os.remove(file_name + "_2")
 
 
 def test_export_accel_data_json(ideal_accelerometer):
@@ -334,7 +351,22 @@ def test_export_accel_data_json(ideal_accelerometer):
         expected_data["az"].append(az)
 
     assert contents == expected_data
+
+    # check exports for accelerometers added more than once to the rocket
+    ideal_accelerometer.measured_data = [
+        ideal_accelerometer.measured_data[:],
+        ideal_accelerometer.measured_data[:],
+    ]
+    ideal_accelerometer.export_measured_data(file_name, format="json")
+    contents = json.load(open(file_name + "_1", "r"))
+    assert contents == expected_data
+
+    contents = json.load(open(file_name + "_2", "r"))
+    assert contents == expected_data
+
     os.remove(file_name)
+    os.remove(file_name + "_1")
+    os.remove(file_name + "_2")
 
 
 def test_export_gyro_data_csv(ideal_gyroscope):
@@ -365,7 +397,24 @@ def test_export_gyro_data_csv(ideal_gyroscope):
         expected_data += f"{t},{wx},{wy},{wz}\n"
 
     assert contents == expected_data
+
+    # check exports for gyroscopes added more than once to the rocket
+    ideal_gyroscope.measured_data = [
+        ideal_gyroscope.measured_data[:],
+        ideal_gyroscope.measured_data[:],
+    ]
+    ideal_gyroscope.export_measured_data(file_name, format="csv")
+    with open(file_name + "_1", "r") as file:
+        contents = file.read()
+    assert contents == expected_data
+
+    with open(file_name + "_2", "r") as file:
+        contents = file.read()
+    assert contents == expected_data
+
     os.remove(file_name)
+    os.remove(file_name + "_1")
+    os.remove(file_name + "_2")
 
 
 def test_export_gyro_data_json(ideal_gyroscope):
@@ -397,4 +446,19 @@ def test_export_gyro_data_json(ideal_gyroscope):
         expected_data["wz"].append(wz)
 
     assert contents == expected_data
+
+    # check exports for gyroscopes added more than once to the rocket
+    ideal_gyroscope.measured_data = [
+        ideal_gyroscope.measured_data[:],
+        ideal_gyroscope.measured_data[:],
+    ]
+    ideal_gyroscope.export_measured_data(file_name, format="json")
+    contents = json.load(open(file_name + "_1", "r"))
+    assert contents == expected_data
+
+    contents = json.load(open(file_name + "_2", "r"))
+    assert contents == expected_data
+
     os.remove(file_name)
+    os.remove(file_name + "_1")
+    os.remove(file_name + "_2")

From 5f8622300a77af3b2927526b66ed5798d7b745c8 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Tue, 30 Apr 2024 23:30:59 +0200
Subject: [PATCH 036/120] ENH: abstract noise printings

---
 rocketpy/prints/sensors_prints.py | 22 +++++++++++++++++-----
 1 file changed, 17 insertions(+), 5 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 8c073190f..554d817e0 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -44,7 +44,12 @@ def quantization(self):
         )
         self._print_aligned("Resolution:", f"{self.sensor.resolution} {self.units}/LSB")
 
+    @abstractmethod
     def noise(self):
+        """Prints the noise of the sensor."""
+        pass
+
+    def _general_noise(self):
         """Prints the noise of the sensor."""
         print("\nNoise of the Sensor:\n")
         self._print_aligned(
@@ -68,11 +73,6 @@ def noise(self):
         self._print_aligned(
             "Cross Axis Sensitivity:", f"{self.sensor.cross_axis_sensitivity} %"
         )
-        if self.sensor.type == "Gyroscope":
-            self._print_aligned(
-                "Acceleration Sensitivity:",
-                f"{self.sensor.acceleration_sensitivity} rad/s/g",
-            )
 
     def all(self):
         """Prints all information of the sensor."""
@@ -89,6 +89,10 @@ def __init__(self, accelerometer):
         """Initialize the class."""
         super().__init__(accelerometer)
 
+    def noise(self):
+        """Prints the noise of the sensor."""
+        self._general_noise()
+
 
 class _GyroscopePrints(_SensorsPrints):
     """Class that contains all gyroscope prints."""
@@ -96,3 +100,11 @@ class _GyroscopePrints(_SensorsPrints):
     def __init__(self, gyroscope):
         """Initialize the class."""
         super().__init__(gyroscope)
+
+    def noise(self):
+        """Prints the noise of the sensor."""
+        self._general_noise()
+        self._print_aligned(
+            "Acceleration Sensitivity:",
+            f"{self.sensor.acceleration_sensitivity} rad/s/g",
+        )

From 4dcc26bf792d36653da1d3dc29fb3558767227d6 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Wed, 1 May 2024 17:53:31 +0200
Subject: [PATCH 037/120] MNT: run isort

---
 rocketpy/sensors/accelerometer.py | 3 ++-
 rocketpy/sensors/gyroscope.py     | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 0028b9aa1..e1b5f1c43 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -1,6 +1,7 @@
-import numpy as np
 import json
 
+import numpy as np
+
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _AccelerometerPrints
 from ..sensors.sensors import Sensors
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 5275ed600..c18446032 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -1,6 +1,7 @@
-import numpy as np
 import json
 
+import numpy as np
+
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
 from ..sensors.sensors import Sensors

From 2131ee9cc28620dd0ee05a59bda3e6a5e7cdb267 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 2 May 2024 16:31:48 +0200
Subject: [PATCH 038/120] ENH: add noise variance

---
 rocketpy/sensors/accelerometer.py | 53 +++++++++++++-----
 rocketpy/sensors/gyroscope.py     | 55 +++++++++++++------
 rocketpy/sensors/sensors.py       | 90 ++++++++++++++++++++++---------
 3 files changed, 145 insertions(+), 53 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index e1b5f1c43..b5e447085 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -28,8 +28,12 @@ class Accelerometer(Sensors):
         The resolution of the sensor in m/s^2/LSB.
     noise_density : float, list
         The noise density of the sensor in m/s^2/√Hz.
-    random_walk : float, list
-        The random walk of the sensor in m/s^2/√Hz.
+    noise_variance : float, list
+        The variance of the noise of the sensor in (m/s^2)^2.
+    random_walk_density : float, list
+        The random walk density of the sensor in m/s^2/√Hz.
+    random_walk_variance : float, list
+        The variance of the random walk of the sensor in (m/s^2)^2.
     constant_bias : float, list
         The constant bias of the sensor in m/s^2.
     operating_temperature : float
@@ -64,7 +68,9 @@ def __init__(
         measurement_range=np.inf,
         resolution=0,
         noise_density=0,
-        random_walk=0,
+        noise_variance=1,
+        random_walk_density=0,
+        random_walk_variance=1,
         constant_bias=0,
         operating_temperature=25,
         temperature_bias=0,
@@ -108,18 +114,31 @@ def __init__(
             The resolution of the sensor in m/s^2/LSB. Default is 0, meaning no
             quantization is applied.
         noise_density : float, list, optional
-            The noise density of the sensor in m/s^2/√Hz. Sometimes called
-            "white noise drift", "angular random walk" for gyroscopes, "velocity
-            random walk" for the accelerometers or "(rate) noise density". If a
-            float or int is given, the same noise density is applied to all
+            The noise density of the sensor for a Gaussian white noise in m/s^2/√Hz.
+            Sometimes called "white noise drift", "angular random walk" for
+            gyroscopes, "velocity random walk" for accelerometers or
+            "(rate) noise density". Default is 0, meaning no noise is applied.
+            If a float or int is given, the same noise density is applied to all
             axes. The values of each axis can be set individually by passing a
             list of length 3.
-        random_walk : float, list, optional
-            The random walk of the sensor in m/s^2/√Hz. Sometimes called "bias
-            (in)stability" or "bias drift"". Default is 0, meaning no random
-            walk is applied. If a float or int is given, the same random walk is
-            applied to all axes. The values of each axis can be set individually
-            by passing a list of length 3.
+        noise_variance : float, list, optional
+            The noise variance of the sensor for a Gaussian white noise in (m/s^2)^2.
+            Default is 1, meaning the noise is normally distributed with a
+            standard deviation of 1 m/s^2. If a float or int is given, the same
+            variance is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        random_walk_density : float, list, optional
+            The random walk of the sensor for a Gaussian random walk in m/s^2/√Hz.
+            Sometimes called "bias (in)stability" or "bias drift"". Default is 0,
+            meaning no random walk is applied. If a float or int is given, the
+            same random walk is applied to all axes. The values of each axis can
+            be set individually by passing a list of length 3.
+        random_walk_variance : float, list, optional
+            The random walk variance of the sensor for a Gaussian random walk in
+            (m/s^2)^2. Default is 1, meaning the noise is normally distributed
+            with a standard deviation of 1 m/s^2. If a float or int is given,
+            the same variance is applied to all axes. The values of each axis
+            can be set individually by passing a list of length 3.
         constant_bias : float, list, optional
             The constant bias of the sensor in m/s^2. Default is 0, meaning no
             constant bias is applied. If a float or int is given, the same bias
@@ -151,6 +170,10 @@ def __init__(
         Returns
         -------
         None
+
+        See Also
+        --------
+        TODO link to documentation on noise model
         """
         super().__init__(
             sampling_rate,
@@ -158,7 +181,9 @@ def __init__(
             measurement_range=measurement_range,
             resolution=resolution,
             noise_density=noise_density,
-            random_walk=random_walk,
+            noise_variance=noise_variance,
+            random_walk_density=random_walk_density,
+            random_walk_variance=random_walk_variance,
             constant_bias=constant_bias,
             operating_temperature=operating_temperature,
             temperature_bias=temperature_bias,
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index c18446032..6ba2b945d 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -28,8 +28,12 @@ class Gyroscope(Sensors):
         The resolution of the sensor in rad/s/LSB.
     noise_density : float, list
         The noise density of the sensor in rad/s/√Hz.
-    random_walk : float, list
-        The random walk of the sensor in rad/s/√Hz.
+    noise_variance : float, list
+        The variance of the noise of the sensor in (rad/s)^2.
+    random_walk_density : float, list
+        The random walk density of the sensor in rad/s/√Hz.
+    random_walk_variance : float, list
+        The random walk variance of the sensor in (rad/s)^2.
     constant_bias : float, list
         The constant bias of the sensor in rad/s.
     operating_temperature : float
@@ -64,7 +68,9 @@ def __init__(
         measurement_range=np.inf,
         resolution=0,
         noise_density=0,
-        random_walk=0,
+        noise_variance=1,
+        random_walk_density=0,
+        random_walk_variance=1,
         constant_bias=0,
         operating_temperature=25,
         temperature_bias=0,
@@ -106,18 +112,31 @@ def __init__(
             The resolution of the sensor in rad/s/LSB. Default is 0, meaning no
             quantization is applied.
         noise_density : float, list, optional
-            The noise density of the sensor in rad/s/√Hz. Sometimes called
-            "white noise drift", "angular random walk" for gyroscopes, "velocity
-            random walk" for the accelerometers or "(rate) noise density".
-            Default is 0, meaning no noise is applied. If a float or int is
-            given, the same noise density is applied to all axes. The values of
+            The noise density of the sensor for a Gaussian white noise in rad/s/√Hz.
+            Sometimes called "white noise drift", "angular random walk" for
+            gyroscopes, "velocity random walk" for the accelerometers or
+            "(rate) noise density". Default is 0, meaning no noise is applied.
+            If a float or int is given, the same noise density is applied to all
+            axes. The values of each axis can be set individually by passing a
+            list of length 3.
+        noise_variance : float, list, optional
+            The noise variance of the sensor for a Gaussian white noise in (rad/s)^2.
+            Default is 1, meaning the noise is normally distributed with a
+            standard deviation of 1 rad/s. If a float or int is given, the same
+            variance is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        random_walk_density : float, list, optional
+            The random walk density of the sensor for a Gaussian random walk in
+            rad/s/√Hz. Sometimes called "bias (in)stability" or "bias drift"".
+            Default is 0, meaning no random walk is applied. If a float or int
+            is given, the same random walk is applied to all axes. The values of
+            each axis can be set individually by passing a list of length 3.
+        random_walk_variance : float, list, optional
+            The random walk variance of the sensor for a Gaussian random walk in
+            (rad/s)^2. Default is 1, meaning the random walk is normally
+            distributed with a standard deviation of 1 rad/s. If a float or int
+            is given, the same variance is applied to all axes. The values of
             each axis can be set individually by passing a list of length 3.
-        random_walk : float, list, optional
-            The random walk of the sensor in rad/s/√Hz. Sometimes called "bias
-            (in)stability" or "bias drift"". Default is 0, meaning no random
-            walk is applied. If a float or int is given, the same random walk is
-            applied to all axes. The values of each axis can be set individually
-            by passing a list of length 3.
         constant_bias : float, list, optional
             The constant bias of the sensor in rad/s. Default is 0, meaning no
             constant bias is applied. If a float or int is given, the same bias
@@ -151,6 +170,10 @@ def __init__(
         Returns
         -------
         None
+
+        See Also
+        --------
+        TODO link to documentation on noise model
         """
         super().__init__(
             sampling_rate,
@@ -158,7 +181,9 @@ def __init__(
             measurement_range=measurement_range,
             resolution=resolution,
             noise_density=noise_density,
-            random_walk=random_walk,
+            noise_variance=noise_variance,
+            random_walk_density=random_walk_density,
+            random_walk_variance=random_walk_variance,
             constant_bias=constant_bias,
             operating_temperature=operating_temperature,
             temperature_bias=temperature_bias,
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index a377bb7c9..0a8438840 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -22,8 +22,12 @@ class Sensors(ABC):
         The resolution of the sensor in sensor units/LSB.
     noise_density : float, list
         The noise density of the sensor in sensor units/√Hz.
-    random_walk : float, list
-        The random walk of the sensor in sensor units/√Hz.
+    noise_variance : float, list
+        The variance of the noise of the sensor in sensor units^2.
+    random_walk_density : float, list
+        The random walk density of the sensor in sensor units/√Hz.
+    random_walk_variance : float, list
+        The variance of the random walk of the sensor in sensor units^2.
     constant_bias : float, list
         The constant bias of the sensor in sensor units.
     operating_temperature : float
@@ -58,7 +62,9 @@ def __init__(
         measurement_range=np.inf,
         resolution=0,
         noise_density=0,
-        random_walk=0,
+        noise_variance=1,
+        random_walk_density=0,
+        random_walk_variance=1,
         constant_bias=0,
         operating_temperature=25,
         temperature_bias=0,
@@ -99,19 +105,33 @@ def __init__(
             The resolution of the sensor in sensor units/LSB. Default is 0,
             meaning no quantization is applied.
         noise_density : float, list, optional
-            The noise density of the sensor in sensor units/√Hz. Sometimes
-            called "white noise drift", "angular random walk" for gyroscopes,
-            "velocity random walk" for the accelerometers or
-            "(rate) noise density". Default is 0, meaning no noise is applied.
-            If a float or int is given, the same noise density is applied to all
+            The noise density of the sensor for a Gaussian white noise in sensor
+            units/√Hz. Sometimes called "white noise drift",
+            "angular random walk" for gyroscopes, "velocity random walk" for
+            accelerometers or "(rate) noise density". Default is 0, meaning no
+            noise is applied. If a float or int is given, the same noise density
+            is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        noise_variance : float, list, optional
+            The noise variance of the sensor for a Gaussian white noise in
+            sensor units^2. Default is 1, meaning the noise is normally
+            distributed with a standard deviation of 1 unit. If a float or int
+            is given, the same noise variance is applied to all axes. The values
+            of each axis can be set individually by passing a list of length 3.
+        random_walk_density : float, list, optional
+            The random walk density of the sensor for a Gaussian random walk in
+            sensor units/√Hz. Sometimes called "bias (in)stability" or
+            "bias drift". Default is 0, meaning no random walk is applied.
+            If a float or int is given, the same random walk is applied to all
             axes. The values of each axis can be set individually by passing a
             list of length 3.
-        random_walk : float, list, optional
-            The random walk of the sensor in sensor units/√Hz. Sometimes called
-            "bias (in)stability" or "bias drift"". Default is 0, meaning no
-            random walk is applied. If a float or int is given, the same random
-            walk is applied to all axes. The values of each axis can be set
-            individually by passing a list of length 3.
+        random_walk_variance : float, list, optional
+            The random walk variance of the sensor for a Gaussian random walk in
+            sensor units^2. Default is 1, meaning the noise is normally
+            distributed with a standard deviation of 1 unit. If a float or int
+            is given, the same random walk variance is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
         constant_bias : float, list, optional
             The constant bias of the sensor in sensor units. Default is 0,
             meaning no constant bias is applied. If a float or int is given, the
@@ -140,13 +160,23 @@ def __init__(
         Returns
         -------
         None
+
+        See Also
+        --------
+        TODO link to documentation on noise model
         """
         self.sampling_rate = sampling_rate
         self.orientation = orientation
         self.resolution = resolution
         self.operating_temperature = operating_temperature
         self.noise_density = self._vectorize_input(noise_density, "noise_density")
-        self.random_walk = self._vectorize_input(random_walk, "random_walk")
+        self.noise_variance = self._vectorize_input(noise_variance, "noise_variance")
+        self.random_walk_density = self._vectorize_input(
+            random_walk_density, "random_walk_density"
+        )
+        self.random_walk_variance = self._vectorize_input(
+            random_walk_variance, "random_walk_variance"
+        )
         self.constant_bias = self._vectorize_input(constant_bias, "constant_bias")
         self.temperature_bias = self._vectorize_input(
             temperature_bias, "temperature_bias"
@@ -202,6 +232,12 @@ def __init__(
         # map which rocket(s) the sensor is attached to and how many times
         self._attached_rockets = {}
 
+    def __repr__(self):
+        return f"{self.name}"
+
+    def __call__(self, *args, **kwargs):
+        return self.measure(*args, **kwargs)
+
     def _vectorize_input(self, value, name):
         if isinstance(value, (int, float)):
             return Vector([value, value, value])
@@ -236,12 +272,6 @@ def _save_data_multiple(self, data):
         if self._counter == len(self.measured_data):
             self._counter = 0
 
-    def __repr__(self):
-        return f"{self.name}"
-
-    def __call__(self, *args, **kwargs):
-        return self.measure(*args, **kwargs)
-
     @abstractmethod
     def measure(self, *args, **kwargs):
         pass
@@ -289,13 +319,25 @@ def apply_noise(self, value):
         """
         # white noise
         white_noise = (
-            np.random.normal(0, 1) * self.noise_density * self.sampling_rate**0.5
-        )
+            Vector(
+                [np.random.normal(0, self.noise_variance[i] ** 0.5) for i in range(3)]
+            )
+            & self.noise_density
+        ) * self.sampling_rate**0.5
 
         # random walk
         self._random_walk_drift = (
             self._random_walk_drift
-            + np.random.normal(0, 1) * self.random_walk / self.sampling_rate**0.5
+            + (
+                Vector(
+                    [
+                        np.random.normal(0, self.random_walk_variance[i] ** 0.5)
+                        for i in range(3)
+                    ]
+                )
+                & self.random_walk_density
+            )
+            / self.sampling_rate**0.5
         )
 
         # add noise

From b2da0c3ab4e649951754739298893ef5ae0981a7 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 2 May 2024 16:33:53 +0200
Subject: [PATCH 039/120] BUG: fix prints for noise variance

---
 rocketpy/prints/sensors_prints.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 554d817e0..95e3458c0 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -56,7 +56,15 @@ def _general_noise(self):
             "Noise Density:", f"{self.sensor.noise_density} {self.units}/√Hz"
         )
         self._print_aligned(
-            "Random Walk:", f"{self.sensor.random_walk} {self.units}/√Hz"
+            "Noise Variance:", f"{self.sensor.noise_variance} ({self.units})^2"
+        )
+        self._print_aligned(
+            "Random Walk Density:",
+            f"{self.sensor.random_walk_density} {self.units}/√Hz",
+        )
+        self._print_aligned(
+            "Random Walk Variance:",
+            f"{self.sensor.random_walk_variance} ({self.units})^2",
         )
         self._print_aligned(
             "Constant Bias:", f"{self.sensor.constant_bias} {self.units}"

From 123d033d0038bcef612a2ba71013d2f33c5c191d Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 2 May 2024 16:34:07 +0200
Subject: [PATCH 040/120] TST: add variances

---
 tests/fixtures/sensors/sensors_fixtures.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
index a4ea781c8..c32a41124 100644
--- a/tests/fixtures/sensors/sensors_fixtures.py
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -7,12 +7,14 @@
 def noisy_rotated_accelerometer():
     """Returns an accelerometer with all parameters set to non-default values,
     i.e. with noise and rotation."""
-    # mpu6050 approx values
+    # mpu6050 approx values, variances are made up
     return Accelerometer(
         sampling_rate=100,
         orientation=(60, 60, 60),
         noise_density=[0, 0.03, 0.05],
-        random_walk=[0, 0.01, 0.02],
+        noise_variance=1.01,
+        random_walk_density=[0, 0.01, 0.02],
+        random_walk_variance=[1, 1, 1.05],
         constant_bias=[0, 0.3, 0.5],
         operating_temperature=25,
         temperature_bias=[0, 0.01, 0.02],
@@ -27,12 +29,14 @@ def noisy_rotated_accelerometer():
 def noisy_rotated_gyroscope():
     """Returns a gyroscope with all parameters set to non-default values,
     i.e. with noise and rotation."""
-    # mpu6050 approx values
+    # mpu6050 approx values, variances are made up
     return Gyroscope(
         sampling_rate=100,
         orientation=(-60, -60, -60),
         noise_density=[0, 0.03, 0.05],
-        random_walk=[0, 0.01, 0.02],
+        noise_variance=1.01,
+        random_walk_density=[0, 0.01, 0.02],
+        random_walk_variance=[1, 1, 1.05],
         constant_bias=[0, 0.3, 0.5],
         operating_temperature=25,
         temperature_bias=[0, 0.01, 0.02],

From 00f0f3a2a562e3fbb3b2ae22edc3da1625f1d3d2 Mon Sep 17 00:00:00 2001
From: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date: Fri, 3 May 2024 15:30:25 -0300
Subject: [PATCH 041/120] Update rocketpy/rocket/rocket.py

Co-authored-by: Pedro Henrique Marinho Bressan <87212571+phmbressan@users.noreply.github.com>
---
 rocketpy/rocket/rocket.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index 073c9c60a..7e03d2522 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -1194,7 +1194,7 @@ def add_sensor(self, sensor, position, x_position=0, y_position=0):
         self.sensors.add(sensor, Vector([x_position, y_position, position]))
         try:
             sensor._attached_rockets[self] += 1
-        except:
+        except KeyError:
             sensor._attached_rockets[self] = 1
 
     def add_air_brakes(

From b4b51a4f471d80fff1ab58eea1308b5a978044b8 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 3 May 2024 23:55:33 +0200
Subject: [PATCH 042/120] ENH: add pressure to .measure params

---
 rocketpy/sensors/accelerometer.py | 33 ++++++++++++++++++++-----------
 rocketpy/sensors/gyroscope.py     | 30 ++++++++++++++++++----------
 rocketpy/simulation/flight.py     | 13 +++++++-----
 3 files changed, 49 insertions(+), 27 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index b5e447085..e0d7a4f38 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -195,22 +195,31 @@ def __init__(
         self.consider_gravity = consider_gravity
         self.prints = _AccelerometerPrints(self)
 
-    def measure(self, t, u, u_dot, relative_position, gravity, *args):
+    def measure(self, time, **kwargs):
         """Measure the acceleration of the rocket
 
         Parameters
         ----------
-        t : float
-            Current time
-        u : list
-            State vector of the rocket
-        u_dot : list
-            Derivative of the state vector of the rocket
-        relative_position : Vector
-            Position of the sensor relative to the rocket cdm
-        gravity : float
-            Acceleration due to gravity
+        time : float
+            Current time in seconds.
+        kwargs : dict
+            Keyword arguments dictionary containing the following keys:
+            - u : np.array
+                State vector of the rocket.
+            - u_dot : np.array
+                Derivative of the state vector of the rocket.
+            - relative_position : np.array
+                Position of the sensor relative to the rocket center of mass.
+            - gravity : float
+                Gravitational acceleration in m/s^2.
+            - pressure : Function
+                Atmospheric pressure profile as a function of altitude in Pa.
         """
+        u = kwargs["u"]
+        u_dot = kwargs["u_dot"]
+        relative_position = kwargs["relative_position"]
+        gravity = kwargs["gravity"]
+
         # Linear acceleration of rocket cdm in inertial frame
         gravity = (
             Vector([0, 0, -gravity]) if self.consider_gravity else Vector([0, 0, 0])
@@ -242,7 +251,7 @@ def measure(self, t, u, u_dot, relative_position, gravity, *args):
         A = self.quantize(A)
 
         self.measurement = tuple([*A])
-        self._save_data((t, *A))
+        self._save_data((time, *A))
 
     def export_measured_data(self, filename, format="csv"):
         """
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 6ba2b945d..c23d64d46 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -197,20 +197,30 @@ def __init__(
         )
         self.prints = _GyroscopePrints(self)
 
-    def measure(self, t, u, u_dot, relative_position, *args):
+    def measure(self, time, **kwargs):
         """Measure the angular velocity of the rocket
 
         Parameters
         ----------
-        t : float
-            Time at which the measurement is taken
-        u : list
-            State vector of the rocket
-        u_dot : list
-            Time derivative of the state vector of the rocket
-        relative_position : Vector
-            Vector from the rocket's center of mass to the sensor
+        time : float
+            Current time in seconds.
+        kwargs : dict
+            Keyword arguments dictionary containing the following keys:
+            - u : np.array
+                State vector of the rocket.
+            - u_dot : np.array
+                Derivative of the state vector of the rocket.
+            - relative_position : np.array
+                Position of the sensor relative to the rocket center of mass.
+            - gravity : float
+                Gravitational acceleration in m/s^2.
+            - pressure : Function
+                Atmospheric pressure profile as a function of altitude in Pa.
         """
+        u = kwargs["u"]
+        u_dot = kwargs["u_dot"]
+        relative_position = kwargs["relative_position"]
+
         # Angular velocity of the rocket in the rocket frame
         omega = Vector(u[10:13])
 
@@ -234,7 +244,7 @@ def measure(self, t, u, u_dot, relative_position, *args):
         W = self.quantize(W)
 
         self.measurement = tuple([*W])
-        self._save_data((t, *W))
+        self._save_data((time, *W))
 
     def apply_acceleration_sensitivity(
         self, omega, u_dot, relative_position, rotation_matrix
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 6386157d3..50bcf9b07 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -709,7 +709,7 @@ def __init__(
                     callback(self)
 
                 if self.sensors:
-                    # u_dot for all sensors
+                    # udot for all sensors
                     u_dot = phase.derivative(self.t, self.y_sol)
                     for sensor, position in node._component_sensors:
                         relative_position = position - self.rocket._csys * Vector(
@@ -717,10 +717,13 @@ def __init__(
                         )
                         sensor.measure(
                             self.t,
-                            self.y_sol,
-                            u_dot,
-                            relative_position,
-                            self.env.gravity(self.solution[-1][3]),
+                            u=self.y_sol,
+                            u_dot=u_dot,
+                            relative_position=relative_position,
+                            gravity=self.env.gravity.get_value_opt(
+                                self.solution[-1][3]
+                            ),
+                            pressure=self.env.pressure,
                         )
 
                 for controller in node._controllers:

From 4c0fbf920edcaccde5266b7eff95e40a0c56dc3e Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sat, 4 May 2024 00:00:37 +0200
Subject: [PATCH 043/120] ENH: add InertialSensors and ScalarSensors

---
 rocketpy/sensors/accelerometer.py |   4 +-
 rocketpy/sensors/gyroscope.py     |   4 +-
 rocketpy/sensors/sensors.py       | 558 +++++++++++++++++++++++++-----
 3 files changed, 467 insertions(+), 99 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index e0d7a4f38..7e332eebf 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -4,10 +4,10 @@
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _AccelerometerPrints
-from ..sensors.sensors import Sensors
+from ..sensors.sensors import InertialSensors
 
 
-class Accelerometer(Sensors):
+class Accelerometer(InertialSensors):
     """Class for the accelerometer sensor
 
     Attributes
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index c23d64d46..bdfb36a05 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -4,10 +4,10 @@
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
-from ..sensors.sensors import Sensors
+from ..sensors.sensors import InertialSensors
 
 
-class Gyroscope(Sensors):
+class Gyroscope(InertialSensors):
     """Class for the gyroscope sensor
 
     Attributes
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 0a8438840..24dd01b8a 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -8,6 +8,222 @@
 class Sensors(ABC):
     """Abstract class for sensors
 
+    Attributes
+    ----------
+    type : str
+        Type of the sensor (e.g. Accelerometer, Gyroscope).
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    measurement_range : float, tuple
+        The measurement range of the sensor in the sensor units.
+    resolution : float
+        The resolution of the sensor in sensor units/LSB.
+    noise_density : float, list
+        The noise density of the sensor in sensor units/√Hz.
+    noise_variance : float, list
+        The variance of the noise of the sensor in sensor units^2.
+    random_walk_density : float, list
+        The random walk density of the sensor in sensor units/√Hz.
+    random_walk_variance : float, list
+        The variance of the random walk of the sensor in sensor units^2.
+    constant_bias : float, list
+        The constant bias of the sensor in sensor units.
+    operating_temperature : float
+        The operating temperature of the sensor in degrees Celsius.
+    temperature_bias : float, list
+        The temperature bias of the sensor in sensor units/°C.
+    temperature_scale_factor : float, list
+        The temperature scale factor of the sensor in %/°C.
+    name : str
+        The name of the sensor.
+    measurement : float
+        The measurement of the sensor after quantization, noise and temperature
+        drift.
+    measured_data : list
+        The stored measured data of the sensor after quantization, noise and
+        temperature drift.
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        measurement_range=np.inf,
+        resolution=0,
+        noise_density=0,
+        noise_variance=1,
+        random_walk_density=0,
+        random_walk_variance=1,
+        constant_bias=0,
+        operating_temperature=25,
+        temperature_bias=0,
+        temperature_scale_factor=0,
+        name="Sensor",
+    ):
+        """
+        Initialize the accelerometer sensor
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor
+        measurement_range : float, tuple, optional
+            The measurement range of the sensor in the sensor units. If a float,
+            the same range is applied both for positive and negative values. If
+            a tuple, the first value is the positive range and the second value
+            is the negative range. Default is np.inf.
+        resolution : float, optional
+            The resolution of the sensor in sensor units/LSB. Default is 0,
+            meaning no quantization is applied.
+        noise_density : float, list, optional
+            The noise density of the sensor for a Gaussian white noise in sensor
+            units/√Hz. Sometimes called "white noise drift",
+            "angular random walk" for gyroscopes, "velocity random walk" for
+            accelerometers or "(rate) noise density". Default is 0, meaning no
+            noise is applied. If a float or int is given, the same noise density
+            is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        noise_variance : float, list, optional
+            The noise variance of the sensor for a Gaussian white noise in
+            sensor units^2. Default is 1, meaning the noise is normally
+            distributed with a standard deviation of 1 unit. If a float or int
+            is given, the same noise variance is applied to all axes. The values
+            of each axis can be set individually by passing a list of length 3.
+        random_walk_density : float, list, optional
+            The random walk density of the sensor for a Gaussian random walk in
+            sensor units/√Hz. Sometimes called "bias (in)stability" or
+            "bias drift". Default is 0, meaning no random walk is applied.
+            If a float or int is given, the same random walk is applied to all
+            axes. The values of each axis can be set individually by passing a
+            list of length 3.
+        random_walk_variance : float, list, optional
+            The random walk variance of the sensor for a Gaussian random walk in
+            sensor units^2. Default is 1, meaning the noise is normally
+            distributed with a standard deviation of 1 unit. If a float or int
+            is given, the same random walk variance is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
+        constant_bias : float, list, optional
+            The constant bias of the sensor in sensor units. Default is 0,
+            meaning no constant bias is applied. If a float or int is given, the
+            same constant bias is applied to all axes. The values of each axis
+            can be set individually by passing a list of length 3.
+        operating_temperature : float, optional
+            The operating temperature of the sensor in degrees Celsius. At 25°C,
+            the temperature bias and scale factor are 0. Default is 25.
+        temperature_bias : float, list, optional
+            The temperature bias of the sensor in sensor units/°C. Default is 0,
+            meaning no temperature bias is applied. If a float or int is given,
+            the same temperature bias is applied to all axes. The values of each
+            axis can be set individually by passing a list of length 3.
+        temperature_scale_factor : float, list, optional
+            The temperature scale factor of the sensor in %/°C. Default is 0,
+            meaning no temperature scale factor is applied. If a float or int is
+            given, the same temperature scale factor is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
+        name : str, optional
+            The name of the sensor. Default is "Sensor".
+
+        Returns
+        -------
+        None
+
+        See Also
+        --------
+        TODO link to documentation on noise model
+        """
+        self.sampling_rate = sampling_rate
+        self.resolution = resolution
+        self.operating_temperature = operating_temperature
+        self.noise_density = noise_density
+        self.noise_variance = noise_variance
+        self.random_walk_density = random_walk_density
+        self.random_walk_variance = random_walk_variance
+        self.constant_bias = constant_bias
+        self.temperature_bias = temperature_bias
+        self.temperature_scale_factor = temperature_scale_factor
+        self.name = name
+        self.measurement = None
+        self.measured_data = []
+        self._counter = 0
+        self._save_data = self._save_data_single
+        self._random_walk_drift = 0
+        self.normal_vector = Vector([0, 0, 0])
+
+        # handle measurement range
+        if isinstance(measurement_range, (tuple, list)):
+            if len(measurement_range) != 2:
+                raise ValueError("Invalid measurement range format")
+            self.measurement_range = measurement_range
+        elif isinstance(measurement_range, (int, float)):
+            self.measurement_range = (-measurement_range, measurement_range)
+        else:
+            raise ValueError("Invalid measurement range format")
+
+        # map which rocket(s) the sensor is attached to and how many times
+        self._attached_rockets = {}
+
+    def __repr__(self):
+        return f"{self.name}"
+
+    def __call__(self, *args, **kwargs):
+        return self.measure(*args, **kwargs)
+
+    def _reset(self, simulated_rocket):
+        """Reset the sensor data for a new simulation."""
+        self._random_walk_drift = (
+            Vector([0, 0, 0]) if isinstance(self._random_walk_drift, Vector) else 0
+        )
+        self.measured_data = []
+        if self._attached_rockets[simulated_rocket] > 1:
+            self.measured_data = [
+                [] for _ in range(self._attached_rockets[simulated_rocket])
+            ]
+            self._save_data = self._save_data_multiple
+        else:
+            self._save_data = self._save_data_single
+
+    def _save_data_single(self, data):
+        """Save the measured data to the sensor data list for a sensor that is
+        added only once to the simulated rocket."""
+        self.measured_data.append(data)
+
+    def _save_data_multiple(self, data):
+        """Save the measured data to the sensor data list for a sensor that is
+        added multiple times to the simulated rocket."""
+        self.measured_data[self._counter].append(data)
+        # counter for cases where the sensor is added multiple times in a rocket
+        self._counter += 1
+        if self._counter == len(self.measured_data):
+            self._counter = 0
+
+    @abstractmethod
+    def measure(self, time, **kwargs):
+        pass
+
+    @abstractmethod
+    def export_measured_data(self):
+        pass
+
+    @abstractmethod
+    def quantize(self, value):
+        """Quantize the sensor measurement"""
+        pass
+
+    @abstractmethod
+    def apply_noise(self, value):
+        """Add noise to the sensor measurement"""
+        pass
+
+    @abstractmethod
+    def apply_temperature_drift(self, value):
+        """Apply temperature drift to the sensor measurement"""
+        pass
+
+
+class InertialSensors(Sensors):
+    """Abstract class for sensors
+
     Attributes
     ----------
     type : str
@@ -45,8 +261,6 @@ class Sensors(ABC):
         frame of reference.
     normal_vector : Vector
         The normal vector of the sensor in the rocket frame of reference.
-    _random_walk_drift : Vector
-        The random walk drift of the sensor in sensor units.
     measurement : float
         The measurement of the sensor after quantization, noise and temperature
         drift.
@@ -165,42 +379,32 @@ def __init__(
         --------
         TODO link to documentation on noise model
         """
-        self.sampling_rate = sampling_rate
-        self.orientation = orientation
-        self.resolution = resolution
-        self.operating_temperature = operating_temperature
-        self.noise_density = self._vectorize_input(noise_density, "noise_density")
-        self.noise_variance = self._vectorize_input(noise_variance, "noise_variance")
-        self.random_walk_density = self._vectorize_input(
-            random_walk_density, "random_walk_density"
-        )
-        self.random_walk_variance = self._vectorize_input(
-            random_walk_variance, "random_walk_variance"
-        )
-        self.constant_bias = self._vectorize_input(constant_bias, "constant_bias")
-        self.temperature_bias = self._vectorize_input(
-            temperature_bias, "temperature_bias"
-        )
-        self.temperature_scale_factor = self._vectorize_input(
-            temperature_scale_factor, "temperature_scale_factor"
+        super().__init__(
+            sampling_rate=sampling_rate,
+            measurement_range=measurement_range,
+            resolution=resolution,
+            noise_density=self._vectorize_input(noise_density, "noise_density"),
+            noise_variance=self._vectorize_input(noise_variance, "noise_variance"),
+            random_walk_density=self._vectorize_input(
+                random_walk_density, "random_walk_density"
+            ),
+            random_walk_variance=self._vectorize_input(
+                random_walk_variance, "random_walk_variance"
+            ),
+            constant_bias=self._vectorize_input(constant_bias, "constant_bias"),
+            operating_temperature=operating_temperature,
+            temperature_bias=self._vectorize_input(
+                temperature_bias, "temperature_bias"
+            ),
+            temperature_scale_factor=self._vectorize_input(
+                temperature_scale_factor, "temperature_scale_factor"
+            ),
+            name=name,
         )
+
+        self.orientation = orientation
         self.cross_axis_sensitivity = cross_axis_sensitivity
-        self.name = name
         self._random_walk_drift = Vector([0, 0, 0])
-        self.measurement = None
-        self.measured_data = []
-        self._counter = 0
-        self._save_data = self._save_data_single
-
-        # handle measurement range
-        if isinstance(measurement_range, (tuple, list)):
-            if len(measurement_range) != 2:
-                raise ValueError("Invalid measurement range format")
-            self.measurement_range = measurement_range
-        elif isinstance(measurement_range, (int, float)):
-            self.measurement_range = (-measurement_range, measurement_range)
-        else:
-            raise ValueError("Invalid measurement range format")
 
         # rotation matrix and normal vector
         if any(isinstance(row, (tuple, list)) for row in orientation):  # matrix
@@ -229,15 +433,6 @@ def __init__(
         # compute total rotation matrix given cross axis sensitivity
         self._total_rotation_matrix = self.rotation_matrix @ _cross_axis_matrix
 
-        # map which rocket(s) the sensor is attached to and how many times
-        self._attached_rockets = {}
-
-    def __repr__(self):
-        return f"{self.name}"
-
-    def __call__(self, *args, **kwargs):
-        return self.measure(*args, **kwargs)
-
     def _vectorize_input(self, value, name):
         if isinstance(value, (int, float)):
             return Vector([value, value, value])
@@ -246,40 +441,6 @@ def _vectorize_input(self, value, name):
         else:
             raise ValueError(f"Invalid {name} format")
 
-    def _reset(self, simulated_rocket):
-        """Reset the sensor data for a new simulation."""
-        self._random_walk_drift = Vector([0, 0, 0])
-        self.measured_data = []
-        if self._attached_rockets[simulated_rocket] > 1:
-            self.measured_data = [
-                [] for _ in range(self._attached_rockets[simulated_rocket])
-            ]
-            self._save_data = self._save_data_multiple
-        else:
-            self._save_data = self._save_data_single
-
-    def _save_data_single(self, data):
-        """Save the measured data to the sensor data list for a sensor that is
-        added only once to the simulated rocket."""
-        self.measured_data.append(data)
-
-    def _save_data_multiple(self, data):
-        """Save the measured data to the sensor data list for a sensor that is
-        added multiple times to the simulated rocket."""
-        self.measured_data[self._counter].append(data)
-        # counter for cases where the sensor is added multiple times in a rocket
-        self._counter += 1
-        if self._counter == len(self.measured_data):
-            self._counter = 0
-
-    @abstractmethod
-    def measure(self, *args, **kwargs):
-        pass
-
-    @abstractmethod
-    def export_measured_data(self):
-        pass
-
     def quantize(self, value):
         """
         Quantize the sensor measurement
@@ -303,6 +464,222 @@ def quantize(self, value):
             z = round(z / self.resolution) * self.resolution
         return Vector([x, y, z])
 
+    def apply_noise(self, value):
+        """
+        Add noise to the sensor measurement
+
+        Parameters
+        ----------
+        value : float
+            The value to add noise to
+
+        Returns
+        -------
+        float
+            The value with added noise
+        """
+        # white noise
+        white_noise = Vector(
+            [np.random.normal(0, self.noise_variance[i] ** 0.5) for i in range(3)]
+        ) & (self.noise_density * self.sampling_rate**0.5)
+
+        # random walk
+        self._random_walk_drift = self._random_walk_drift + Vector(
+            [np.random.normal(0, self.random_walk_variance[i] ** 0.5) for i in range(3)]
+        ) & (self.random_walk_density / self.sampling_rate**0.5)
+
+        # add noise
+        value += white_noise + self._random_walk_drift + self.constant_bias
+
+        return value
+
+    def apply_temperature_drift(self, value):
+        """
+        Apply temperature drift to the sensor measurement
+
+        Parameters
+        ----------
+        value : float
+            The value to apply temperature drift to
+
+        Returns
+        -------
+        float
+            The value with applied temperature drift
+        """
+        # temperature drift
+        value += (self.operating_temperature - 25) * self.temperature_bias
+        # temperature scale factor
+        scale_factor = (
+            Vector([1, 1, 1])
+            + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
+        )
+        value = value & scale_factor
+
+        return value
+
+
+class ScalarSensors(Sensors):
+    """Abstract class for sensors
+
+    Attributes
+    ----------
+    type : str
+        Type of the sensor (e.g. Barometer, GPS).
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    measurement_range : float, tuple
+        The measurement range of the sensor in the sensor units.
+    resolution : float
+        The resolution of the sensor in sensor units/LSB.
+    noise_density : float
+        The noise density of the sensor in sensor units/√Hz.
+    noise_variance : float
+        The variance of the noise of the sensor in sensor units^2.
+    random_walk_density : float
+        The random walk density of the sensor in sensor units/√Hz.
+    random_walk_variance : float
+        The variance of the random walk of the sensor in sensor units^2.
+    constant_bias : float
+        The constant bias of the sensor in sensor units.
+    operating_temperature : float
+        The operating temperature of the sensor in degrees Celsius.
+    temperature_bias : float
+        The temperature bias of the sensor in sensor units/°C.
+    temperature_scale_factor : float
+        The temperature scale factor of the sensor in %/°C.
+    name : str
+        The name of the sensor.
+    measurement : float
+        The measurement of the sensor after quantization, noise and temperature
+        drift.
+    measured_data : list
+        The stored measured data of the sensor after quantization, noise and
+        temperature drift.
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        measurement_range=np.inf,
+        resolution=0,
+        noise_density=0,
+        noise_variance=1,
+        random_walk_density=0,
+        random_walk_variance=1,
+        constant_bias=0,
+        operating_temperature=25,
+        temperature_bias=0,
+        temperature_scale_factor=0,
+        name="Sensor",
+    ):
+        """
+        Initialize the accelerometer sensor
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor
+        measurement_range : float, tuple, optional
+            The measurement range of the sensor in the sensor units. If a float,
+            the same range is applied both for positive and negative values. If
+            a tuple, the first value is the positive range and the second value
+            is the negative range. Default is np.inf.
+        resolution : float, optional
+            The resolution of the sensor in sensor units/LSB. Default is 0,
+            meaning no quantization is applied.
+        noise_density : float, list, optional
+            The noise density of the sensor for a Gaussian white noise in sensor
+            units/√Hz. Sometimes called "white noise drift",
+            "angular random walk" for gyroscopes, "velocity random walk" for
+            accelerometers or "(rate) noise density". Default is 0, meaning no
+            noise is applied. If a float or int is given, the same noise density
+            is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        noise_variance : float, list, optional
+            The noise variance of the sensor for a Gaussian white noise in
+            sensor units^2. Default is 1, meaning the noise is normally
+            distributed with a standard deviation of 1 unit. If a float or int
+            is given, the same noise variance is applied to all axes. The values
+            of each axis can be set individually by passing a list of length 3.
+        random_walk_density : float, list, optional
+            The random walk density of the sensor for a Gaussian random walk in
+            sensor units/√Hz. Sometimes called "bias (in)stability" or
+            "bias drift". Default is 0, meaning no random walk is applied.
+            If a float or int is given, the same random walk is applied to all
+            axes. The values of each axis can be set individually by passing a
+            list of length 3.
+        random_walk_variance : float, list, optional
+            The random walk variance of the sensor for a Gaussian random walk in
+            sensor units^2. Default is 1, meaning the noise is normally
+            distributed with a standard deviation of 1 unit. If a float or int
+            is given, the same random walk variance is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
+        constant_bias : float, list, optional
+            The constant bias of the sensor in sensor units. Default is 0,
+            meaning no constant bias is applied. If a float or int is given, the
+            same constant bias is applied to all axes. The values of each axis
+            can be set individually by passing a list of length 3.
+        operating_temperature : float, optional
+            The operating temperature of the sensor in degrees Celsius. At 25°C,
+            the temperature bias and scale factor are 0. Default is 25.
+        temperature_bias : float, list, optional
+            The temperature bias of the sensor in sensor units/°C. Default is 0,
+            meaning no temperature bias is applied. If a float or int is given,
+            the same temperature bias is applied to all axes. The values of each
+            axis can be set individually by passing a list of length 3.
+        temperature_scale_factor : float, list, optional
+            The temperature scale factor of the sensor in %/°C. Default is 0,
+            meaning no temperature scale factor is applied. If a float or int is
+            given, the same temperature scale factor is applied to all axes. The
+            values of each axis can be set individually by passing a list of
+            length 3.
+        name : str, optional
+            The name of the sensor. Default is "Sensor".
+
+        Returns
+        -------
+        None
+
+        See Also
+        --------
+        TODO link to documentation on noise model
+        """
+        super().__init__(
+            sampling_rate=sampling_rate,
+            measurement_range=measurement_range,
+            resolution=resolution,
+            noise_density=noise_density,
+            noise_variance=noise_variance,
+            random_walk_density=random_walk_density,
+            random_walk_variance=random_walk_variance,
+            constant_bias=constant_bias,
+            operating_temperature=operating_temperature,
+            temperature_bias=temperature_bias,
+            temperature_scale_factor=temperature_scale_factor,
+            name=name,
+        )
+
+    def quantize(self, value):
+        """
+        Quantize the sensor measurement
+
+        Parameters
+        ----------
+        value : float
+            The value to quantize
+
+        Returns
+        -------
+        float
+            The quantized value
+        """
+        value = min(max(value, self.measurement_range[0]), self.measurement_range[1])
+        if self.resolution != 0:
+            value = round(value / self.resolution) * self.resolution
+        return value
+
     def apply_noise(self, value):
         """
         Add noise to the sensor measurement
@@ -319,24 +696,16 @@ def apply_noise(self, value):
         """
         # white noise
         white_noise = (
-            Vector(
-                [np.random.normal(0, self.noise_variance[i] ** 0.5) for i in range(3)]
-            )
-            & self.noise_density
-        ) * self.sampling_rate**0.5
+            np.random.normal(0, self.noise_variance**0.5)
+            * self.noise_density
+            * self.sampling_rate**0.5
+        )
 
         # random walk
         self._random_walk_drift = (
             self._random_walk_drift
-            + (
-                Vector(
-                    [
-                        np.random.normal(0, self.random_walk_variance[i] ** 0.5)
-                        for i in range(3)
-                    ]
-                )
-                & self.random_walk_density
-            )
+            + np.random.normal(0, self.random_walk_variance**0.5)
+            * self.random_walk_density
             / self.sampling_rate**0.5
         )
 
@@ -363,9 +732,8 @@ def apply_temperature_drift(self, value):
         value += (self.operating_temperature - 25) * self.temperature_bias
         # temperature scale factor
         scale_factor = (
-            Vector([1, 1, 1])
-            + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
+            1 + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
         )
-        value = value & scale_factor
+        value = value * scale_factor
 
         return value

From 6c4229d274e77605991f9ca0984404f88de4dcc5 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sat, 4 May 2024 00:02:15 +0200
Subject: [PATCH 044/120] ENH: add Barometer class

---
 rocketpy/__init__.py          |   2 +-
 rocketpy/sensors/__init__.py  |   3 +-
 rocketpy/sensors/barometer.py | 183 ++++++++++++++++++++++++++++++++++
 3 files changed, 186 insertions(+), 2 deletions(-)
 create mode 100644 rocketpy/sensors/barometer.py

diff --git a/rocketpy/__init__.py b/rocketpy/__init__.py
index fe55dda41..1e0c0bef5 100644
--- a/rocketpy/__init__.py
+++ b/rocketpy/__init__.py
@@ -37,5 +37,5 @@
     Tail,
     TrapezoidalFins,
 )
-from .sensors import Accelerometer, Gyroscope, Sensors
+from .sensors import Accelerometer, Gyroscope, Barometer
 from .simulation import Flight
diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 5bfe07805..754a3f704 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1,3 +1,4 @@
 from .accelerometer import Accelerometer
 from .gyroscope import Gyroscope
-from .sensors import Sensors
+from .sensors import Sensors, InertialSensors, ScalarSensors
+from .barometer import Barometer
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
new file mode 100644
index 000000000..3a98154c4
--- /dev/null
+++ b/rocketpy/sensors/barometer.py
@@ -0,0 +1,183 @@
+import json
+
+import numpy as np
+
+from ..mathutils.vector_matrix import Matrix, Vector
+from ..prints.sensors_prints import _BarometerPrints
+from ..sensors.sensors import ScalarSensors
+
+
+class Barometer(ScalarSensors):
+    """Class for the barometer sensor
+
+    Attributes
+    ----------
+    type : str
+        Type of the sensor, in this case "Barometer".
+    prints : _BarometerPrints
+        Object that contains the print functions for the sensor.
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    orientation : tuple, list
+        Orientation of the sensor in the rocket.
+    measurement_range : float, tuple
+        The measurement range of the sensor in Pa.
+    resolution : float
+        The resolution of the sensor in Pa/LSB.
+    noise_density : float
+        The noise density of the sensor in Pa/√Hz.
+    noise_variance : float
+        The variance of the noise of the sensor in Pa^2.
+    random_walk_density : float
+        The random walk density of the sensor in Pa/√Hz.
+    random_walk_variance : float
+        The variance of the random walk of the sensor in Pa^2.
+    constant_bias : float
+        The constant bias of the sensor in Pa.
+    operating_temperature : float
+        The operating temperature of the sensor in degrees Celsius.
+    temperature_bias : float
+        The temperature bias of the sensor in Pa/°C.
+    temperature_scale_factor : float
+        The temperature scale factor of the sensor in %/°C.
+    name : str
+        The name of the sensor.
+    measurement : float
+        The measurement of the sensor after quantization, noise and temperature
+        drift.
+    measured_data : list
+        The stored measured data of the sensor after quantization, noise and
+        temperature drift.
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        measurement_range=np.inf,
+        resolution=0,
+        noise_density=0,
+        noise_variance=1,
+        random_walk_density=0,
+        random_walk_variance=1,
+        constant_bias=0,
+        operating_temperature=25,
+        temperature_bias=0,
+        temperature_scale_factor=0,
+        name="Barometer",
+    ):
+        """
+        Initialize the barometer sensor
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor in Hz.
+        measurement_range : float, tuple, optional
+            The measurement range of the sensor in the Pa. If a float, the same
+            range is applied both for positive and negative values. If a tuple,
+            the first value is the positive range and the second value is the
+            negative range. Default is np.inf.
+        resolution : float, optional
+            The resolution of the sensor in Pa/LSB. Default is 0, meaning no
+            quantization is applied.
+        noise_density : float, optional
+            The noise density of the sensor for a Gaussian white noise in Pa/√Hz.
+            Sometimes called "white noise drift", "angular random walk" for
+            gyroscopes, "velocity random walk" for accelerometers or
+            "(rate) noise density". Default is 0, meaning no noise is applied.
+        noise_variance : float, optional
+            The noise variance of the sensor for a Gaussian white noise in Pa^2.
+            Default is 1, meaning the noise is normally distributed with a
+            standard deviation of 1 Pa. If a float or int is given, the same
+            variance is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        random_walk_density : float, optional
+            The random walk of the sensor for a Gaussian random walk in Pa/√Hz.
+            Sometimes called "bias (in)stability" or "bias drift"". Default is 0,
+            meaning no random walk is applied.
+        random_walk_variance : float, optional
+            The random walk variance of the sensor for a Gaussian random walk in
+            Pa^2. Default is 1, meaning the noise is normally distributed with a
+            standard deviation of 1 Pa. If a float or int is given, the same
+            variance is applied to all axes. The values of each axis can be set
+            individually by passing a list of length 3.
+        constant_bias : float, optional
+            The constant bias of the sensor in Pa. Default is 0, meaning no
+            constant bias is applied.
+        operating_temperature : float, optional
+            The operating temperature of the sensor in degrees Celsius. At 25°C,
+            the temperature bias and scale factor are 0. Default is 25.
+        temperature_bias : float, optional
+            The temperature bias of the sensor in Pa/°C. Default is 0, meaning no
+            temperature bias is applied.
+        temperature_scale_factor : float, optional
+            The temperature scale factor of the sensor in %/°C. Default is 0,
+            meaning no temperature scale factor is applied.
+        name : str, optional
+            The name of the sensor. Default is "Barometer".
+
+        Returns
+        -------
+        None
+
+        See Also
+        --------
+        TODO link to documentation on noise model
+        """
+        super().__init__(
+            sampling_rate=sampling_rate,
+            measurement_range=measurement_range,
+            resolution=resolution,
+            noise_density=noise_density,
+            noise_variance=noise_variance,
+            random_walk_density=random_walk_density,
+            random_walk_variance=random_walk_variance,
+            constant_bias=constant_bias,
+            operating_temperature=operating_temperature,
+            temperature_bias=temperature_bias,
+            temperature_scale_factor=temperature_scale_factor,
+            name=name,
+        )
+        self.type = "Barometer"
+        self.prints = _BarometerPrints(self)
+
+    def measure(self, time, **kwargs):
+        """Measures the pressure at barometer location
+
+        Parameters
+        ----------
+        time : float
+            Current time in seconds.
+        kwargs : dict
+            Keyword arguments dictionary containing the following keys:
+            - u : np.array
+                State vector of the rocket.
+            - u_dot : np.array
+                Derivative of the state vector of the rocket.
+            - relative_position : np.array
+                Position of the sensor relative to the rocket center of mass.
+            - gravity : float
+                Gravitational acceleration in m/s^2.
+            - pressure : Function
+                Atmospheric pressure profile as a function of altitude in Pa.
+            - elevation : float
+                Elevation of the launch site in meters.
+        """
+        u = kwargs["u"]
+        relative_position = kwargs["relative_position"]
+        pressure = kwargs["pressure"]
+
+        # Calculate the altitude of the sensor
+        relative_altitude = (Matrix.transformation(u[6:10]) @ relative_position).z
+
+        # Calculate the pressure at the sensor location and add noise
+        P = pressure(relative_altitude + u[2])
+        P = self.apply_noise(P)
+        P = self.apply_temperature_drift(P)
+        P = self.quantize(P)
+
+        self.measurement = P
+        self.measured_data.append((time, P))
+
+    def export_measured_data(self):
+        pass

From 99959048785016415e0b2c3081ca333d6c8a1e6c Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sat, 4 May 2024 00:02:35 +0200
Subject: [PATCH 045/120] BUG: fix drawing for scalar sensors

---
 rocketpy/plots/rocket_plots.py | 31 ++++++++++++++++---------------
 1 file changed, 16 insertions(+), 15 deletions(-)

diff --git a/rocketpy/plots/rocket_plots.py b/rocketpy/plots/rocket_plots.py
index 0d7b5b130..e57fe87e4 100644
--- a/rocketpy/plots/rocket_plots.py
+++ b/rocketpy/plots/rocket_plots.py
@@ -218,7 +218,7 @@ def draw(self, vis_args=None, plane="xz"):
         self._draw_motor(last_radius, last_x, ax, vis_args)
         self._draw_rail_buttons(ax, vis_args)
         self._draw_center_of_mass_and_pressure(ax)
-        self._draw_sensor(ax, self.rocket.sensors, plane, vis_args)
+        self._draw_sensors(ax, self.rocket.sensors, plane, vis_args)
 
         plt.title("Rocket Representation")
         plt.xlim()
@@ -555,7 +555,7 @@ def _draw_center_of_mass_and_pressure(self, ax):
             cp, 0, label="Static Center of Pressure", color="red", s=10, zorder=10
         )
 
-    def _draw_sensor(self, ax, sensors, plane, vis_args):
+    def _draw_sensors(self, ax, sensors, plane, vis_args):
         """Draw the sensor as a small thick line at the position of the sensor,
         with a vector pointing in the direction normal of the sensor. Get the
         normal vector from the sensor orientation matrix."""
@@ -591,19 +591,20 @@ def _draw_sensor(self, ax, sensors, plane, vis_args):
                 zorder=10,
                 label=sensor.name,
             )
-            ax.quiver(
-                x_pos,
-                y_pos,
-                normal_x,
-                normal_y,
-                color=colors[(i + 1) % len(colors)],
-                scale_units="xy",
-                angles="xy",
-                minshaft=2,
-                headwidth=2,
-                headlength=4,
-                zorder=10,
-            )
+            if abs(sensor.normal_vector) != 0:
+                ax.quiver(
+                    x_pos,
+                    y_pos,
+                    normal_x,
+                    normal_y,
+                    color=colors[(i + 1) % len(colors)],
+                    scale_units="xy",
+                    angles="xy",
+                    minshaft=2,
+                    headwidth=2,
+                    headlength=4,
+                    zorder=10,
+                )
 
     def all(self):
         """Prints out all graphs available about the Rocket. It simply calls

From 354e681eaee2841fdbf2af25afffb7785e17004a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sat, 4 May 2024 00:02:57 +0200
Subject: [PATCH 046/120] ENH: barometer prints

---
 rocketpy/prints/sensors_prints.py | 43 ++++++++++++++++++++++++-------
 1 file changed, 34 insertions(+), 9 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 95e3458c0..731fc3fcc 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -4,7 +4,7 @@
     "Gyroscope": "rad/s",
     "Accelerometer": "m/s^2",
     "Magnetometer": "T",
-    "PressureSensor": "Pa",
+    "Barometer": "Pa",
     "TemperatureSensor": "K",
 }
 
@@ -44,10 +44,9 @@ def quantization(self):
         )
         self._print_aligned("Resolution:", f"{self.sensor.resolution} {self.units}/LSB")
 
-    @abstractmethod
     def noise(self):
         """Prints the noise of the sensor."""
-        pass
+        self._general_noise()
 
     def _general_noise(self):
         """Prints the noise of the sensor."""
@@ -82,6 +81,28 @@ def _general_noise(self):
             "Cross Axis Sensitivity:", f"{self.sensor.cross_axis_sensitivity} %"
         )
 
+    def all(self):
+        """Prints all information of the sensor."""
+        self.identity()
+        self.quantization()
+        self.noise()
+
+
+class _InertialSensorsPrints(_SensorsPrints):
+    def __init__(self, sensor):
+        super().__init__(sensor)
+
+    def orientation(self):
+        """Prints the orientation of the sensor."""
+        print("\nOrientation of the Sensor:\n")
+        self._print_aligned("Orientation:", self.sensor.orientation)
+        self._print_aligned("Normal Vector:", self.sensor.normal_vector)
+        print("Rotation Matrix:")
+        for row in self.sensor.rotation_matrix:
+            value = " ".join(f"{val:.2f}" for val in row)
+            value = [float(val) for val in value.split()]
+            self._print_aligned("", value)
+
     def all(self):
         """Prints all information of the sensor."""
         self.identity()
@@ -90,19 +111,15 @@ def all(self):
         self.noise()
 
 
-class _AccelerometerPrints(_SensorsPrints):
+class _AccelerometerPrints(_InertialSensorsPrints):
     """Class that contains all accelerometer prints."""
 
     def __init__(self, accelerometer):
         """Initialize the class."""
         super().__init__(accelerometer)
 
-    def noise(self):
-        """Prints the noise of the sensor."""
-        self._general_noise()
-
 
-class _GyroscopePrints(_SensorsPrints):
+class _GyroscopePrints(_InertialSensorsPrints):
     """Class that contains all gyroscope prints."""
 
     def __init__(self, gyroscope):
@@ -116,3 +133,11 @@ def noise(self):
             "Acceleration Sensitivity:",
             f"{self.sensor.acceleration_sensitivity} rad/s/g",
         )
+
+
+class _BarometerPrints(_SensorsPrints):
+    """Class that contains all barometer prints."""
+
+    def __init__(self, barometer):
+        """Initialize the class."""
+        super().__init__(barometer)

From 1f761c020e9aed1003c6082779bf2e58ba2a7b6e Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sat, 4 May 2024 14:12:50 +0200
Subject: [PATCH 047/120] DOC: change docs for scalar sensors

---
 rocketpy/sensors/barometer.py | 10 ++----
 rocketpy/sensors/sensors.py   | 58 ++++++++---------------------------
 2 files changed, 15 insertions(+), 53 deletions(-)

diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 3a98154c4..c24d6b508 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from ..mathutils.vector_matrix import Matrix, Vector
+from ..mathutils.vector_matrix import Matrix
 from ..prints.sensors_prints import _BarometerPrints
 from ..sensors.sensors import ScalarSensors
 
@@ -88,9 +88,7 @@ def __init__(
         noise_variance : float, optional
             The noise variance of the sensor for a Gaussian white noise in Pa^2.
             Default is 1, meaning the noise is normally distributed with a
-            standard deviation of 1 Pa. If a float or int is given, the same
-            variance is applied to all axes. The values of each axis can be set
-            individually by passing a list of length 3.
+            standard deviation of 1 Pa.
         random_walk_density : float, optional
             The random walk of the sensor for a Gaussian random walk in Pa/√Hz.
             Sometimes called "bias (in)stability" or "bias drift"". Default is 0,
@@ -98,9 +96,7 @@ def __init__(
         random_walk_variance : float, optional
             The random walk variance of the sensor for a Gaussian random walk in
             Pa^2. Default is 1, meaning the noise is normally distributed with a
-            standard deviation of 1 Pa. If a float or int is given, the same
-            variance is applied to all axes. The values of each axis can be set
-            individually by passing a list of length 3.
+            standard deviation of 1 Pa.
         constant_bias : float, optional
             The constant bias of the sensor in Pa. Default is 0, meaning no
             constant bias is applied.
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 24dd01b8a..aecaf4e48 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -79,48 +79,31 @@ def __init__(
             units/√Hz. Sometimes called "white noise drift",
             "angular random walk" for gyroscopes, "velocity random walk" for
             accelerometers or "(rate) noise density". Default is 0, meaning no
-            noise is applied. If a float or int is given, the same noise density
-            is applied to all axes. The values of each axis can be set
-            individually by passing a list of length 3.
+            noise is applied.
         noise_variance : float, list, optional
             The noise variance of the sensor for a Gaussian white noise in
             sensor units^2. Default is 1, meaning the noise is normally
-            distributed with a standard deviation of 1 unit. If a float or int
-            is given, the same noise variance is applied to all axes. The values
-            of each axis can be set individually by passing a list of length 3.
+            distributed with a standard deviation of 1 unit.
         random_walk_density : float, list, optional
             The random walk density of the sensor for a Gaussian random walk in
             sensor units/√Hz. Sometimes called "bias (in)stability" or
             "bias drift". Default is 0, meaning no random walk is applied.
-            If a float or int is given, the same random walk is applied to all
-            axes. The values of each axis can be set individually by passing a
-            list of length 3.
         random_walk_variance : float, list, optional
             The random walk variance of the sensor for a Gaussian random walk in
             sensor units^2. Default is 1, meaning the noise is normally
-            distributed with a standard deviation of 1 unit. If a float or int
-            is given, the same random walk variance is applied to all axes. The
-            values of each axis can be set individually by passing a list of
-            length 3.
+            distributed with a standard deviation of 1 unit.
         constant_bias : float, list, optional
             The constant bias of the sensor in sensor units. Default is 0,
-            meaning no constant bias is applied. If a float or int is given, the
-            same constant bias is applied to all axes. The values of each axis
-            can be set individually by passing a list of length 3.
+            meaning no constant bias is applied.
         operating_temperature : float, optional
             The operating temperature of the sensor in degrees Celsius. At 25°C,
             the temperature bias and scale factor are 0. Default is 25.
         temperature_bias : float, list, optional
             The temperature bias of the sensor in sensor units/°C. Default is 0,
-            meaning no temperature bias is applied. If a float or int is given,
-            the same temperature bias is applied to all axes. The values of each
-            axis can be set individually by passing a list of length 3.
+            meaning no temperature bias is applied.
         temperature_scale_factor : float, list, optional
             The temperature scale factor of the sensor in %/°C. Default is 0,
-            meaning no temperature scale factor is applied. If a float or int is
-            given, the same temperature scale factor is applied to all axes. The
-            values of each axis can be set individually by passing a list of
-            length 3.
+            meaning no temperature scale factor is applied.
         name : str, optional
             The name of the sensor. Default is "Sensor".
 
@@ -593,48 +576,31 @@ def __init__(
             units/√Hz. Sometimes called "white noise drift",
             "angular random walk" for gyroscopes, "velocity random walk" for
             accelerometers or "(rate) noise density". Default is 0, meaning no
-            noise is applied. If a float or int is given, the same noise density
-            is applied to all axes. The values of each axis can be set
-            individually by passing a list of length 3.
+            noise is applied.
         noise_variance : float, list, optional
             The noise variance of the sensor for a Gaussian white noise in
             sensor units^2. Default is 1, meaning the noise is normally
-            distributed with a standard deviation of 1 unit. If a float or int
-            is given, the same noise variance is applied to all axes. The values
-            of each axis can be set individually by passing a list of length 3.
+            distributed with a standard deviation of 1 unit.
         random_walk_density : float, list, optional
             The random walk density of the sensor for a Gaussian random walk in
             sensor units/√Hz. Sometimes called "bias (in)stability" or
             "bias drift". Default is 0, meaning no random walk is applied.
-            If a float or int is given, the same random walk is applied to all
-            axes. The values of each axis can be set individually by passing a
-            list of length 3.
         random_walk_variance : float, list, optional
             The random walk variance of the sensor for a Gaussian random walk in
             sensor units^2. Default is 1, meaning the noise is normally
-            distributed with a standard deviation of 1 unit. If a float or int
-            is given, the same random walk variance is applied to all axes. The
-            values of each axis can be set individually by passing a list of
-            length 3.
+            distributed with a standard deviation of 1 unit.
         constant_bias : float, list, optional
             The constant bias of the sensor in sensor units. Default is 0,
-            meaning no constant bias is applied. If a float or int is given, the
-            same constant bias is applied to all axes. The values of each axis
-            can be set individually by passing a list of length 3.
+            meaning no constant bias is applied.
         operating_temperature : float, optional
             The operating temperature of the sensor in degrees Celsius. At 25°C,
             the temperature bias and scale factor are 0. Default is 25.
         temperature_bias : float, list, optional
             The temperature bias of the sensor in sensor units/°C. Default is 0,
-            meaning no temperature bias is applied. If a float or int is given,
-            the same temperature bias is applied to all axes. The values of each
-            axis can be set individually by passing a list of length 3.
+            meaning no temperature bias is applied.
         temperature_scale_factor : float, list, optional
             The temperature scale factor of the sensor in %/°C. Default is 0,
-            meaning no temperature scale factor is applied. If a float or int is
-            given, the same temperature scale factor is applied to all axes. The
-            values of each axis can be set individually by passing a list of
-            length 3.
+            meaning no temperature scale factor is applied.
         name : str, optional
             The name of the sensor. Default is "Sensor".
 

From 17feded08ee383ed8bc4c176a90b4ffdc9b0265b Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sun, 5 May 2024 16:08:04 +0200
Subject: [PATCH 048/120] ENH: add barometer export data

---
 rocketpy/sensors/accelerometer.py |  3 +-
 rocketpy/sensors/barometer.py     | 54 +++++++++++++++++++++++++++++--
 rocketpy/sensors/gyroscope.py     |  3 +-
 3 files changed, 54 insertions(+), 6 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 7e332eebf..bdd4f8bee 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -254,8 +254,7 @@ def measure(self, time, **kwargs):
         self._save_data((time, *A))
 
     def export_measured_data(self, filename, format="csv"):
-        """
-        Export the measured values to a file
+        """Export the measured values to a file
 
         Parameters
         ----------
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index c24d6b508..7bbc8c02a 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -175,5 +175,55 @@ def measure(self, time, **kwargs):
         self.measurement = P
         self.measured_data.append((time, P))
 
-    def export_measured_data(self):
-        pass
+    def export_measured_data(self, filename, format="csv"):
+        """Export the measured values to a file
+
+        Parameters
+        ----------
+        filename : str
+            Name of the file to export the values to
+        format : str
+            Format of the file to export the values to. Options are "csv" and
+            "json". Default is "csv".
+
+        Returns
+        -------
+        None
+        """
+        if format == "csv":
+            # if sensor has been added multiple times to the simulated rocket
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    with open(filename + f"_{i+1}", "w") as f:
+                        f.write("t,pressure\n")
+                        for t, pressure in data:
+                            f.write(f"{t},{pressure}\n")
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                with open(filename, "w") as f:
+                    f.write("t,pressure\n")
+                    for t, pressure in self.measured_data:
+                        f.write(f"{t},{pressure}\n")
+                print(f"Data saved to {filename}")
+        elif format == "json":
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    dict = {"t": [], "pressure": []}
+                    for t, pressure in data:
+                        dict["t"].append(t)
+                        dict["pressure"].append(pressure)
+                    with open(filename + f"_{i+1}", "w") as f:
+                        json.dump(dict, f)
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                dict = {"t": [], "pressure": []}
+                for t, pressure in self.measured_data:
+                    dict["t"].append(t)
+                    dict["pressure"].append(pressure)
+                with open(filename, "w") as f:
+                    json.dump(dict, f)
+                print(f"Data saved to {filename}")
+        else:
+            raise ValueError("Invalid format")
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index bdfb36a05..91f78b7eb 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -286,8 +286,7 @@ def apply_acceleration_sensitivity(
         return self.acceleration_sensitivity & A
 
     def export_measured_data(self, filename, format="csv"):
-        """
-        Export the measured values to a file
+        """Export the measured values to a file
 
         Parameters
         ----------

From faf098ac3ca493fbf369862f3c2d73c4ca909a97 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sun, 5 May 2024 16:08:25 +0200
Subject: [PATCH 049/120] BUG: fix scalars sensors prints

---
 rocketpy/prints/sensors_prints.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 731fc3fcc..fe636a53b 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -77,9 +77,6 @@ def _general_noise(self):
         self._print_aligned(
             "Temperature Scale Factor:", f"{self.sensor.temperature_scale_factor} %/°C"
         )
-        self._print_aligned(
-            "Cross Axis Sensitivity:", f"{self.sensor.cross_axis_sensitivity} %"
-        )
 
     def all(self):
         """Prints all information of the sensor."""
@@ -103,6 +100,12 @@ def orientation(self):
             value = [float(val) for val in value.split()]
             self._print_aligned("", value)
 
+    def _general_noise(self):
+        super()._general_noise()
+        self._print_aligned(
+            "Cross Axis Sensitivity:", f"{self.sensor.cross_axis_sensitivity} %"
+        )
+
     def all(self):
         """Prints all information of the sensor."""
         self.identity()

From 960b1c3d2d9b1bcfe567d74844abdc88c02dc033 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sun, 5 May 2024 16:08:45 +0200
Subject: [PATCH 050/120] TST: add barometers to tests

---
 tests/fixtures/flight/flight_fixtures.py   |  10 +-
 tests/fixtures/rockets/rocket_fixtures.py  |  17 +-
 tests/fixtures/sensors/sensors_fixtures.py |  40 ++-
 tests/test_sensors.py                      |  69 ++---
 tests/unit/test_sensors.py                 | 282 +++++++++++++++++----
 5 files changed, 324 insertions(+), 94 deletions(-)

diff --git a/tests/fixtures/flight/flight_fixtures.py b/tests/fixtures/flight/flight_fixtures.py
index 9976ddac2..0b47707b1 100644
--- a/tests/fixtures/flight/flight_fixtures.py
+++ b/tests/fixtures/flight/flight_fixtures.py
@@ -161,14 +161,14 @@ def flight_calisto_air_brakes(calisto_air_brakes_clamp_on, example_plain_env):
 
 
 @pytest.fixture
-def flight_calisto_accel_gyro(calisto_accel_gyro, example_plain_env):
+def flight_calisto_sensors(calisto_sensors, example_plain_env):
     """A rocketpy.Flight object of the Calisto rocket. This uses the calisto
-    with an ideal accelerometer and a gyroscope. The environment is the simplest
-    possible, with no parameters set.
+    with a set of ideal sensors. The environment is the simplest possible, with
+    no parameters set.
 
     Parameters
     ----------
-    calisto_accel_gyro : rocketpy.Rocket
+    calisto_sensors : rocketpy.Rocket
         An object of the Rocket class.
     example_plain_env : rocketpy.Environment
         An object of the Environment class.
@@ -180,7 +180,7 @@ def flight_calisto_accel_gyro(calisto_accel_gyro, example_plain_env):
         condition.
     """
     return Flight(
-        rocket=calisto_accel_gyro,
+        rocket=calisto_sensors,
         environment=example_plain_env,
         rail_length=5.2,
         inclination=85,
diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index 0161f3950..9e971f124 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -244,27 +244,19 @@ def calisto_air_brakes_clamp_off(calisto_robust, controller_function):
 
 
 @pytest.fixture
-def calisto_accel_gyro(
+def calisto_sensors(
     calisto,
     calisto_nose_cone,
     calisto_tail,
     calisto_trapezoidal_fins,
     ideal_accelerometer,
     ideal_gyroscope,
+    ideal_barometer,
 ):
     """Create an object class of the Rocket class to be used in the tests. This
     is the same Calisto rocket that was defined in the calisto fixture, but with
-    an ideal accelerometer and a gyroscope added at the center of dry mass.
-    Meaning the readings will be the same as the values saved on a Flight object.
-
-    Parameters
-    ----------
-    calisto : rocketpy.Rocket
-        An object of the Rocket class. This is a pytest fixture.
-    accelerometer : rocketpy.Accelerometer
-        An object of the Accelerometer class. This is a pytest fixture.
-    gyroscope : rocketpy.Gyroscope
-        An object of the Gyroscope class. This is a pytest fixture.
+    a set of ideal sensors added at the center of dry mass, meaning the readings
+    will be the same as the values saved on a Flight object.
 
     Returns
     -------
@@ -278,6 +270,7 @@ def calisto_accel_gyro(
     calisto.add_sensor(ideal_accelerometer, -0.1180124376577797)
     calisto.add_sensor(ideal_accelerometer, -0.1180124376577797)
     calisto.add_sensor(ideal_gyroscope, -0.1180124376577797)
+    calisto.add_sensor(ideal_barometer, -0.1180124376577797)
     return calisto
 
 
diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
index c32a41124..08982c9d4 100644
--- a/tests/fixtures/sensors/sensors_fixtures.py
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -1,6 +1,8 @@
+import numpy as np
 import pytest
 
 from rocketpy import Accelerometer, Gyroscope
+from rocketpy.sensors.barometer import Barometer
 
 
 @pytest.fixture
@@ -47,6 +49,22 @@ def noisy_rotated_gyroscope():
     )
 
 
+@pytest.fixture
+def noisy_barometer():
+    """Returns a barometer with all parameters set to non-default values,
+    i.e. with noise and temperature drift."""
+    return Barometer(
+        sampling_rate=50,
+        noise_density=19,
+        noise_variance=19,
+        random_walk_density=0.01,
+        constant_bias=1000,
+        operating_temperature=25,
+        temperature_bias=0.02,
+        temperature_scale_factor=0.02,
+    )
+
+
 @pytest.fixture
 def quantized_accelerometer():
     """Returns an accelerometer with all parameters set to non-default values,
@@ -69,15 +87,33 @@ def quantized_gyroscope():
     )
 
 
+@pytest.fixture
+def quantized_barometer():
+    """Returns a barometer with all parameters set to non-default values,
+    i.e. with noise and temperature drift."""
+    return Barometer(
+        sampling_rate=50,
+        measurement_range=7e4,
+        resolution=0.16,
+    )
+
+
 @pytest.fixture
 def ideal_accelerometer():
     return Accelerometer(
-        sampling_rate=100,
+        sampling_rate=10,
     )
 
 
 @pytest.fixture
 def ideal_gyroscope():
     return Gyroscope(
-        sampling_rate=100,
+        sampling_rate=10,
+    )
+
+
+@pytest.fixture
+def ideal_barometer():
+    return Barometer(
+        sampling_rate=10,
     )
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 92960732e..a06cb8926 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -8,15 +8,15 @@
 from rocketpy.sensors.gyroscope import Gyroscope
 
 
-def test_sensor_on_rocket(calisto_accel_gyro):
+def test_sensor_on_rocket(calisto_sensors):
     """Test the sensor on the rocket.
 
     Parameters
     ----------
     calisto_accel_gyro : Rocket
-        Pytest fixture for the calisto rocket with an accelerometer and a gyroscope.
+        Pytest fixture for the calisto rocket with a set of ideal sensors.
     """
-    sensors = calisto_accel_gyro.sensors
+    sensors = calisto_sensors.sensors
     assert isinstance(sensors, Components)
     assert isinstance(sensors[0].component, Accelerometer)
     assert isinstance(sensors[1].position, Vector)
@@ -24,80 +24,91 @@ def test_sensor_on_rocket(calisto_accel_gyro):
     assert isinstance(sensors[2].position, Vector)
 
 
-def test_ideal_sensors(flight_calisto_accel_gyro):
+def test_ideal_sensors(flight_calisto_sensors):
     """Test the ideal sensors. All types of sensors are here to reduvce
     testing time.
 
     Parameters
     ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    flight_calisto_sensors : Flight
+        Pytest fixture for the flight of the calisto rocket with a set of ideal
+        sensors.
     """
-    accelerometer = flight_calisto_accel_gyro.rocket.sensors[0].component
+    accelerometer = flight_calisto_sensors.rocket.sensors[0].component
     time, ax, ay, az = zip(*accelerometer.measured_data[0])
     ax = np.array(ax)
     ay = np.array(ay)
     az = np.array(az)
     a = np.sqrt(ax**2 + ay**2 + az**2)
-    sim_accel = flight_calisto_accel_gyro.acceleration(time)
+    sim_accel = flight_calisto_sensors.acceleration(time)
 
     # tolerance is bounded to numerical errors in the transformation matrixes
     assert np.allclose(a, sim_accel, atol=1e-12)
     # check if both added accelerometer instances saved the same data
     assert (
-        flight_calisto_accel_gyro.sensors[0].measured_data[0]
-        == flight_calisto_accel_gyro.sensors[0].measured_data[1]
+        flight_calisto_sensors.sensors[0].measured_data[0]
+        == flight_calisto_sensors.sensors[0].measured_data[1]
     )
 
-    gyroscope = flight_calisto_accel_gyro.rocket.sensors[2].component
+    gyroscope = flight_calisto_sensors.rocket.sensors[2].component
     time, wx, wy, wz = zip(*gyroscope.measured_data)
     wx = np.array(wx)
     wy = np.array(wy)
     wz = np.array(wz)
     w = np.sqrt(wx**2 + wy**2 + wz**2)
-    flight_wx = np.array(flight_calisto_accel_gyro.w1(time))
-    flight_wy = np.array(flight_calisto_accel_gyro.w2(time))
-    flight_wz = np.array(flight_calisto_accel_gyro.w3(time))
+    flight_wx = np.array(flight_calisto_sensors.w1(time))
+    flight_wy = np.array(flight_calisto_sensors.w2(time))
+    flight_wz = np.array(flight_calisto_sensors.w3(time))
     sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
     assert np.allclose(w, sim_w, atol=1e-12)
 
+    barometer = flight_calisto_sensors.rocket.sensors[3].component
+    time, pressure = zip(*barometer.measured_data)
+    pressure = np.array(pressure)
+    sim_pressure = np.array(flight_calisto_sensors.pressure(time))
+    assert np.allclose(pressure, sim_pressure, atol=1e-12)
 
-def test_export_sensor_data(flight_calisto_accel_gyro):
+
+def test_export_sensor_data(flight_calisto_sensors):
     """Test the export of sensor data.
 
     Parameters
     ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    flight_calisto_sensors : Flight
+        Pytest fixture for the flight of the calisto rocket with a set of ideal
+        sensors.
     """
-    flight_calisto_accel_gyro.export_sensor_data("test_sensor_data.json")
+    flight_calisto_sensors.export_sensor_data("test_sensor_data.json")
     # read the json and parse as dict
     filename = "test_sensor_data.json"
     with open(filename, "r") as f:
         data = f.read()
         sensor_data = json.loads(data)
     # convert list of tuples into list of lists to compare with the json
-    flight_calisto_accel_gyro.sensors[0].measured_data[0] = [
+    flight_calisto_sensors.sensors[0].measured_data[0] = [
+        list(measurement)
+        for measurement in flight_calisto_sensors.sensors[0].measured_data[0]
+    ]
+    flight_calisto_sensors.sensors[1].measured_data[1] = [
         list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[0].measured_data[0]
+        for measurement in flight_calisto_sensors.sensors[1].measured_data[1]
     ]
-    flight_calisto_accel_gyro.sensors[1].measured_data[1] = [
+    flight_calisto_sensors.sensors[2].measured_data = [
         list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[1].measured_data[1]
+        for measurement in flight_calisto_sensors.sensors[2].measured_data
     ]
-    flight_calisto_accel_gyro.sensors[2].measured_data = [
+    flight_calisto_sensors.sensors[3].measured_data = [
         list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[2].measured_data
+        for measurement in flight_calisto_sensors.sensors[3].measured_data
     ]
     assert (
         sensor_data["Accelerometer"]["1"]
-        == flight_calisto_accel_gyro.sensors[0].measured_data[0]
+        == flight_calisto_sensors.sensors[0].measured_data[0]
     )
     assert (
         sensor_data["Accelerometer"]["2"]
-        == flight_calisto_accel_gyro.sensors[1].measured_data[1]
-    )
-    assert (
-        sensor_data["Gyroscope"] == flight_calisto_accel_gyro.sensors[2].measured_data
+        == flight_calisto_sensors.sensors[1].measured_data[1]
     )
+    assert sensor_data["Gyroscope"] == flight_calisto_sensors.sensors[2].measured_data
+    assert sensor_data["Barometer"] == flight_calisto_sensors.sensors[3].measured_data
     os.remove(filename)
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index ebb0c5b60..b122243f1 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -59,6 +59,15 @@ def test_gyroscope_prints(noisy_rotated_gyroscope, quantized_gyroscope):
     assert True
 
 
+def test_barometer_prints(noisy_barometer, quantized_barometer):
+    """Test the print methods of the Barometer class. Checks if all
+    attributes are printed correctly.
+    """
+    noisy_barometer.prints.all()
+    quantized_barometer.prints.all()
+    assert True
+
+
 def test_rotation_matrix(noisy_rotated_accelerometer):
     """Test the rotation_matrix property of the Accelerometer class. Checks if
     the rotation matrix is correctly calculated.
@@ -92,7 +101,9 @@ def test_ideal_accelerometer_measure(ideal_accelerometer):
         + Vector.cross(omega, Vector.cross(omega, relative_position))
     )
     ax, ay, az = Matrix.transformation(u[6:10]) @ accel
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
 
     # check last measurement
     assert len(ideal_accelerometer.measurement) == 3
@@ -101,7 +112,9 @@ def test_ideal_accelerometer_measure(ideal_accelerometer):
 
     # check measured values
     assert len(ideal_accelerometer.measured_data) == 1
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
     assert len(ideal_accelerometer.measured_data) == 2
 
     assert all(isinstance(i, tuple) for i in ideal_accelerometer.measured_data)
@@ -122,7 +135,7 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
     rot = Matrix.transformation(u[6:10])
     ax, ay, az = rot @ Vector(u[10:13])
 
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u=u, u_dot=UDOT, relative_position=relative_position)
 
     # check last measurement
     assert len(ideal_gyroscope.measurement) == 3
@@ -131,7 +144,7 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
 
     # check measured values
     assert len(ideal_gyroscope.measured_data) == 1
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u=u, u_dot=UDOT, relative_position=relative_position)
     assert len(ideal_gyroscope.measured_data) == 2
 
     assert all(isinstance(i, tuple) for i in ideal_gyroscope.measured_data)
@@ -139,6 +152,45 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
     assert ideal_gyroscope.measured_data[0][1:] == approx([ax, ay, az], abs=1e-10)
 
 
+def test_ideal_barometer_measure(ideal_barometer, example_plain_env):
+    """Test the measure method of the Barometer class. Checks if saved
+    measurement is (P) and if measured_data is [(t, P), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector(
+        [np.random.randint(-1, 1), np.random.randint(-1, 1), np.random.randint(-1, 1)]
+    )
+
+    rot = Matrix.transformation(u[6:10])
+    P = example_plain_env.pressure((rot @ relative_position).z + u[2])
+
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+
+    # check last measurement
+    assert isinstance(ideal_barometer.measurement, (int, float))
+    assert ideal_barometer.measurement == approx(P, abs=1e-10)
+
+    # check measured values
+    assert len(ideal_barometer.measured_data) == 1
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+    assert len(ideal_barometer.measured_data) == 2
+
+    assert all(isinstance(i, tuple) for i in ideal_barometer.measured_data)
+    assert ideal_barometer.measured_data[0][0] == t
+    assert ideal_barometer.measured_data[0][1] == approx(P, abs=1e-10)
+
+
 def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
@@ -177,7 +229,9 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     az += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    noisy_rotated_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
     assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.5)
 
 
@@ -210,10 +264,37 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     wz += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_gyroscope.measure(t, u, UDOT, relative_position, gravity)
+    noisy_rotated_gyroscope.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
     assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.5)
 
 
+def test_noisy_barometer_measure(noisy_barometer, example_plain_env):
+    """Test the measure method of the Barometer class. Checks if saved
+    measurement is (P) and if measured_data is [(t, P), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector(
+        [np.random.randint(-1, 1), np.random.randint(-1, 1), np.random.randint(-1, 1)]
+    )
+
+    rot = Matrix.transformation(u[6:10])
+    P = example_plain_env.pressure((rot @ relative_position).z + u[2])
+    # expected measurement with constant bias
+    P += 1000
+
+    # check last measurement considering noise error bounds
+    noisy_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+    assert noisy_barometer.measurement == approx(P, rel=0.5)
+
+
 def test_quantization_accelerometer(quantized_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
@@ -243,7 +324,9 @@ def test_quantization_accelerometer(quantized_accelerometer):
     az = round(az / 0.4882) * 0.4882
 
     # check last measurement considering noise error bounds
-    quantized_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    quantized_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
     assert quantized_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
 
 
@@ -268,25 +351,48 @@ def test_quantization_gyroscope(quantized_gyroscope):
     wz = round(wz / 0.4882) * 0.4882
 
     # check last measurement considering noise error bounds
-    quantized_gyroscope.measure(t, u, UDOT, relative_position, gravity)
+    quantized_gyroscope.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
     assert quantized_gyroscope.measurement == approx([wx, wy, wz], abs=1e-10)
 
 
+def test_quantization_barometer(quantized_barometer, example_plain_env):
+    """Test the measure method of the Barometer class. Checks if saved
+    measurement is (P) and if measured_data is [(t, P), ...]
+    """
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    # calculate acceleration at sensor position in inertial frame
+    relative_position = Vector([0.4, 0.4, 1])
+    # expected measurement without noise
+    P = example_plain_env.pressure(
+        (Matrix.transformation(u[6:10]) @ relative_position).z + u[2]
+    )
+    # expected measurement with quantization
+    P = 7e4  # saturated
+    P = round(P / 0.16) * 0.16
+
+    # check last measurement considering noise error bounds
+    quantized_barometer.measure(
+        t, u=u, relative_position=relative_position, pressure=example_plain_env.pressure
+    )
+    assert quantized_barometer.measurement == approx(P, abs=1e-10)
+
+
 def test_export_accel_data_csv(ideal_accelerometer):
     """Test the export_data method of accelerometer. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
-    """
+    exported correctly."""
     t = SOLUTION[0]
     u = SOLUTION[1:]
     relative_position = Vector([0, 0, 0])
     gravity = 9.81
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
+    ideal_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
 
     file_name = "sensors.csv"
 
@@ -322,20 +428,17 @@ def test_export_accel_data_csv(ideal_accelerometer):
 
 def test_export_accel_data_json(ideal_accelerometer):
     """Test the export_data method of the accelerometer. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal
-        accelerometer and a gyroscope.
-    """
+    exported correctly."""
     t = SOLUTION[0]
     u = SOLUTION[1:]
     relative_position = Vector([0, 0, 0])
     gravity = 9.81
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
+    ideal_accelerometer.measure(
+        t, u=u, u_dot=UDOT, relative_position=relative_position, gravity=gravity
+    )
 
     file_name = "sensors.json"
 
@@ -371,19 +474,12 @@ def test_export_accel_data_json(ideal_accelerometer):
 
 def test_export_gyro_data_csv(ideal_gyroscope):
     """Test the export_data method of the gyroscope. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal
-        accelerometer and a gyroscope.
-    """
+    exported correctly."""
     t = SOLUTION[0]
     u = SOLUTION[1:]
     relative_position = Vector([0, 0, 0])
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u=u, u_dot=UDOT, relative_position=relative_position)
+    ideal_gyroscope.measure(t, u=u, u_dot=UDOT, relative_position=relative_position)
 
     file_name = "sensors.csv"
 
@@ -419,18 +515,12 @@ def test_export_gyro_data_csv(ideal_gyroscope):
 
 def test_export_gyro_data_json(ideal_gyroscope):
     """Test the export_data method of the gyroscope. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
-    """
+    exported correctly."""
     t = SOLUTION[0]
     u = SOLUTION[1:]
     relative_position = Vector([0, 0, 0])
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u=u, u_dot=UDOT, relative_position=relative_position)
+    ideal_gyroscope.measure(t, u=u, u_dot=UDOT, relative_position=relative_position)
 
     file_name = "sensors.json"
 
@@ -462,3 +552,103 @@ def test_export_gyro_data_json(ideal_gyroscope):
     os.remove(file_name)
     os.remove(file_name + "_1")
     os.remove(file_name + "_2")
+
+
+def test_export_barometer_data_csv(ideal_barometer, example_plain_env):
+    """Test the export_data method of the barometer. Checks if the data is
+    exported correctly."""
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector([0, 0, 0])
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+
+    file_name = "sensors.csv"
+
+    ideal_barometer.export_measured_data(file_name, format="csv")
+
+    with open(file_name, "r") as file:
+        contents = file.read()
+
+    expected_data = "t,pressure\n"
+    for t, pressure in ideal_barometer.measured_data:
+        expected_data += f"{t},{pressure}\n"
+
+    assert contents == expected_data
+
+    # check exports for gyroscopes added more than once to the rocket
+    ideal_barometer.measured_data = [
+        ideal_barometer.measured_data[:],
+        ideal_barometer.measured_data[:],
+    ]
+    ideal_barometer.export_measured_data(file_name, format="csv")
+    with open(file_name + "_1", "r") as file:
+        contents = file.read()
+    assert contents == expected_data
+
+    with open(file_name + "_2", "r") as file:
+        contents = file.read()
+    assert contents == expected_data
+
+    os.remove(file_name)
+    os.remove(file_name + "_1")
+    os.remove(file_name + "_2")
+
+
+def test_export_barometer_data_json(ideal_barometer, example_plain_env):
+    """Test the export_data method of the barometer. Checks if the data is
+    exported correctly."""
+    t = SOLUTION[0]
+    u = SOLUTION[1:]
+    relative_position = Vector([0, 0, 0])
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+
+    file_name = "sensors.json"
+
+    ideal_barometer.export_measured_data(file_name, format="json")
+
+    contents = json.load(open(file_name, "r"))
+
+    expected_data = {"t": [], "pressure": []}
+    for t, pressure in ideal_barometer.measured_data:
+        expected_data["t"].append(t)
+        expected_data["pressure"].append(pressure)
+
+    assert contents == expected_data
+
+    # check exports for gyroscopes added more than once to the rocket
+    ideal_barometer.measured_data = [
+        ideal_barometer.measured_data[:],
+        ideal_barometer.measured_data[:],
+    ]
+    ideal_barometer.export_measured_data(file_name, format="json")
+    contents = json.load(open(file_name + "_1", "r"))
+    assert contents == expected_data
+
+    contents = json.load(open(file_name + "_2", "r"))
+    assert contents == expected_data
+
+    os.remove(file_name)
+    os.remove(file_name + "_1")
+    os.remove(file_name + "_2")

From f535e0fd57fb6156dbec0a0e62f87bebca605545 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Sun, 5 May 2024 16:12:04 +0200
Subject: [PATCH 051/120] DEV: update sensors testing

---
 docs/notebooks/sensors_testing.ipynb | 192 +++++++++++++++++++++------
 1 file changed, 150 insertions(+), 42 deletions(-)

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors_testing.ipynb
index 797dcb232..2d4cd6081 100644
--- a/docs/notebooks/sensors_testing.ipynb
+++ b/docs/notebooks/sensors_testing.ipynb
@@ -198,14 +198,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from rocketpy import Accelerometer, Gyroscope\n",
+    "from rocketpy import Accelerometer, Gyroscope, Barometer\n",
     "accel_noisy_nosecone = Accelerometer(sampling_rate=100,\n",
     "                  consider_gravity=False,\n",
     "                  orientation=(60,60,60),\n",
     "                  measurement_range=70,\n",
     "                  resolution=0.4882,\n",
     "                  noise_density=0.05,\n",
-    "                  random_walk=0.02,\n",
+    "                  random_walk_density=0.02,\n",
     "                  constant_bias=1 ,\n",
     "                  operating_temperature=25,\n",
     "                  temperature_bias=0.02,\n",
@@ -256,7 +256,9 @@
       "Noise of the Sensor:\n",
       "\n",
       "Noise Density:             (0.05, 0.05, 0.05) m/s^2/√Hz\n",
-      "Random Walk:               (0.02, 0.02, 0.02) m/s^2/√Hz\n",
+      "Noise Variance:            (1, 1, 1) (m/s^2)^2\n",
+      "Random Walk Density:       (0.02, 0.02, 0.02) m/s^2/√Hz\n",
+      "Random Walk Variance:      (1, 1, 1) (m/s^2)^2\n",
       "Constant Bias:             (1, 1, 1) m/s^2\n",
       "Operating Temperature:     25 °C\n",
       "Temperature Bias:          (0.02, 0.02, 0.02) m/s^2/°C\n",
@@ -284,7 +286,9 @@
       "Noise of the Sensor:\n",
       "\n",
       "Noise Density:             (0, 0, 0) m/s^2/√Hz\n",
-      "Random Walk:               (0, 0, 0) m/s^2/√Hz\n",
+      "Noise Variance:            (1, 1, 1) (m/s^2)^2\n",
+      "Random Walk Density:       (0, 0, 0) m/s^2/√Hz\n",
+      "Random Walk Variance:      (1, 1, 1) (m/s^2)^2\n",
       "Constant Bias:             (0, 0, 0) m/s^2\n",
       "Operating Temperature:     25 °C\n",
       "Temperature Bias:          (0, 0, 0) m/s^2/°C\n",
@@ -302,34 +306,78 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.001064225153655079"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "np.radians(0.06097560975609756097560975609756)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
     "gyro_clean = Gyroscope(sampling_rate=100)\n",
-    "gyro_noisy = Gyroscope(sampling_rate=100, \n",
-    "              orientation=(180, 0, 0),\n",
-    "              acceleration_sensitivity=0.02,\n",
-    "                  measurement_range=70,\n",
-    "                  resolution=0.4882,\n",
-    "                  noise_density=0.05,\n",
-    "                  random_walk=0.02,\n",
-    "                  constant_bias=1 ,\n",
-    "                  operating_temperature=25,\n",
-    "                  temperature_bias=0.02,\n",
-    "                  temperature_scale_factor=0.02,\n",
-    "                  cross_axis_sensitivity=0.02,\n",
-    "                  )\n",
-    "calisto.add_sensor(gyro_clean, -0.10482544178314143+0.5, 127/2000)\n",
+    "gyro_noisy = Gyroscope(\n",
+    "        sampling_rate=100,\n",
+    "        resolution=0.001064225153655079,\n",
+    "        orientation=(-60, -60, -60),\n",
+    "        noise_density=[0, 0.03, 0.05],\n",
+    "        noise_variance=1.01,\n",
+    "        random_walk_density=[0, 0.01, 0.02],\n",
+    "        random_walk_variance=[1, 1, 1.05],\n",
+    "        constant_bias=[0, 0.3, 0.5],\n",
+    "        operating_temperature=25,\n",
+    "        temperature_bias=[0, 0.01, 0.02],\n",
+    "        temperature_scale_factor=[0, 0.01, 0.02],\n",
+    "        cross_axis_sensitivity=0.5,\n",
+    "        acceleration_sensitivity=[0, 0.0008, 0.0017],\n",
+    "        name=\"Gyroscope\",\n",
+    "    )\n",
+    "calisto.add_sensor(gyro_clean, -0.10482544178314143)#+0.5, 127/2000)\n",
     "calisto.add_sensor(gyro_noisy, 1.278-0.4, 127/2000-127/4000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "barometer_clean = Barometer(sampling_rate=50,\n",
+    "                            measurement_range=100000,\n",
+    "                            resolution=0.16,\n",
+    "                            noise_density=19,\n",
+    "                            noise_variance=19,\n",
+    "                            random_walk_density=0.01,\n",
+    "                            constant_bias=1,\n",
+    "                            operating_temperature=25,\n",
+    "                            temperature_bias=0.02,\n",
+    "                            temperature_scale_factor=0.02,\n",
+    "                            )\n",
+    "calisto.add_sensor(barometer_clean, -0.10482544178314143+0.5, -127/2000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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Zv38/DRo0YOvWrUyZMoU5c+agr69P586dadSokcy0tQADBgzgzp07bNmyhdWrV2NlZZVnpaKgnzdBEARBKC4KUVFRYmSeIAifzLNnz3Bzc2PGjBmMHDmypMMRBEEQBKEIiDEVgiAIgiAIgiB8FFGpEARBEARBEATho4hKhSAIgiAIgiAIH0WMqRAEQRAEQRAE4aOIlgpBEARBEARBED6KmFK2CGRkZPDy5Uu0tbWLZLViQRAEQSgOmZmZxMXFYWFhgaKieK8oCELREZWKIvDy5UtcXFxKOgxBEARBKJDbt29Tvnz5kg5DEIQviKhUFAFtbW0AQkNDcyzw9aW5cuVKoRZKK8tEzuQnciY/kTP5lcWcxcbGYmVlJf2/JQiCUFREpaIIZHd50tXV/eIrFSYmJl/8PRY1kTP5iZzJT+RMfmU5Z6KrriAIRU10qBTkUqlSpZIOodQROZOfyJn8RM7kJ3ImCIJQdESlQpDLtWvXSjqEUkfkTH4iZ/ITOZOfyJkgCELREZUKQRAEQRAEQRA+ihhTIcjF0tKypEModUTO5CdyJj+RM/mJnH16GRkZpKWllXQYgiAUgLKyslxTT4tKhSAXZWXxkZGXyJn8RM7kJ3ImP5GzTyczM5Po6GgSEhLEIHFBKCUyMzPR1NREX1+/QP9uxW9UQS4hISGYmZmVdBilisiZ/ETO5CdyJj+Rs08nOjqaxMRETE1N0dDQEBULQfjMZWZmkpiYSHh4OAAGBgYfPEdUKgRBEARBKDYZGRkkJCRgamqKoaFhSYcjCEIBaWhoABAWFoaent4Hu0KJgdqCXMTK4fITOZOfyJn8RM7kJ3L2aaSlpaGgoCA9oAiCUHpktywWZCyUqFQIcnn27FlJh1DqiJzJT+RMfiJn8hM5+7RElydBKH3k+XcrKhWCXGJiYko6hFJH5Ex+ImfyEzmTn8iZIAhC0RGVCkEu6urqJR1CqSNyJj+RM/mJnMlP5EwQBKHoFKpSkZqayvPnz3n06BFv3rwp6piEz5izs3NJh1DqiJzJT+RMfiJn8hM5E0pa//796dSpU0mH8cVISEigS5cuGBoaoqKiQnR0dEmHVKYUuFLx9u1b1q9fT+vWrbGxscHNzY06derg6OhItWrV+P7777l27Vpxxip8Bq5cuVLSIZQ6ImfyEzmTn8iZ/ETOhA959eoVY8aMoVKlSmhra1O+fHkaNWrEmjVrSEhI+OjyFy9ezLp164og0rylpKTw888/4+7ujq6uLubm5jRq1Ijff/+d1NTUIruOj48PHh4eRVZeYWzcuJFz585x9uxZQkND0dPTy3GMn58fKioquU7UsHPnTlRUVHBwcPgU4X5xCjSl7MqVK1m0aBF2dnZ4eXkxZswYLCwsUFdX582bNwQGBnLhwgU6deqEh4cH8+fPp0KFCsUduyAIgiAIQrF48uQJjRs3Rl9fn5kzZ+Ls7Iyamhp37tzht99+o3z58rRp0ybXc1NTU1FRUfngNXJ76C1KKSkptGzZklu3bjF9+nTq1auHrq4uAQEBLFq0CDc3N9zc3Io1BnmlpKSgqqpaqHOfPHlCpUqVPtgKqaWlRVhYGBcuXKBu3brS9g0bNmBtbV2oawsFbKm4fv06f/31FydOnOCHH37A09OTKlWqYG9vj4eHB7169WLlypXcv3+fVq1aceHChWIL+LfffsPV1RULCwuaNWvG1atX8zzWz8+Pli1bYmdnh52dHR06dMhx/PDhwzE0NJT58vb2Lrb4SzsLC4uSDqHUETmTn8iZ/ETO5CdyVvqkJycT9/w56cnJxX6tkSNHoqyszMWLF+ncuTOVK1fG3t6etm3bsn//flq3bi0dq6Kiwpo1a+jQoQN6enrMnTuX9PR0Bg0ahKOjIzo6OlStWpVly5bJXOP97k+enp6MHj2an376CVNTUywtLfHx8ZH2Z2Zm4uPjg729PVpaWlhbWzN69Og872HZsmX8/fffHD16lGHDhuHm5oa9vT3du3fn/PnzODo6AllricyfP1+K1d3dnV27dknl+Pv7o6KiwqlTp6hduza6uro0bNiQBw8eAFnPWzNnzuTWrVuoqKigoqKCn58fkLXw4eDBg7GwsMDQ0JDmzZtz8+ZNqezsFo5169bh6OiItrZ2nveze/duXF1d0dLSwsHBgcWLF8vkbvHixfz999+oqKjg6emZZznKysp069aN33//Xdr2/Plz/P396datm8yxQUFBdOzYkfLly6Ovr0+dOnU4efKkzDGrV6+mcuXKUmtW165dpX27du3Czc0NHR0dzMzM8PLyIj4+Ps/YSrMCtVT89ttvBSpMTU2Nfv36fVRA+dm9ezeTJ09m4cKFeHh4sGbNGry9vbl06RImJiY5jv/nn3/o1KkTtWrVQk1NjaVLl9KpUyfOnz9PuXLlpOM8PT1ZsWKFzH0IudPU1CzpEEodkTP5iZzJT+RMfiJnpcvrgAD+GTOGtPh4lLW0qL94MWa1axfLtSIjIzl+/DizZs1CS0sr12Pen2pz5syZzJ49m4ULF6KsrExGRgaWlpZs3boVIyMjLly4wNChQ7GwsKBz5855XvuPP/5g9OjR/PPPP1y8eJEBAwZQr149mjVrxu7du1m6dCmbN2+mSpUqvHr1ilu3buVZ1pYtW/D09KR69eo59mU//APMnz+fLVu2sHLlShwcHPj777/p06cPJiYmNGrUSDpnypQpLFiwAGNjY4YPH86gQYM4e/YsXbp04e7duxw7dowjR44A/7XCdOvWDQ0NDQ4cOICenh6//vorXl5e3Lt3T1oMMSgoiD179vDnn3+ipKSU671cvXqV7t27M3XqVDp37syFCxcYOXIkhoaG9OnThx07djBx4kTu3r3Ljh07Ptja0bdvX5o1a8bixYvR1NRk48aNeHl5YWpqKnNcXFwcX3/9NT4+PqipqbFp0ybat2/P3bt3sba25sqVK4wZM4bff/+dunXrEhUVxblz5wB4+fIlvXr1Yu7cubRv3563b99y7tw5MjMz842ttCpVK2qvWrWK3r1707NnTwAWLVrE8ePH2bx5c6419bVr18p8v2zZMg4cOMDZs2dlaqJqamqYmZkVa+xfiqCgIIyNjUs6jFJF5Ex+ImfyEzmTn8hZ6ZGenJxVofj/cQxpCQn8M2YM7U6fRqkYXgQ+fvyYzMxMnJycZLabm5uTlJQEwNChQ5k7d660r1u3bvTt21fm+GnTpkl/t7Oz4+LFi+zcuTPfSoWLiwtTpkwBwNHRkVWrVnHq1CmaNWvGs2fPMDc3x9PTExUVFaytralVq1a+99G4ceN87zU5OZl58+Zx5MgRqSuQvb09//zzD7/++qtMpWLmzJnS9+PHj6dt27YkJSWhoaGBtrY2SkpKmJubS8efO3eOy5cv8+LFC+mFra+vL/v372fXrl0MGjQIyOrytGHDhlxfEGdbsmQJTZs2ZdKkSQA4OTkRGBjIokWL6NOnD4aGhmhqaqKqqioTQ16qV6+OnZ0du3btolevXmzcuJEFCxbw5MkTmeNcXV1xdXWVvp8xYwb79u3jwIEDDB8+nNDQULS0tGjVqhU6OjrY2NhIlbiXL1+SlpZGhw4dsLGxAb7sRTflrlQkJSWxdu1azp07R0REBBkZGTL7z5w5U1SxyUhJSeHmzZuMGTNG2qaoqEjjxo25fPlygcpISEggLS0NAwMDme3nzp3DyckJfX19GjZsyKRJk6Tac26Sk5NJfqfp9e3bt3LejSAIgiAIBZUYHk7au11GMjNJi48nMTwcbUvLTxbH+fPnycjIoHfv3jLPAUCug5RXrVrF77//TmhoKImJiaSkpMg8oObm/YdOCwsLwsLCAPD29mb58uU4OTnRokULvvnmG1q3bo2ycu6PcwV5I/748WMSEhL45ptvZLanpKTkGG/xbmzZD+5hYWF5jkO4desWcXFxOV7cJiYmyjy829jY5FuhALh//z5t27aV2VavXj2WLVtGenp6ni0c+enbty9+fn5YW1sTHx/PN998w8qVK2WOiYuLw8fHh8OHD0uVhMTEREJDQwFo1qwZ1tbW0s/Ey8uL9u3bo6mpiaurK02bNqV69eq0aNGCZs2a0alTpxzPoV8KuSsVo0aN4vTp07Rt2xZ3d/dPtkJmZGQk6enpOT50JiYmPHz4sEBlzJgxA3Nzc5lae9OmTaUZrYKDg5k5cyZdunTh6NGjeX5AFy9ejK+vb47tV65cQUtLC3d3dwIDA0lMTERHRwc7OzupedLGxoaMjAzpw+jm5sbjx4+Ji4tDS0sLJycnrl+/DoClpSVKSko8ffoUgGrVqhESEkJsbCzq6upUrVpVGiNSrlw51NXVpX+kzs7OPH/+nOjoaFRVVXFzc+PSpUtA1i8CbW1tHj9+DEDlypV5/fo1UVFRKCsr4+HhwaVLl8jMzMTExAQDAwMpx1ZWVjx58oTw8HAUFRWpWbMmV65cIT09HSMjI0xNTQkMDASy3rDExsby+vVrAGrXrs21a9dITU3FwMCAcuXKcffuXQAqVKhAQkICL1++BKBGjRrcuXOHpKQk9PT0sLa25vbt2wDY2tqSlpbG8+fPAXB3d+f+/fskJCSgra1NhQoVpP6a2b/oslfOdXV1JSgoiLi4ODQ1NalUqZI0a5mlpSXKysqEhIQAWb88nz17RkxMDOrq6jg7O0uzxVhYWKCpqUlQUBAAVatW5cWLF7x58wYVFRXc3d0JCAgAQF9fn6ioKB49eiTlOywsjMjISJSUlKhRowaXL18mIyMDExMTDA0NpX6qTk5OvHnzhvDwcBQUFKhVqxZXr14lLS0NQ0NDzMzMpHw7ODgQFxfHq1evAKhVqxY3btwgJSUFfX19LC0tuXPnDpD1FiopKYkXL14AWf8Z3r17l6SkJHR1dbG1tZX5zKanp0v5rl69Og8fPiQ+Ph5tbW0cHBy4ceOG9PlQVFSU+cwGBwfz9u1bNDQ0qFy5spTv8uXLo6qqSnBwsJTv0NBQoqOjUVRUJCMjQ3phYG5ujpaWlpTv7Gb/qKioHPk2NTVFT09PynelSpWIiIggIiJC+sxm59vY2BhjY2Pu378vfWZjYmKk/8Df/cwaGhpibm7OvXv3pM9sfHy8lO+aNWty69YtkpOT0dfXx8rKSvrM2tnZkZKSwr///it9Zov6d0T2f3Ql/TuiYsWKREVFlYrfEWlpaVJ5Jfk7wszMDF1d3U/yOyL7fksbDRMTlLW0sloqMjNBQQFlTU00PvAgWlgODg4oKCjkeL6wt7fPikdDI8c573eT2r59Oz/++CO+vr7UqVMHHR0dFi5cKP07y8v7A7wVFBSkF7hWVlbcvXuXkydPcuLECUaOHMnChQs5depUrgPDHR0dpc9KXuLi4gDYv3+/TNdwyNkd/N1rZD//vf9y+V3x8fFYWFhw4sSJHPv09fWlv5dUV8QePXowYcIEfHx86NmzZ66Vs/Hjx3Py5ElpEiINDQ26du1KSkoKADo6Oly+fBl/f3+OHz/OjBkzmDlzJhcuXEBfX58jR45w/vx5Tpw4wcqVK5k6dSr//PMPdnZ2n/p2i51CVFSUXB27bGxs2L59O3Xq1CmumHL18uVLqlatypEjR2Sa+qZNm8Y///yT6wf2XUuWLJG6P1WtWjXP40JCQnB3d2fPnj15Nhnm1lLh4uJCTEwMurq6ct5Z6fLw4cMczcFC/kTO5CdyJj+RM/mVxZzFxsaip6dHSEjIJ/v/KiUlhYiICGxsbD5qwcFPOaYCoGXLlty7d4+7d+/mqDB4enri6urKokWLgKyH7Z07d9KuXTvpmO+//57AwECOHTsmbfPy8iIiIkKq7Pfv35+YmBhpUPT75QJ06tQJPT091q9fnyPGBw8e4OzsTEBAAO7u7jn2L1iwgMmTJ3Px4sUc4ypSU1NJSUkhIyMDCwsL1qxZQ69evXLNhb+/P82aNSM8PFyqDNy4cYOaNWvy6NEjbG1tmTdvHtu2bZNeMgGcOHGC1q1bc//+fWxtbXMt28fHh3379uU78Q7At99+S0REBIcPH5a2/fTTTxw5ckS65tixY7l582aOgdTv8vPzY9y4cURERABZFYsdO3Zw+/ZtKlWqxNKlS1m+fLn0UsXNzY3OnTtL3a7i4uKwtbWld+/eMj+nbPHx8RgbG7NlyxY6dOggsy89PZ0KFSrw/fffy/S8+ZwlJSXx9OlTjI2NPzhORe6WCgsLC3R0dAodXGEZGRmhpKREeHi4zPbw8PAPjodYvnw5S5YsYc+ePflWKCDrDZeRkRHBwcF5VirU1NTK7GBusdih/ETO5CdyJj+RM/mJnJUuZrVr0+70aRLDw9EwMSmWsRTvWr58OY0bN6ZOnTpMmTIFFxcXFBUVuXLlCg8ePMj1If5dDg4ObNq0iWPHjmFra8vmzZu5cuVKng/XBeHn50d6ejq1atVCU1OTLVu2oKGhIfXXf9+oUaM4dOgQXl5eTJ8+nfr166Ojo8PVq1dZsGABa9euxc3NjbFjx/K///2PjIwM6tevT0xMDOfPn0dXV5fevXsXKDYbGxtCQkK4ceMGlpaW6Ojo4OnpSZ06dejUqRPz5s3D0dGRFy9ecPjwYdq1a0eNGjUKfO9jxoyhbt26zJ49m86dO3Px4kVWrVrF8uXLC1xGbtatW8fy5csxMjLKdb+joyN79uyhVatWKCgoMH36dJnWmYMHD/LkyRMaNmyIgYEBhw8fJiMjAycnJwICAjh9+jTNmjXD1NSUS5cuER4eTuXKlT8q5s+V3Ctqz5w5k+nTp0tN85+Kqqoqrq6unD17VtqWkZGBv78/NWvWzPO8ZcuW8fPPP7Njx45cZz9437///ktUVJQYuJ2Hgsy7LcgSOZOfyJn8RM7kJ3JW+iipqaFtaVnsFQrI6nJ3+fJlmjZtyuTJk/Hw8KBOnTqsXLmSsWPHMmPGjHzPHzx4MO3bt6dHjx7Ur1+fyMhIvvvuu4+KSV9fn3Xr1tG4cWPc3d05efIke/fuzfOBWE1NjSNHjvC///2PX3/9lQYNGlC3bl1WrFjBiBEjpPUcZsyYwcSJE/H19cXFxYXWrVtz+PBhubrodOzYES8vL5o3b46FhQXbtm1DQUGBAwcO0LBhQwYOHEiVKlXo1asXT58+lfs5y93dna1bt/Lnn3/i5ubGjBkzmD59On369JGrnPdpaGjkmT/Iau0xMDCgUaNGdOjQgebNm8s8T+rp6bF3715atGiBi4sLa9euZdOmTVStWhVdXV3+/vtv2rZtS5UqVZg2bRq+vr58/fXXHxXz50ru7k8RERH079+f8+fPo6mpmaP/2fuj5ovS7t27GT58OIsWLcLd3Z01a9awd+9eAgICMDU1laZqmzp1KgBLly5l7ty5rF27ltrvNJFqaWmhra1NXFwcvr6+tGnTBjMzM4KDg5k+fTpxcXGcO3euwK0RsbGx2NralonuT4IgCELpVZq7PwmC8OkVa/enQYMG8fLlS6ZMmYKJicknG6gNWbXgyMhI5s6dS1hYGM7OzuzYsUOaU/j58+coKv7X+LJ+/XpSUlJyTPE2fvx4fvrpJ5SUlLh79y7btm0jJiYGc3NzvvrqKyZOnFhmuzd9SEBAgEwFTfgwkTP5iZzJT+RMfiJngiAIRUfuSsWlS5c4evToB5dALy6DBg2S5jV+34EDB2S+f3fFxtxoaGjIrBgpCIIgCIIgCIL85B5T4ejoSGJiYnHEIpQCYqyJ/ETO5CdyJj+RM/mJnAmCIBQduSsVU6dOZcqUKZw7d46oqChiY2NlvoQvmxgzIj+RM/mJnMlP5Ex+ImeCIAhFR+5KRefOnbl8+TLt27fHyckJe3t77O3tsbOzkxaFEb5c2YszCQUnciY/kTP5iZzJT+RMEASh6Mg9pmL//v3FEYfwESIiIjhy5AiZmflP5FWuXDmaNm36SQfXC4IgCIIgCF8+uSsV9evXL444hI+wYsWKD86Xne2vv/6iVatWhb7Wl7pgS3ESOZOfyJn8RM7kJ3ImCIJQdArU/en58+dyFfrixYtCBSMUTmpqKjY2NiQnJ+f79dVXX/Hjjz+Snp5e6GuFhYUVYeRlg8iZ/ETO5CdyJj+RM0EQhKJToJYKT09PWrZsybfffpvnsvSxsbHs2bOHX375hT59+jBkyJAiDVTIn4KCwgcXJfH19aVmzZr4+fnRv3//Ql0nMjISBweHQp1bVomcyU/kTH4iZ/ITOStZMTHPSEiI+GTX09Q0Rk/P+pNdTxDKmgJVKi5cuMDChQvp2LEj6urquLq6Ym5ujrq6OtHR0Tx48ID79+9TrVo1ZsyYQfPmzYs7bqEQatSoQbdu3ZgyZQrdunVDU1NT7jKUlJSKIbIvm8jZfzIzMws0pkfkTH4iZ/Ir9TnLzIRSOkYuJuYZv/ziTGrqp5uiXkVFgyFD7nxWFYv+/fsTExMj1swSvggFqlQYGhoye/ZsJk+ezLFjx7h48SLPnz8nMTERIyMjvL29adq0KVWqVCnueIWPNHv2bCpVqsSSJUuYOHGi3OfXqFGjGKL6somcZbn08hKupq6oKX14tXqRM/mJnMmv1Ofs8QlwLJ0v8RISIkhNTeTrr3pgaGBa7NeLehPGkdNbSEiIkLtS8erVK+bPn8/hw4d5/vw5enp6VKhQgR49etC7d+9CvaDLtnjx4g9OsiIIpYVcA7U1NDRo164d7dq1K654hGJmb2/PsGHDmDdvHoMGDcLExESu8y9fvkzNmjWLKbovk8gZZGRmsOjqIv745o8CHS9yJj+RM/mV6pylJMCZeaW2UpHN0MAUU2PLkg4jT0+ePKFx48bo6+szc+ZMnJ2dUVNT486dO/z222+UL1+eNm3a5DgvNTUVFRWVD5avp6dXHGELQomQe50KofSbPHkyCgoKzJo1S+5zMzIyiiGiL5vIGRwLOcbdyLsFns5Y5Ex+ImfyK9U5u7gK4l6XdBRfvJEjR6KsrMzFixfp3LkzlStXxt7enrZt27J//35at24NgIqKCmvWrKFDhw7o6ekxd+5c0tPTGTRoEI6Ojujo6FC1alWWLVsmU37//v3p1KmT9L2npyejR4/mp59+wtTUFEtLS3x8fKT9mZmZ+Pj4YG9vj5aWFtbW1owePfqT5EIQPkRUKsogY2NjJkyYwOrVqwkKCpLrXHlbNgSRs9T0VJZeWwqAokLBfuWU9ZwVhsiZ/EptzuIj4NySUjueorSIjIzk+PHjDB06FC0trVyPefdFycyZM2nXrh3Xr1+nb9++ZGRkYGlpydatW7l16xaTJk1iypQp7NixI9/r/vHHH2hpafHPP/8wd+5cZs2axYkTJwDYvXs3S5cuZdWqVQQGBrJz506cnZ2L7qYF4SOISkUZ9f3332NqasqkSZPkOs/Q0LCYIvpylfWc/fnwT57HZU1LrUDBHoLKes4KQ+RMfqU2Z2cXQMpbKGAlXSicx48fk5mZiZOTk8x2c3Nz9PX10dfXZ8KECdL2bt260bdvX+zt7bG2tkZFRYVp06ZRo0YN7Ozs6NGjB3369GHnzp35XtfFxYUpU6bg6OjIt99+i4eHB6dOnQLg2bNnmJub4+npibW1NbVq1WLgwIFFf/OCUAjiN1IZpaGhwcyZM9m+fTuXLl0q8HkPHjwoxqi+TGU5Z3Epcfxy8xcgq0JR0O5PZTlnhSVyJr9SmbOoYLi8LuvvolJRIs6fP8+VK1eoUqUKycnJ0nYPD48cx65atYpatWphYWGBvr4+v/32G8+ePcu3fBcXF5nvLSwspDVVvL29SUxMxMnJiSFDhrB3717S0tKK4K4E4eOJ30hlWO/evXF2dmb8+PFi9gmhWKy/s543yW+Agnd9EgQhH6dmQkZq1t/Fv6li5eDggIKCAg8fPpTZbm9vj4ODAxoaGjLb3+8itX37dn788Uf69evHoUOHuHLlCn369CElJSXf674/wFtBQUEa/2NlZcXdu3dZvnw5GhoajBw5kq+++orU1NTC3qYgFBm5fyNt3bqVY8eOSd9PmzYNW1tbvLy8CA0NLdLghOKlpKTE/Pnz8ff359ChQwU65/1mYOHDymrOwhLC+OPef7M9FbSVAspuzj6GyJn8Sl3O/r0Gd95Zz0BUKoqVkZERzZo1Y9WqVcTHx8t9/vnz56lbty5Dhw6levXqODg48OTJk4+OS0NDg9atW7NkyRJOnDjBxYsXuX379keXKwgfS64pZSFrTuWff/4ZgEuXLrFu3TpmzZrFsWPHmDRpEhs3bizyIIXi88033/DVV18xfvx4vLy8UFbO/yPx5s0bDAwMPlF0X4aymrNVN1aRlJ4kfa8oxzuMspaz4E7epEVEoGxsjN2u/Ptb56Ws5awolKqcZWbC8amy2xRK+eJ9ZK0f8TlfZ/ny5TRu3Jg6deowZcoUXFxcUFRU5MqVKzx48AB3d/c8z3VwcGDTpk0cO3YMW1tbNm/ezJUrV7C1tS3kXYCfnx/p6enUqlULTU1NtmzZgoaGBjY2NoUuUxCKityVin///Rd7e3sADh06RJs2bejbty+1a9embdu2RR6gULwUFBTw9fWlZs2a+Pn5MWDAgHyPDw8Pl37+QsGUxZwFRQex5/EemW3ydH8qazlLi4gg7fXHTQ9a1nJWFEpVzh6fgJC/ZbeV4pYKTU1jVFQ0OHJ6yye7poqKBpqaxnKdU6FCBS5fvsy8efOYPHkyz58/R01NjcqVKzN27Fi+++67PM8dPHgwN27coEePHigoKNC1a1e+++47jhw5Uuh70NfXx9fXlx9++IH09HScnZ3Zu3cvRkZGhS5TEIqK3JUKLS0toqKisLS05PTp0wwbNgwAdXV1kpKSPnC28DmqUaMG3bp1Y+rUqXTv3j3f1UHl6cIiZCmLOVtzcw0ZmbJrAMiTh7KYM3nE+fsT538WzVq10KxZA2UjI5GzQihVOTs9O+e2Ulyp0NOzZsiQOyQkRHyya2pqGsu9mjZkDZReunQpS5cuzfOY3MY0qKmpsW7dOtatWyezffbs/36W69evl9l38uTJHOXs2vVflzexALHwOZO7UtGkSRO+//57XFxcCAoKonnzrNU879+/j5WVVZEHKHwas2fPplKlSixZsoSJEyfmeVytWrU+YVRfhrKYs9oWtTkSIvs2Tp6WirKYM4DMlBQSrl3P95iUp095NXUqmampvNmS9ZZX1aEC1rVqERsVhWbNmiiLt5YFUqo+Z3aN4cV7n43SVCnKhZ6edaEe8gVB+DzJXalYsGABs2fP5t9//+X333+X5vm+ceOGzKqQQvHIzMzk5MmT+Pn58d1336GhocGrV69ITk4mISEh31aG/Njb2zNs2DDmzp1L7dq18+xnHBgYSOXKlT/mFsqcspgz20xbjFWMiUjNegupoqBCc4PmXLt2rUDnl7WcqaemoACkv3nD0x495D4/5XEQKY+DeLNlKwAZ5cuTUaUy6ZWrkFG5EujpFXHEuTt+/Dj37t2jatWqGBgYoKamhrq6OhoaGmhoaKClpSV9aWtro6Ojg4aGRom1GFy9ejXXaUA/S41+yFpFO/3/Zw5S14OaYn0CQRA+HwpRUVFiLtGPFBsbi62tLTExMejq6hZ5+ZmZmVy9epUdO3awY8cOgoODcz3u6tWr+Q4a+5CIiAgcHByIiYkpdBmCAKCgokDlVZVRVMlqnXg44SEpL/OfRrEsO2VfAfP3ppEsCiEpKVxKiGd7dDSB78ynX9yUlJRIT08v8LE6Ojro6emhp6cnLSqmr6+PgYEBBgYGGBoaYmBgQOJtczJTldDQUaHduGro6Oh8VIUkICCA2rVrF/r8TyrqCSyrnvV3dT0YeQ205BsfAFn/X+np6RESElIs/1/lJiUlhYiICGxsbFBXV/8k1xQEoWgkJSXx9OlTjI2NUVVVzfdYuVsqzp8/n+/+evXqyVukkIvcKhLGxsZ07NiRKlWqMHr0aDZt2iTzNrdSpUofdU1jY2MePHjAv//+m+cxz549w9paNFfLoyzm7F7cPeYHzwfASt0Kv7/85Dq/rOVMfcQIiHpDprIyGY6O+R6rEBWFYh6DujPMzcmoXPn/WykqY2ZoSBugTTHEnJvAwEB69eqFv78/9erVIzU1laSkJBITE0lMTCQ+Pp74+Hji4uKIi4vj7du3vH37ltjYWGJiYqSvN2/eEBQURHR0NJGRkbx584bk5GRm9tyGgbYJYWH/oqfXEBUVFYyNjTE2NsbExARTU1NMTU0xMzOTvszNzaW/v/8fYqlaUfuJ/39/t21YqAqFIAhCcZK7UtGmTc7/nt59UxQR8ekGXX2JLly4wJo1a/D395dqhh07dqRz5840adIEZWVlqQtJ5cqVpZaJZ8+ecf/+/WKPz8LCotivURoZGxvn+RDs4ODwyd4Ifi7OXTsn/b2xXWO5W9DKWs4eqaiSBqgYGeG4Z3e+x2YkJBA65DsSLl9G1cYma7B2rVpkVK6EgYPDpwn4A7K7NKmqqqKqqlokP8uEhAS2TrtC0ts0TEyM2b59O+Hh4URERBAeHk5YWBgvX77k1q1bvH79msjISMz0rfCuN4JnEQ959OIGMSkvMTYzwsLCAgsLC4yMjLC3t6d8+fJYWlpiaWmJqakpioqf4QDo4LP//d2uccnFIQiCkAe5KxXvd71JTU3l1q1bzJkzh8mTJxdZYGWVr68ve/fupWnTpowfPx4PDw/09PSIj4/n5s2bKCgoSD+DwMBA1NTUeP78Oe3atSc5ufhn35o4cSJz5swp9uuUNurq6jx48CDXikVgYGDp6WJRRAJeBUh/r20h/72XxZwVlKKmJla/rCH97VtUzMyk7QEBAdT+TCoVxUFTUxMlJSUgDSUFFarbN4Z8ZoNNSU7lwp4gkuPSqWxVA6/qPcgkg0TeEJYQQtC/tzh1YhcvX/9LWlqadJ6ysjLly5fHysoKa2tr6cvGxkb60tbWLv4bfldm5nuVikaf9vqCIAgFIHelIrc3Tl999RWqqqpMnjyZ06dPF0lgZZWXlxd79+7F2dkZNzc3TExMAGSa7VX+v+919iDH5ORkTIzVad+tP/8+f42puRnGJoVvGo9PzJoKVEsj59s6B2t7Js2ammN7YcoqyrgKQ1kpk7T0jx8gGvMmgr3bthAREVGmuuzkJS4ljrsRd4GsGZ88zErJQNhSRFFTE8VCTsrwJUhOSOPYb3flPk8BRTQxwlbTCNsKHjRz6IeprS76lqoo6iQSm/aaF6+eExoaSmhoKM+ePeOff/7h339lKx7GxsbY2tpib2+PnZ0dFSpUwN7eHgcHBywtLf+/8lOEwgIhe+pVbTMwqVi05QuCIBQBuSsVeTExMeHx48dFVVyZtWPHDgCWLVvGsmXLsLW1pXHjxjRo0IBatWrl+oZMTTWVy2fHs3LtWVZsP0K9OvYc2j2s0DGkpGagoAAqyjkf3qPfxtGhWcG7MuRXVlHGVRgZGRlF1M1Bl0nDxhMWm3tLkcMX/PY4N13+6kJ6ZtYg3apGVdFR1ZG7jLKWM2VjY5k/C6Os5awoZGbC6+BY0lK0KOdkgGvlCrRtb4SiouzLhvT0dF68eMHTp08JCQkhJCSE4OBgnjx5QkBAAKGhoWRkZL30UFVVxd7eHkdHRypWrIiTkxMVK1akcuXK0ksiuW32/u/vdo1K/VSygiB8meSuVNy9K/t2KDMzk1evXrF06VKcnZ2LLLC8/PbbbyxfvpywsDCqVq3K/Pnz850ScO/evcydO5dnz55hb2/P9OnTpbU1suOfO3cuf/zxBzExMdSuXZuff/6ZChUqFPu9FERISAihoaH4+fmhqKiIq6urNDg7e3YVFeV0Vq49y6z5WesChIU/Z/OuxYW6nqGBKd807QnA4VObiXoTJrNfU6suCfEXiqSsooxLXrZWFalfq2WRlJUdm2JczsWPAOLi4srUaqcRif+NqypM1ycoezmz27Xzo8soSzlTUlGkQvX8H9DT0zIJuh4GucxvaFQ+qxKhapCKaz1HNLTzn9FESUkJKysrrKysaNCgQY79KSkpPH36lMePH0tfDx8+ZNeuXTx9+lSqcBgZGVGlShWqVq2Ks7MzLi4uVKtWDX19/fxvOCHyv79/QV2fnj179knHYeY39k0QhI8nd6WiUaNGKCgokJkp+5u6Ro0aLF++vMgCy83u3buZPHkyCxcuxMPDgzVr1uDt7c2lS5dyfQMUEBDAoEGDmDJlCl5eXuzcuZNevXpx+vRpqlSpAmS1CKxdu5ZVq1ZhY2PDnDlz8Pb25sKFC5/N1HfZlYeMjAyuX7/OzZs3AejevTsNGjRAVSWDw0f+63aWmpZCeGTeMzjlJzUthbiEWDIy0nkd/pzomHCZ/Xa6ToRHFuwB6ENlZVNIV0ApUZl0jTQylXKf4bigZRWUjo4BsXFviqSs1LQUYuPe5L4zIIC0w4fhm2/gMx8jcPVJLEGvE6lgpoGHfeEH1qam/1e5qmVeuMXFXr16hY2NTaFjKIvKUs7UtVRo3r/qB4+7f/Elpzbex9BCk3JOBpR30qeco75UiQgICPhghaIgVFVVcXR0xDGXmbuSk5N59OgR9+/f5969e9y7d49z586xbt06aRVmW1tb3N3d8fDwoFatWtSqVeu/rsbpaZD2znTAX0il4tmzZ1StWpWkpOIfC5hNXV2du3fvlqqKRUhICI6Ojly+fBk3N7eSDkcQ8iV3peLGjRsy3ysoKGBsbPxJHsBXrVpF79696dkz6431okWLOH78OJs3b2b06NE5jv/ll1/w9PRk1KhRAEyaNIkzZ87w22+/sWjRIjIzM1mzZg3jxo2jZcuWAKxevZqKFSty8ODBz3Yxv+y3XsnJyZw+fVr6vihEx4Sz/8g6oqLDSEvL/c17UZal8VoLi38sUUpTIl05nZf1n5NoFl+scQFER4ez8U/foikrJqus5p7VZHf8+CP4+lIBYMYMGD8e5s//6OsVB59dT1hxNFT6foSXFVM75TMKNg9vkt6Qlvlf33M3U7eiCE8QCqVSHQsqVDdFRa2IxzjIQU1NDWdn5xwt+ampqTx48ICbN29y/fp1rl27xvz584mNjUVBQYFq1arx1Vdf0aWBA3Wzm1sUlMDA9tPfRDGIiIj4pBUKyJpvX96xb/379+ePP/5g9uzZjB8/Xtq+b98+vL29pYqhIAiFqFRYWVkVRxwflJKSws2bNxkzZoy0TVFRkcaNG3P58uVcz7l8+TLDhsmOLWjatCmHDh0C4OnTp7x+/ZomTZpI+3V1dfHw8ODy5ct5ViqSk5NJfmchqbdv3xb2tj5abhUKRQV9tNXqFKq8uPgYzl+4jUW5VDq17oGhganM/szMBOpWH12gsqLehHHx2nHS0lL5+qucZWWkpHNjyBmpJUYpXQmbS/a4/dIERVUlucqS178vg/G/sK9Iyop6E8aR01tITnln0cCAAPD1lT3Q1xc6dvzsWiyuPomVqVAArDgaSqvqxnK3WPwb9y+KCopkZGagoqiChrJGoWKqVatwLRxlmchZ7vKrUJRkzlRUVKTKRvaLsoyMDB48eMCFCxc4e/Ysu3btIuTIS3Z21kBJUQGU1Uos3rJMXV2dBQsWMGjQIAwMDEo6HEH4bBWoUvHLL7/Qp08f1NXV+eWXX/I9dsiQIUUS2PsiIyNJT0/P0c3JxMSEhw8f5npOWFgYpqayD4ympqaEhWX1oX/9/wtI5VZm9jG5Wbx4Mb7vPzACV65cQUtLC3d3dwIDA0lMTERHRwc7Oztu3boFgI2NDRkZGYSGZj3Eubm58fjxY+Li4tDS0pJmdurfvz/3798nOTkZLy8vIOvn4OXlhbq6OuvXr0dZWZnx48dz584d9u/fL8URHBLN/yYcyTP+ghg8uDVxyU3RSc9ERyuJpy+yF4nKwEA3iTexmigqZFLV8RX3HpuRnqGIvk4iBnoJBD/P6teto/kAbZ0kDAwrEZdsTyXjaO4/MSU1TQld7SS0U16QnvjOqruZkJ6YzsuQilSrk0zQM2OSU5TR1kxGR+cBpqbDMTBMQVVNHRRMeR2ZNQC4sv1rgv81JClZBU2NFKzMo3kQnPVzNzeJBeBVeNbDcUW7MEJf6ZOcXpHy5Y3R09PndVTWGgpmRm9RUsrgRZgeAI424bwM1yUuQQ011TQqWEdw77E5ACaGcaippvH8lT7JKYmoqp4mMVGTgIAAVFRUcM/jMxl0+DAmlSsTFhZGZGQkSkpK1KhRg8uXL5ORkYGJiQmGhoY8ePAAACcnJ968eUN4eDgKCgrUqlWLq1evkpaWhqGhIWZmZgQGBgJZA3Xj4uJ49eoVkPXAdOPGDVJSUtDX18fS0pI7d+4AYG9vT1JSEi9evODfqGRUFTPxrpyIgUYGz2OVOPtMjacPbpAWroaNjQ3p6ek8f/4cgOrVq/Pw4UPi4+PR1tbGwcFBasG0srLCQMWAyJRI1BXUSUxMJDg4mLdv36KhoUHlypWldVbKly+PqqqqNEWyi4sLoaGhREdHExcXx1dffSW9MDA3N0dLS4ugoCAAqlSpwqtXr4iKisrKt7s7AQFZ09iampqip6fHo0ePgKxFISMiIoiIiEBRUZGaNWtK+c5eOC17jRdHR0diYmKkf/+1a9fm2rVrpKamYmhoiLm5Offu3QOgQoUKxMfHS/muWbMmt27dIjk5GX19faysrLh9+zYAdnZ2pKSkSAtLfszvCCcnJ65fvw4gzTT09OlTYmJiaNiwISEhIcTGxqKurk7VqlW5evUqAOXKlUNdXZ0nT54A4OzszPPnz4mOjkZVVRU3NzcuXbok5VtbW1uafKNy5cq8fv2aqKgolJWV8fDw4NKlS2RmZmJiYoKBgQEPHz6U8vj8+XNSU1OlfF+5coX09HSMjIwwNTWVPrOOjo7ExsZKv4vfzbeBgQHlypWTxvFVqFABZXVQ0VQgUymV9PR07ty5Q1JSEnp6elhbW0v5trW1JS0tTfrMuru7c//+fRISEtDW1qZChQrcvHmTmJgYXFxcgKzuOACurq4EBQURFxeHpqYmlSpVkj6zlpaWKCsrExISIn1mnz17RkxMDOrq6jg7O3PlyhUga00fTU1N6TNbtWpVXrx4wZs3b3J8Zs3MzNDV1eXRo0dERUWhoaGBkpIS6urq7L2fxsu4TCx1FUhBledPnnzU74iXL18iyMfT05OgoCDmz5/PvHnzcj1m9+7dzJgxg8ePH2NhYcHw4cOll6D+/v40a9Ysxznffvst69evx8HBgadPn+bYn1cryJ07d/jpp584d+4cWlpaNGvWjIULF2L8ERM9CEJRUIiKisq9E/s73NzcOHXqFIaGhvn26VNQUJD+sytqL1++pGrVqhw5ckTm7dK0adP4559/OHHiRI5zzMzMWLVqlUyLw7p16/D19eXBgwcEBATwzTffcO/ePczNzaVj+vXrh4KCAuvXr881ltxaKlxcXIiJifnoRZ48PT05derUR5VhZ6vP8CGFb6l4HHwbi3JxubZUPHvljLX5nQKVld26EB0Tnn9LRVJ61mBKBVBSV8q3pSKvsuRVHC0VTb9aS8NGg7I2BgRAnVx+BhcvfpYtFd/My/nv9vBP1Qs1tsJzhydhCWGYappysvPJQsUUEBAg1qmQ0+eQs2vXruHh4cHVq1flXvCwJJRkzrInOXm3+9OVK1ekCoulpSVfffUVX3/9Nd1ezEAx7hXolINxgR913djYWPT09AgJCflkC0ympKQQERGBjY2N1FX62rVrJZL7gIAAuT6b/fv3JyYmhm+//ZZvv/2WwMBALC0tZbo/Xb16lXr16jF16lQ6d+7MhQsXGDlyJMuXL6dPnz6kpKQQFRUllXn//n3atGnDsmXL6NevH+Hh4VKLfXp6Ol27dkVFRYXTp0/nGFMRHR1NlSpV6N+/P7169SIxMZGJEyeSlpbG8ePHizxfgpCUlCQtxvzu8ga5KVBLxbvjKN4fU/GpGBkZoaSkRHi47KDa8PBwzN5ZAOpd77ZKZHu39SL7vPDwcJlKRXh4eL4zWampqaGmVnLN0EpKSqSnp6OgoED16tVRU0vnwoWb0v6MzGjikgvZUqEM9eqWJyo6mSOnt+TYbWbWmXPndxS4OFPj8igrq+RaFoBGrXfGVCil87zWU+7/dbtQZcnDUN+syMoCUFZWQU1V778NtWtnjaF4t0Xrxx8/uwoFgIe9LiO8rGS6QI382uqjBmt/rA/OhiPkIHImv0+Rs+zKw/379wkMDOTu3bvcvXuXO3fuEBmZNauTrq4u1atXp2PHjtSqVYs6derIDrpfOLPY4xTy1759e1xdXZkxYwa//vqrzL4lS5bQtGlTJk2aBGS1HgUGBrJo0SL69OmDqqqq9IwRGRnJkCFD6Nu3L/369QNke0uMGTOGV69eceFC7rMsrlq1Cjc3N2bNmiVt+/XXX7Gzs+Phw4c4OTkV6X0LgjyKbJ2K4qaqqoqrqytnz56lVatWQFb/U39/fwYNGpTrOTVr1uTs2bMMHTpU2nbmzBlq1qwJZHUzMDMzw9/fX2oCj42N5erVq9I/9s9BdiUCspr1XVxcOHDgAFu3bqVmzZoEB11m29ZF/Lbh0kdfS1/PhLZfDyAjI53dB9fmmBnpzZu/i6wsgESzeILbPfzg7E8FKUse+vomtG85sGjK0jOhY6vBxCS+V7mdPx86diT59m3UXFw+ywpFtqmd7GlV3bhIZn8qCpaWliV6/dJI5Ex+RZWzzMxMoqKiCAoK4vHjxzx69IhHjx7x4MEDHj58SGxsVjdMFRUVHB0dqVq1Kt9//700paydnR0KYu2Jz97cuXNp3rw5Y8eOldl+//592rZtK7OtXr16LFu2jPT0dGkxxNTUVLp06YK1tTWLF+ec9v3XX39lw4YNnD17Ns81TW7dusWZM2dyrRA/efJEVCqEElWgSkV27bsgZs+eXehgPmTYsGEMHz4cNzc33N3dWbNmDQkJCfTo0QOAoUOHYmFhwdSpWSs+DxkyhDZt2rBixQpatGjB7t27uXHjhvSPWUFBge+++46FCxdSoUIFaUpZc3NzqeJS0gwMDGjUqBENGjSgfv36mJmZcefOHQ4cOICGRtYgWAUFBRbM6syLV8EcOhyOirIqJkaFW2TJ0MAUbc2sB0ozE0tUlGWbugyNhxAVkf+4moKWVZRxyctI3xRdbYMiKcvQIKusmMRcdtauzQ0o8W4pBeFhr1vilYlsd+7cKRU5+5yInMlPnpwlJCRIi98FBwcTEhLCkydPpK+YmP8majA1NcXR0REXFxe8vb2pWLEilSpVokKFCtK4OaH0adiwIS1atGDy5Mn07t1b7vOHDx/O8+fPOX/+PMrKso9fZ86cYfTo0WzatIlq1arlUULWejStW7dmzpw5OfZZWFjIHZMgFKUCVSqyB79lu3nzJunp6dIKrkFBQSgqKhb7HModO3YkMjKSuXPnEhYWhrOzMzt27JC6Mz1//lxmheTatWuzdu1a5syZw6xZs7C3t2fTpk3SGhUAo0aNIj4+njFjxhATE0OdOnXYsWNHia1R0aFDB06dOkX//v3x9vbGycnpg2+wUtOUSEpKZfNv4/nt9/O4u1niUb3w89Vnr1ydvdjcu24/tOCbxmNyOUv+sooyrsLIyMgosrISE1PIyBAPCwDGGsYyfwrC5y4lJYUXL17w/Plznj9/TmhoqPT17NmzHIu0KSsrY21tjZ2dHTVq1KBLly5UqFCBChUq4ODgUPRjFbRNZf8USszs2bOpUaOGTItApUqVOH/+vMxx58+fx8nJSWqlWLx4MTt37uTs2bM5Fql8/PgxXbt25aeffqJDhw75Xr969ers2bMHW1vbHBUTQShpBfpEvjuz0MqVK9HW1mbVqlVS81t0dDQjRoygTm4DU4vYoEGD8uzudODAgRzb2rdvT/v27fMsT0FBgYkTJzJx4sSiCvGjnD17FoCYmBjS0tI+cHSW5BQVajbypX23HugZuHDqOpy6HlvoGOITs6ap1dJQzLFPRyuTI+cKPoVufmUVZVyFoayUSVq6bIUtKiKS5JSUHMeqqapiaJz7asUxbyLYu20L+/Z75brf3l7+9R5Ks+2tt390GQXN2aNHj3Kd0llHRyfXhci+ZGXtc1YQSUlJvH79mlevXvHq1StevnzJixcvePXqFS9evJCmFX9/rJ6Ojo60graHhwcdO3bExsZG+ipfvrz0sPhJDPH/dNcS8uXi4kL37t1ZsWKFtG3MmDHUrVuX2bNn07lzZy5evMiqVaukBYFPnjzJhAkTWLZsGcbGxtKMcRoaGqiqqtKhQwfc3NwYOHCgtA+QGeuZbejQoaxbt45evXoxbtw4DA0NCQoKYvv27axdu/bTfi4F4T1yV3NXrVrFzp07Zfrz6evrM3HiRLy9vRkxYkRRxlfmtGjRgh07dnD06FF27dqFlZUVzZs3p2nTplSsWBFtbW3pIert27ekpKRkDWCPSGLFwlXFHl/jxo3x9xf/wb1PXV09z+n8PvUCT1+CguTs0aNH+fYffvjwYZmqWHzpn7PMzEwSEhKIjIyUviIiIggPD5e+wsLCCAsL4/Xr14SFhcl0SYKs8WlmZmaUK1cOCwsLXF1dqVixIuXLl6d8+fJYWlpiaWmJnp5eHlEIRSV70dxPvaJ2UUy7On36dHbs+G/CEnd3d7Zu3cqMGTOYPXs2FhYWTJ8+nT59+gDwzz//kJ6ezvDhwxk+fLh03rfffsvUqVO5f/8+9+/fz7EoX25TypYrVw5/f38mTpxIy5YtSU5OxsbGhhYtWsj01BCEkiB3peLt27fSjBXvioyMJC4urkiCKst69OiBu7s7FSpUICAggB07drB7927Wr19PhQoV6Ny5szQzVeXKlalUqRKVKlXi4cMHMs3zhZWamppvn9/w8HAWLVr00df5HAUGBtKrV68892/atInKlSvnus/Y2DjPVVpfvHhRYotGllYFydmHFp0syUUpS8Ln/DlLTU0lMTGR+Ph46evt27fSV2xsLDExMdJXdHQ00dHRvHnzhqioKKKionjz5k2uD6CqqqqYmJhIX7a2ttSuXRtTU1PMzMwwMzPD3NwcCwsLjI2NZd7kfg7T8JZV1tbW3L17t0j+3yqo/H5P5yW3qeVtbW2Jj4+X2daxY0c6duyYaxlTp06VxnrmJr9VuW1tbXPsd3R0lKnUCMLnQu5KRatWrRgxYgQzZ86U5nq+evUq06ZNo3Xr1kUeYFmjqakp5bVFixa0aNGCVatWcfr0af7880/Wrl0rzXedvaiVn58fZ86c4cKFC2hqahb62jExMTg7OzN69Gi++uqrXI959epVnrNSlGXZi6vl5v79+2JwppwKkrPsBb0Ku/9L8zl8zkaPHg0gLfSVkpJCUlKSNHtdfnR0dNDT00NfX1/608bGBjc3N4yMjDAwMMDIyEj6yl64UFtbW8ycVEpZW1vL/ZAvCMLnq0CL370rISGBqVOnsnnzZqn2rKysTK9evZgxYwZaWlrFEujnLDY2Fltb2yJZ/O5DUlNTmTJlCvPnz8+x72MXnJo0aRILFy6UWdhPEARBXt7e3tSoUQM1NTXU1dXR0NBAQ0MDTU1NtLW10dLSQltbGx0dHXR1ddHS0iqRvuBpaWllbrDr57L4nSAIpYM8i9/JXanIFh8fL638aWtrWyYrE9k+ZaUCst6KHz16FFtbWzQ0NFi5ciWHDx/m8ePHhW6p+Pfff3F0dGTkyJF07do1z+O+5MV1Pqb7U36+5JwVl4LkrLh+XqXV5/A5S0xMJCQkBC8vryLpu17cbt68iaura0mH8UmJSoUgCPIo8hW1c6OlpUXVqlULe7rwEYyNjenZ87+pUM3NzVFTU/uork/Tpk1DS0uLSZMm5fsfTWpq6ke1hpRmlStXLtS9l+WcFVZR5KywP6/S6nP5nNWvX7+kQyiwL31wuyAIwqdUqErF9evX2bt3L8+fP88xgGjjxo1FEpjw6dy5c4cNGzawZMmSD765+lRvtkqCjo7OR+3Py5ecs+JSkJwV18+rtBKfM/mJnAmCIBQduSsVu3btYtiwYTRt2pTTp0/z1VdfERQURFhY2GezCrUgn59++gk7OzuGDBnywWNtbW2LP6AS4ujoyMOHD4t83YMvOWfFpSA5K66fV2klPmfyEzkTBEEoOnJXKhYvXszs2bMZOHAg1tbWzJ07FxsbG8aMGYOZmVlxxCgUozNnznDw4EG2b9/+wb5yALdu3fqip2AsjgfRLz1nxaGgOStrFYf8iM+Z/ETOBEEQio7cK6WEhITQokULAFRUVEhISEBBQYGhQ4eKrk+lTEZGBj/88AM1a9akc+fOJR2OIAiCIAiCUErJ3VKhp6cnLXJnYWFBYGAgVapUISYmhoSEhCIPUCg+O3bs4MqVK5w5c6bA87zb2NgUc1RfHpEz+YmcyU/kTH4iZ4IgCEVH7paKevXqcfr0aQDatWvHhAkT+P777xk0aBCNGzcu8gCF4pGSksLEiRNp3bq1XD+3gixiJcgSOZOfyJn8RM7kJ3ImCP+5f/8+9evXR1tbGw8Pj5IORyiF5K5U+Pr6SkvRjxs3jmHDhhEeHk6bNm1YtmxZkQcoFI81a9YQEhLCvHnz5Drv+fPnxRTRl0vkTH4iZ/ITOZOfyJnwIa9eveL777/HyckJLS0t7OzsaN++PadOnSrS63h6ejJ27NgiLVNePj4+aGlpcffuXY4dO5brMf3790dFRYVhw4bl2Ddy5EhUVFTo379/cYcqfKbk7v5kYGAg/V1RUZHRo0dL3ycmJhZJUELxiomJwcfHh/79+4u1RgRBEAQhFyEhITRu3Bh9fX3mzZuHs7MzqampHDt2jFGjRnHnzp2SDjGHlJSUAk26kpugoCBatmz5wW6BVlZW/PnnnyxcuBANDQ0ga82Xbdu2YW1tXahrC18GuVsqcpOcnMzKlSupXr16URQnFDNfX18SEhKYMWOG3OeKn7H8RM7kJ3ImP5Ez+YmclT7Xgt+yMyCMa8E5p5IuaiNHjkRBQYHz58/TsWNHnJycqFq1KmPGjOHcuXPScdHR0QwePBgLCwsMDQ1p3rw5N2/elPb7+Pjg4eHBpk2bcHBwwMjIiJ49e0rTYffv35+zZ8+yfPlyVFRUUFFRISQkBMhaR6p169bo6+tTvnx5+vTpQ0REhFS2p6cno0aNYuzYsZibm9OyZctc7yUjI4NZs2Zha2uLlpYWHh4eHD16VNqvoqLCtWvXmDVrFioqKvj4+OSZl+rVq2NpacmePXukbXv27MHKygo3NzeZY48ePUrjxo0xNjbGzMyMdu3aERQUJO1PSUlh1KhRWFlZoa2tTYUKFZg/fz4AmZmZ+Pj4YG9vj5aWFtbW1jIvsoXPT4ErFcnJyfj4+NC0aVO8vLw4ePAgAJs3b6Z69eqsXr2aoUOHFlugQtH4999/Wbx4MWPHjqVcuXJyn//w4cNiiOrLJnImP5Ez+YmcyU/krHSZvSeE1gtuMcrvEa0X3GL2npBiu1ZUVBRHjx5l6NChaGlp5divr68v/b1bt26Eh4dz4MABAgICqF69Ol5eXkRFRUnHPHnyhP3797N371727dvH2bNn8fX1BbKm6q9Tpw4DBgwgNDSU0NBQrKysiI6OpkWLFri5uXHx4kX++usvwsLC6N69u0wsf/zxB6qqqvj7+7Ny5cpc72fZsmUsXryY+fPnc+3aNVq0aEGHDh149OgRAKGhoVKFKTQ09INdsfr27Yufn5/0/e+//06fPn1yHBcfH8/o0aO5ePEiR48eRVFREW9vbzIyMgBYsWIFf/31F1u3buXu3bv4+flJLSW7d+9m6dKlrFq1isDAQHbu3Imzs3O+cQklq8Ddn+bOncvvv/9O48aNuXz5Mv369aNHjx5cuXKFmTNn0r59e5SUlIozVqEITJs2DS0tLcaPH1+o8+Pj44s4oi+fyJn8RM7kJ3ImP5Gz0uNa8FtWHv9XZtvK4//yjZsR7nY6RX69x48fk5mZScWKFfM97ty5c1y+fJkXL16gpqYGZPUG2L9/P7t27WLQoEFAVkvBunXr0NHJirVnz56cOnWKmTNnoqenh6qqKpqampibm0tlr1q1Cjc3N2bNmiVt+/XXX7Gzs+Phw4c4OTkB4ODg8MHxkYsXL+aHH36ga9euQNYz3ZkzZ1i2bBnLly/H3NwcJSUltLW1ZWLIS8+ePZk8eTJPnz4F4Pz582zevJmzZ8/KHJc9Bvfd+C0sLLh37x7Ozs48e/YMBwcH6tevj4KCgkzXq2fPnmFubo6npycqKipYW1tTq1atD8YmlJwCVyr27dvH6tWr+eabb7h37x4NGzYkLS2Nv//+u8DTkQol686dO2zYsIElS5agq6tbqDK0tbWLOKovn8iZ/ETO5CdyJj+Rs9LjSVjuYzafhCUWS6UiMzOzQMfdunWLuLi4HIv/JiYm8uTJE+l7W1tbqUIBYG5uTnh4+AfLPnPmjEyrSLYnT55IlQp3d/d8y4mNjeXFixfUq1dPZnu9evW4detWvufmxcTEhJYtW7Jx40YyMzNp2bIlxsbGOY579OgRM2bM4NKlS0REREgtFKGhoTg7O9O7d2+++eYbqlatSosWLWjVqhXNmzcHwNvbm+XLl+Pk5ESLFi345ptvaN26NcrKcg8HFj6RAv9kXrx4gaurKwBVqlRBTU2NYcOGiQpFKfLTTz9hZ2fHkCFDCl2Gg4NDEUZUNoicyU/kTH4iZ/ITOSs97E015Nr+sRwdHVFQUODBgwf5HhcfH4+FhQUnTpzIse/dysD7D8IKCgrSA3Ze4uLiaN26NXPmzMmxz8LCQvp7bt2zPoW+ffvy/fffA+Q5+2eHDh2wtrZmzZo1WFhYkJGRgZubGykpKUBWhejRo0ccOXKEkydP0r17dzw9Pdm+fTtWVlbcvXuXkydPcuLECUaOHMnChQs5deoUKioqn+w+hYIr8JiK9PR0mRkFlJWVS+yDLMhSUlIiJCQEHR2dfL8OHjzI3LlzCz0zBMCNGzeKLvAyQuRMfiJn8hM5k5/IWenhbqfD8OblZbaNaFG+WFopAAwNDWnRogWrV6/OtZtcdHQ0kDVo+dWrVygrK+Pg4CDzldub+7yoqqrmWDelevXq3Lt3D1tb2xxly/P8paurS7ly5Th//rzM9vPnz1O5cuUCl/M+Ly8vUlJSSE1NpUWLFjn2R0ZG8uDBAyZOnEjTpk2pXLkyb968yTW+Ll268Msvv7BlyxZ2794tjUfR0NCgdevWLFmyhBMnTnDx4kVu375d6JiF4lXglorMzEyGDx8u9RlMSkpi7NixOT7YGzduLNoIhQ8aPHgwRkZGH2yuLVeuHN7e3p8oKkEQBEEoOpM62PKNmxFPwhKxN9UotgpFtmXLltG4cWPq1avHtGnTcHFxIS0tjRMnTrB27Vpu376Np6cnderUoVOnTsybNw9HR0devHjB4cOHadeuHTVq1CjQtWxsbLh06RIhISFoa2tjaGjI0KFDWbduHb169WLcuHEYGhoSFBTE9u3bWbt2rVzjWMeOHSvNpOTq6oqfnx83b978qGc2JSUl6QE/t1gMDAwwMjLi119/xdzcnNDQUCZOnChzzOLFi7GwsMDNzQ1FRUV27tyJubk5+vr6+Pn5kZ6eTq1atdDU1GTLli1oaGh8cMpboeQUuFLRrVs3me87d+5c5MEIhWNpaSk1QRY3KyurT3KdL4nImfxEzuQnciY/kbPSx91Op9grE9ns7e25dOkSc+fOZfz48bx8+RITExPc3d1ZsWIFkNWN6cCBA0yZMoWBAwcSHh6Oubk5DRo0yDHOIj9jx46lf//+VKtWjcTERB49eoStrS3+/v5MnDiRli1bkpycjI2NDS1atEBRUb4VAUaOHElsbCzjx48nLCyMypUrs2fPHhwdHeUq5335jc9UVFRk8+bNjBkzBjc3N5ycnFiyZAmenp7SMTo6Ovz88888fvwYJSUlatSowf79+1FUVERfXx9fX19++OEH0tPTcXZ2Zu/evRgZGX1UzELxUYiKiirYaCQhT7Gxsdja2hITE1PoAdClxatXrwo0M4TwH5Ez+YmcyU/kTH5lMWexsbHo6ekREhLyyf6/SklJISIiAhsbG9TV1T/JNQVBKBpJSUk8ffoUY2PjD3afL5LF74SyI3v6OKHgRM7kJ3ImP5Ez+YmcCYIgFB1RqRAEQRAEQRAE4aOISoUgl2rVqpV0CKWOyJn8RM7kJ3ImP5EzQRCEoiMqFYJcgoODSzqEUkfkTH4iZ/ITOZOfyJkgCELREZUKQS5v374t6RBKHZEz+YmcyU/kTH4iZ4IgCEWn1FQq3rx5w+DBg7G2tsbW1paRI0cSFxeX7/E//vgjtWrVoly5cri4uPDTTz8RGxsrc5yhoWGOr127dhX37ZRaGhrFs3rpl0zkTH4iZ/ITOZOfyJkgCELRKfA6FSVt8ODBvH79mt27d5OWlsaIESMYM2YMv/76a67Hv3z5kpcvX+Lj40PFihUJDQ1l3LhxvHz5Ej8/P5ljV6xYITNvsp6eXrHeS2n2MatvllUiZ/ITOZOfyJn8RM4EQRCKTqloqXjw4AEnT55k6dKl1KhRgzp16jBv3jx2797Ny5cvcz2nSpUqbNy4ka+//ho7OzsaNWrEpEmTOHr0KGlpaTLH6unpYWZmJn2JebTzdu3atZIOodQROZOfyJn8RM7kJ3ImCIJQdEpFS8Xly5fR09OjevXq0rYmTZqgqKjI1atXad26dYHKiY2NRUdHB2Vl2dseP34833//Pba2tvTt25eePXuioKCQZznJyckkJyfLlPvun1+y+Pj4MnGfRUnkTH4iZ/ITOZNfWcxZ9v1mZop1bwVBKFqlolIRFhaGiYmJzDZlZWUMDAwICwsrUBmRkZH8/PPP9OnTR2b7hAkTaNiwIZqampw+fZoffviB+Ph4hgwZkmdZixcvxtfXN8d2KyurAsUiCIIgCCUpLi5OdPX9zPj5+TFu3DgiIiJKOpRSISEhgb59+3LixAnevn1LeHg4+vr6JR1WmVailYoZM2awdOnSfI+5ePHiR18nNjaWrl27UrFiRX788UeZfT/88IP092rVqhEfH8/y5cvzrVSMGTOGYcOGSd9nZGQQHR2NgYFBvi0cpd3bt29xcXHh9u3b6OjolHQ4pYLImfxEzuQncia/spqzzMxM4uLisLCwKOlQPnvh4eFMnz6dw4cP8/r1awwMDKhWrRqTJk2ifv36AKioqLBz507atWsnV9kODg6MHDmS77//XtrWpUsXvvnmm4+KOSUlhWXLlrFlyxYeP36MpqYmTk5O9O/fn549e6KiovJR5Wfz8fFh3759XL16tUjKK4yNGzdy7tw5zp49i7Gxca6VZD8/PwYOHAiAgoIC5cqVw9PTk7lz52JqavqpQ/7ilWilYvjw4XTv3j3fY2xtbTE1NSU8PFxme1paGm/evPngh+Lt27d07twZHR0d/vjjjw/+g6pRowY///wzycnJqKmp5XqMmppajn1lqXaso6ODrq5uSYdRqoicyU/kTH4iZ/IrizkTLRQF06VLF1JSUli/fj12dna8fv2a06dPExUVVSzX09DQ+KgZyVJSUmjZsiW3bt1i+vTp1KtXD11dXQICAli0aBFubm64ubkVXcBFICUlBVVV1UKd++TJEypVqoSzs3O+x+nq6nL37l0yMjK4desWAwcO5OXLlxw6dCjHsenp6SgoKKCo+PkMOf4cY8pLiUZobGyMk5NTvl+qqqrUrFmTmJgYbty4IZ179uxZMjIy8PDwyLP82NhYOnXqhKqqKps3by7QAOzbt2+jr6+fZ4VCEARBEIQSEhCAwqZNEBBQrJeJjo7m3LlzzJ07lyZNmmBjY0OtWrX48ccfadOmDZDV2gDg7e2NioqK9H1QUBAdO3akfPny6OvrU6dOHU6ePCmV7enpydOnT/nf//6HioqK9LLTz88PY2NjmTj++usv6tSpg7a2Nubm5nh7e+cZ87Jly/j77785evQow4YNw83NDXt7e7p378758+dxdHQEsnpXzJ8/H0dHR3R0dHB3d5eZSt/f3x8VFRVOnTpF7dq10dXVpWHDhjx48ECKc+bMmdy6dUuKP3tWzejoaAYPHoyFhQWGhoY0b96cmzdvSmX7+Pjg4eHBunXrcHR0RFtbO8/72b17N66urmhpaeHg4MDixYtlcrh48WL+/vtvVFRUZGbwfJ+CggLm5uaUK1eOr7/+mhEjRnDy5EkSExOlnB84cIBq1aqhpaXFs2fPSE5OZvz48djY2KCnp0e9evXw9/eXynz69Cnt27fHxMQEPT09XF1dOXz4MJC1pMG3336LhYUFOjo6VK5cmd9//10mt9HR0VJZN27cQEVFhZCQECm/hYnpc1AqxlRUrFgRT09PRo8ezcKFC0lNTeXHH3+kY8eOUhPuixcv6NChA6tWrcLDw0OqUCQmJvLLL7/w9u1baaEjY2NjlJSUOHLkCGFhYdSoUQN1dXXOnDnD4sWLGT58eEneriAIgiAI71GcMAHFn3+Wvs/43//ImDu3WK6lra2NtrY2+/bto3bt2rm+aLxw4QLlypXjt99+w8vLCyUlJSBrvMrXX3+Nj48PampqbNq0ifbt23P37l2sra3ZsWMHHh4eDBw4kAEDBuQZw6FDh/D29mbChAls2LCBlJQUjhw5kufxW7ZswdPTU2ZSm2zvVl7mz5/Pli1bWLlyJQ4ODvz999/06dMHExMTGjVqJJ0zZcoUFixYgLGxMcOHD2fQoEGcPXuWLl26cPfuXY4dOybFk9361a1bNzQ0NDhw4AB6enr8+uuveHl5ce/ePQwNDYGsSteePXv4888/pZy97+rVq3Tv3p2pU6fSuXNnLly4wMiRIzE0NKRPnz7s2LGDiRMncvfuXXbs2CFXa4e6ujoZGRnSTKAJCQksWLCANWvWYGRkhKmpKaNGjSIwMJDNmzdjYWHBvn37aNWqFdevX8fR0ZFRo0aRkpLCqVOn0NLSIjAwUKogTZs2jcDAQA4cOICxsTFBQUEkJiYWOL7CxvQ5KBWVCoC1a9cyfvx4OnTogIKCAm3atGHevHnS/rS0NB49eiT94G7duiX19Xu/NePGjRtYW1ujrKzMunXrmDx5MpmZmdjZ2TFr1ix69+796W6sFFFTU2P8+PGiFUcOImfyEzmTn8iZ/ETOSpmAAJkKBYDizz+T0b491K5d5JfLfj747rvvWLt2LdWrV6dRo0Z06dKFatWqAUgTyOjr62Nubi6d6+rqiqurq/T9jBkz2LdvHwcOHGD48OEYGhqipKQktT7kZe7cuXTp0oVp06bJlJ2Xx48f07hx43zvKzk5mXnz5nHkyBHq1q0LgL29Pf/88w+//vqrTKVi5syZ0vfjx4+nbdu2JCUloaGhgba2NkpKSjLxnzt3jsuXL/PixQvp35Wvry/79+9n165dDBo0CMjq8rRhw4YcE/C8a8mSJTRt2pRJkyYB4OTkRGBgIIsWLaJPnz4YGhqiqamJqqpqvjl836NHj/j111/x8PCQxlKlpqayfPlyKbfPnj3Dz8+PJ0+eUK5cOQDGjh3L0aNH8fPzY9asWTx79oyOHTvi4uIi5TBbaGgobm5u1KhRA8jqxi+vwsT0OSg1lQoDA4M8F7oDsLa2lunn2KBBgw/2e2zWrBnNmjUrshi/dGpqavz0008lHUapInImP5Ez+YmcyU/krHRRePQoz+2ZxVCpAOjYsSMtW7bk3LlzBAQEcOTIEX7++Wd++eWXHDNJvisuLg4fHx8OHz7My5cvSUtLIzExkdDQULmuf/PmzXxbMt5XkGmCHz9+TEJCQo4B4SkpKTnGW2Q/MAPSg3tYWBjW1ta5ln3r1i3i4uIwMzOT2Z6YmMiTJ0+k721sbPKtUADcv3+ftm3bymyrV68ey5YtIz09Pc8WjtzExMSgr69PRkYGSUlJ1K9fn19++UXar6qqKlUUAe7cuUN6ejpVqlSRKSc5ORkjIyMARowYwYgRIzh+/Dienp506NBBKmPIkCF06dKF69ev07x5c9q2bUu9evUKHG9hY/oclJpKhSAIgiAIZVNmHt078tpeVNTV1aUXkJMmTWLw4MH4+PjkW6kYP348J0+eZP78+VSoUAENDQ26du1KSkqKXNeWd9C2o6OjNO4hL3FxcQDs379feuOd7f1Wu3cntsme2TIjIyPPsuPj47GwsODEiRM59r07mY2mpma+MRY1HR0dLl26hKKiIhYWFjnyqqGhITNzZ1xcHEpKSgQEBOSovGR3cRowYAAtWrTg0KFDnDhxgvnz5+Pr68uIESP4+uuvCQoK4vDhw5w4cQIvLy+GDh2Kr6+vNNj63QpgampqjpgLE9Pn4PMfSi4IgiAIQtlWuzYZ//ufzKaMH34olq5P+alcuTLx8fHS9yoqKqSnp8scc/78eXr37k379u1xcXHB3Nycp0+fyhyjqqqa7wM6ZLUUnDp1qsCxde/enZMnT3L9+vUc+1JTU4mPj6dKlSqoqanx7NkzHBwcZL7kWWtLVVU1x31Xr16dV69eoaysnKPs9wegf0ilSpU4f/68zLbz58/j5OQkVysFgKKiIg4ODtjb2xeooubm5kZ6ejrh4eE57uPdrlZWVlYMGTKEHTt2MGbMGNatWyftMzExoXfv3mzcuJGFCxfy22+/AUh5ePnypXTsuwPZPzamkiYqFYIgCIIgfPYy5s4l7dw50jdsIO3cOTLmzCm2a0VGRtK8eXM2b97MrVu3CA4OZufOnSxcuFCa/Qmy+sufOnWKV69e8ebNGyCrxWDPnj3cuHGDmzdv8u233+aoQNjY2PD333/z77//5rnY3ZQpU9i+fTszZswgMDCQ27dvs2DBgjxjHjVqFPXq1cPLy4tVq1Zx8+ZNnjx5wo4dO6hfvz6PHj1CR0eHsWPH8r///Y+NGzcSFBTEtWvXWLFiBRs3bixwfmxsbAgJCeHGjRtERESQnJyMp6cnderUoVOnThw/fpyQkBDOnz/PlClTuHLlSoHLhqz1wE6dOsXs2bN5+PAhGzduZNWqVYwZM0aucgrDycmJ7t27069fP/bs2UNwcDCXLl1i/vz50jS0Y8eO5dixYwQHB3Pt2jXOnDlD5cqVAZg+fTr79+/n8ePH3L17l0OHDlGpUiUAqfI2c+ZMHj16xKFDh1iyZEmRxPQ5EJUKQRAEQRBKh9q1yezVq9hbKLS1talVqxZLly6ladOmuLm5MX36dAYMGMCyZcuk43x9fTl58iR2dnbUrFkTgAULFmBgYECjRo3o0KEDzZs3zzEj07Rp0wgJCaFixYp5LkTYuHFjtm3bxoEDB6hRowYtWrTg8uXLecaspqbGkSNH+N///sevv/5KgwYNqFu3LitWrGDEiBHSeg4zZsxg4sSJ+Pr64uLiQuvWrTl8+DB2dnYFzk/Hjh3x8vKiefPmWFhYsG3bNhQUFDhw4AANGzZk4MCBVKlShV69evH06dMc4yw+xN3dna1bt/Lnn3/i5ubGjBkzmD59er7dzorSunXr6NWrF+PHj6dq1ap4e3tz5coVqTUnPT2dUaNGSflzdHRk+fLlQFYrzuTJk3F3d6dp06YoKSmxefNmIKtl648//uD+/fu4u7uzYMECZsyYUSQxfQ4UoqKiPjyyRxAEQRAEoRBSUlKIiIjAxsamQOtFCYLw+UhKSuLp06cYGxt/cOpe0VIh5GvhwoV4eXlRvnz5Ak+LlpmZyZw5c6hcuTLlypWjQ4cOBAUFFW+gn5E3b94wePBgrK2tsbW1ZeTIkdLguLy0adMGQ0NDma+xY8d+oog/vd9++w1XV1csLCxo1qyZNP1zXvbu3Uvt2rWxsLCgfv36HD9+/BNF+vmQJ2dbtmzJ8XnK623ol+r8+fN0796dKlWqYGhoyMGDBz94zrlz52jSpAnm5uZ4eHiwZcuWTxCpIAjCl0FUKoR8paSk0K5dO/r161fgc5YtW8batWtZuHAhx48fR1NTE29vb5KSkoox0s/H4MGDuX//Prt372bbtm1cuHChQP1Ae/fuTWBgoPQ1ffr04g+2BOzevZvJkyczfvx4Tp8+jbOzM97e3oSHh+d6fEBAAIMGDaJnz56cOXOGli1b0qtXL+7du/eJIy858uYMsmY8effzVJDBgF+S+Ph4nJ2d8fX1LdDxT58+pVu3bjRo0AB/f3++++47vv/+e5mVkAVBEIS8ie5PQoFs2bKFiRMnSsvI5yUzM5MqVaowbNgwRo4cCUBsbCwVK1ZkxYoVdOrU6RNEW3IePHhA3bp1OXnypNSH9sSJE3Tt2pU7d+7k+ba4TZs2ODs7M7eYVof9nDRr1gx3d3fpYS8jIwMXFxcGDRrE6NGjcxzfv39/EhIS2LZtm7StefPmuLi4sGjRok8VdomSN2cF/fdaVhgaGvLHH3/QqlWrPI+ZPn06x44dk5lxZsCAAcTExLBz585PEeYXS3R/EoTSS3R/EkrM06dPef36NU2aNJG26erq4uHhke8Asy/F5cuX0dPTkxmU16RJExQVFT/YxWfnzp04ODhQr149fHx8SEhIKO5wP7mUlBRu3rwps+qroqIijRs3zvPzcfny5RyrxDZt2rRMfJ6gcDmDrDf11apVw9nZmZ49exIYGPgpwi21yvrnTBAE4WOJxe+EIvX69WuAHKtlmpiYEBYWVhIhfVJhYWE57l1ZWRkDA4N8779Tp05YWVlhYWHB3bt3mT59Oo8fP5Zrir/SIDIykvT09Fw/Hw8fPsz1nLCwMExNTWW2mZqalonPExQuZw4ODixfvpyqVasSGxvLihUr+Prrrzl//jzly5f/FGGXOnl9zt6+fUtiYqLcC5EJgiCUNaJSUQbNmDGDpUuX5nvMxYsXcXJy+kQRff4KmrPC6tu3r/T3KlWqYGZmRvv27QkODpZrmj9BAKhVqxa1atWS+b5OnTr8/vvvTJo0qQQjEwRBEL5UolJRBg0fPpzu3bvne0xBZ3p6X/Zc1OHh4TKrPIaHh0tzZJdGBc2ZqalpjsGzaWlpvHnzJsdb0Px4eHgA8OTJky+qUmFkZISSklKOHIWHh+c5j3lurRK5vVX+UhUmZ+9TUVHBxcWF4ODg4gjxi5DX50xHR0e0UgiCIBSAqFSUQcbGxtJS8UXNxsYGMzMz/P39cXFxAbIGal+9elWuGaQ+NwXNWc2aNYmJieHGjRu4ubkBcPbsWTIyMqSKQkHcvn0bQKZi9iVQVVXF1dWVs2fPSoNmMzIy8Pf3Z9CgQbmeU7NmTc6ePcvQoUOlbWfOnJEWmvrSFSZn70tPTycwMJBmzZoVZ6ilWs2aNXNMVVyWPmeCIAgfSwzUFvL1/Plzbt++zfPnz8nIyOD27dvcvn1bZt2F2rVr89dffwGgoKDAd999x8KFCzl8+DD37t1j2LBhmJub5zvzypeiYsWKeHp6Mnr0aK5evcrFixf58ccf6dixozTz04sXL6hdu7Y0cDs4OJgFCxZw48YNnj17xuHDhxk2bBj16tWjatWqJXk7xWLYsGFs3LiRrVu38uDBA8aNG0dCQgI9evQAYOjQofj4+EjHDxkyhJMnT7JixQoePnzIvHnzuHHjBgMHDiypW/jk5M2Zr68vp06dIiQkhJs3bzJkyBBCQ0P59ttvS+oWPrm4uDjp9xVkTSKR/bsMwMfHR6ai2q9fP54+fcq0adN4+PAh69atY+/evTLHCIIgCHkTLRVCvubOncvWrVul77NnR9m/fz8NGjQA4NGjR8TGxkrHjBo1ivj4eMaMGUNMTAx16tRhx44dZWYqwbVr1zJ+/Hg6dOiAgoICbdq0Yd68edL+tLQ0Hj16RGJiIpDVNcXf3581a9aQkJBA+fLladOmDePGjSupWyhWHTt2JDIykrlz5xIWFoazszM7duyQujM9f/4cRcX/3nfUrl2btWvXMmfOHGbNmoW9vT2bNm2iSpUqJXULn5y8OYuOjmb06NGEhYWhr6+Pq6srR44coVKlSiV1C5/cjRs3aNu2rfT95MmTAejevTsrV67k9evXUgUDslpZt23bxqRJk/jll18oV64cS5cuxdPT85PHLgjZPD09cXV1LTPTZ8vL39+fZs2aER4ejr6+fkmHU+aJdSoEQRAEQSg2pX2digsXLtCkSRO8vLzYv3//J712aa9U+Pn5MW7cOCIiIoql/JSUFKKiojAzM0NBQaFQZYSEhODo6IiJiQkPHjxAR0dH2ufh4UG7du2YOnVqUYVc6oh1KgRBEARBEIrAhg0bGD58OH///TcvXrwo6XDkkp6eTkZGRkmH8dHyug9VVVXMzc0LXaF419u3b0tt5e1zISoVgiAIgiAIuYiLi2PHjh0MGTKEli1b5rp20F9//UWdOnXQ1tbG3Nwcb29vaV9ycjITJkzAzs4OLS0tKlWqxPr166X9d+7coXXr1ujr61O+fHn69OmT71v95ORkxo8fj42NDXp6etSrVw9/f39pv5+fH8bGxhw4cIBq1aqhpaXFs2fPePPmDX379sXExARdXV1at27No0ePcpx38OBBqlatiq6uLl27diUhIYGNGzfi4OCAiYkJo0ePJj09vUDx+Pv7M3DgQGJiYlBRUUFFRUUa+1XY+3ifv78/KioqREdHy5x37NgxXFxc0NfXp1WrVrx8+TLPnGYbPnw4S5YsyXcNpA/l8enTp7Rv3x4TExP09PRwdXXl8OHD0v4P/bwzMjL4+eefqVSpElpaWtjb2zN37lxp/+3bt2nevDk6OjqYmZnx3XffyYxx7d+/P506dWLRokVYWVlhZmbGyJEjSU1NLdDP7GOJMRWCIAiCIHxSSuuaQlwJLGCpbUr6gFMFPnzHjh1UrFiRihUr0qNHD8aNG8ePP/4ovRk/dOgQ3t7eTJgwgQ0bNpCSksKRI0ek8/v168fFixdZvHgx1apVIyQkRHqIjI6OpkWLFvTv35+ff/6ZxMREJk6cSPfu3XPMRJZt1KhRBAYGsnnzZiwsLNi3bx+tWrXi+vXrODo6ApCQkMCCBQtYs2YNRkZGmJqa0qtXLx4/fsyePXvQ0dFh4sSJtG3bllu3bqGioiKdt2LFCjZt2kRcXBydO3fG29sbfX199u/fT3BwMF26dKFevXp06dLlg/HUrVuXhQsXMmPGDO7evZuVfm3tj7qPgkhISGDRokVs2LABRUVF+vbty/jx4/njjz/yPa9r166cOHGCWbNmsWzZslyPGTBgQL55HDVqFCkpKZw6dQotLS0CAwOley7Iz3vSpEmsW7eOn3/+mfr16/Py5UsePHgAQHx8PK1ataJOnTpcuHCB8PBwhgwZwqhRo2QqqmfOnMHc3Jzjx48TFBREjx49cHV1lSY3KUjuC0uMqRAEQRAEodjkNqZCaakzCm8//Pa4qGXqWJD+/Z0CH9+oUSO8vb0ZNWoUaWlpWFlZsW3bNmnSkoYNG2JnZ5drC8bDhw+pWrUqR44cyXXA/5w5czh37hyHDh2Stj1//hw7Ozvu3r2Lk5OTzJiKZ8+e4eTkxJMnTyhXrpx0jpeXFzVr1mTWrFn4+fkxcOBArly5gqurK5A1mUqVKlXw9/enXr16AERGRmJnZ8f69evx9vaWzrt//z4VKlQAsmad27x5M//++6/0YNyqVStsbGxYtWpVgeN5f0xFYe8jN+8P1M7tPlavXs3s2bNlJmZ4V/aYisuXLxMWFkb79u25ffs2FSpUkBlTUZA8Vq9enY4dOzJlyhS5f94WFhZYWFiwdOlSBgwYkOP83377jYkTJxIcHIyWlhYAhw8fpn379jx79gwzMzP69+/P2bNnefDgAUpKSkDW5BSKiops3ry5QLl/nzxjKkRLhSAIgiAIn5a2KSXyRlO74ItmPnjwgMuXL7Nz504AlJWV6dy5M+vXr5cqFTdv3sz1ATB7n5KSEo0aNcp1/61btzhz5kyusxY9efIEJycnmW137twhPT09x8x3ycnJGBkZSd+rqqpSrVo16fv79++jrKxM7dq1pW1GRkY4OTlx//59aZumpqb0IA5Zi9na2tpKFQpAZoHXgsbzvsLeR0G9fx8WFhb5dml6V4sWLahfvz7Tp0/P0bJRkDyOGDGCESNGcPz4cTw9PenQoYN0Dx/6eUdHR5OcnEzTpk1zje3+/ftSV7Bs9erVIyMjg4cPH0qLoVapUkWqUEDWeld37mRVpAv7MysoUakQBEEQBOGTkqcLUknZsGEDaWlpWFtbS9syMzNRU1Nj2bJl6Onp5bva+odWYo+Li6N169bMmTMnx77sdY3eP15JSYmAgACZh0ZA5sFfQ0OjUAOXs7tBZVNQUEBZWTnHtuwB0wWN53O4j8zMgldhZ8+eTcOGDRk7dqzc1x4wYAAtWrTg0KFDnDhxgvnz5+Pr68uIESM++PN+8uSJ3NfLTW73/7E/s4ISlQpBEARBEIR3pKWlsWnTJnx9fWnevLnMPm9vb7Zt28aQIUNwcXHh1KlT9O3bN0cZzs7OZGRkcPbs2Vy7P1WvXp09e/Zga2ub4+E9N25ubqSnpxMeHi6tE1UQlSpVIi0tjYCAAJluOw8fPqRy5coFLqcw8aiqqsoM7P6Y+/hUatWqRYcOHZg0aZLM9oLm0crKiiFDhjBkyBBpjMSIESM++PN2dHREQ0ODU6dO5dr6ValSJTZu3Eh8fLzUWnH+/HkUFRVztGrlpbhzL2Z/EgRBEARBeMfBgwd58+YN/fv3x9nZWearQ4cObNiwAYApU6awfft2ZsyYQWBgILdv32bBggUA2Nra8u233zJo0CD27dtHcHAw/v7+7NixA4ChQ4cSFRVFr169uHz5MkFBQRw7dowBAwbkeBAHcHJyonv37vTr1489e/YQHBzMpUuXmD9/vkw//fc5OjrStm1bhg4dyrlz57h58yZ9+vShfPnyMgtEyqsg8djY2BAXF8epU6eIiIggISGh0PfxKfn4+HD69GkePnwobStIHseOHcuxY8cIDg7m2rVrnDlzRqpwfOjnra6uzg8//MCECRP4448/CAoK4uLFi9Ig7B49eqCurk7//v25c+cOZ86cYfTo0fTs2VPq+vQhxZ17UakQBKFYnDt3DkNDQ2JiYvI9ztXVldWrV3+SmL777ruPnof8xIkTNGrU6IuY+10QhNxt2LABT09P9PT0cuzr0KEDV69e5datWzRu3Jht27Zx4MABatSoQYsWLbh8+bJ07MqVK+nYsSMjR47E2dmZ7777jvj4eADKlSuHv78/6enptGzZkurVqzNu3Dj09fVRVMz98WzdunX06tWL8ePHU7VqVby9vbly5QpWVlb53s9vv/1G9erVad++PQ0bNiQzM5P9+/fn6Cojrw/FU69ePQYPHkyPHj2wsLDg559//qj7+FScnJzo27cvSUlJMts/lMf09HRGjRqFi4sLrVu3xtHRkeXLlwMF+3lPmjSJMWPGMGPGDFxcXOjZs6c0hkVTU5ODBw8SFRVF3bp16dq1K1999VWeM1XlpThzL2Z/EoQybPjw4WzduhXI6odpaWlJ165dGTt2bIGa4/OTkpLCmzdvMDU1RUFBgS1btjBx4kRCQkJkjouIiEBTUxNNTc2Put6H3Llzh3bt2nHz5s2P7jvq6enJ4MGD6dq1axFFJwhfrtK+orYglGViRW1BEArM09OTwMBArly5wvDhw5k/f770ZuVjqKqqYmZm9sGBdsbGxsVeoQBYu3Yt7dq1K5LBaN27d2ft2rVFEJUgCIIgfBlEpUIQyjg1NTXMzMywsrKif//+NG7cWFoBNDo6mqFDh2JnZ0f58uXp3LkzQUFB0rmhoaF0794dOzs7LC0tqVu3rrSIz7vdn86dO8eIESOIjY3F0NAQQ0ND5s2bB+Ts/vT8+XN69uyJlZUV1tbW9OvXT2Y6wHnz5tGoUSO2b9+Oq6srNjY2DBgwgLdv3+Z5j+np6ezfv5+vv/5aZrurqys///wzQ4cOxcrKimrVqnH48GEiIiKkGBo0aMD169dlzvv666+5fv06wcHBhcy6IAiCIHxZRKVCEAQZGhoapKamAlndo65fv86WLVs4evQomZmZdO3aVdr/ww8/kJyczMGDBzl37hzTp0+XmUM7W61atZgzZw46OjoEBgYSGBjIiBEjchyXkZFBz549efPmDQcOHGD37t08ffo0x0wYISEhHDx4kK1bt7Jt2zbOnz/P0qVL87ynu3fvEhsbi5ubW459q1evpnbt2pw5c4YWLVrw3XffMXToUDp37szp06exs7Nj6NChMlMSWlpaYmpqyoULFwqUU0EQBEH40okpZQVBALLmX/f39+fUqVMMGjSIoKAgDh8+zOHDh6XFftauXYuLiwsHDx6kffv2PH/+nDZt2kgL6dja2uZatqqqKrq6uigoKOQ7S4W/vz/37t3j+vXrWFpaArBq1Srq1avHtWvXcHd3B7IqHytXrkRHRweALl264O/vz+TJk3MtNzQ0FCUlJUxMTHLsa968uTQd5A8//MD69eulgXgAo0aNwsvLi7CwMJnYzc3NCQ0NzfNeBEEQBKEsES0VglDGHT16FCsrKywsLOjSpQsdOnTgxx9/5OHDhygrK1OjRg3pWENDQxwcHKRp9gYPHszChQv5+uuvmTt3Lnfv3v2oWB4+fEj58uWlCgVkzc2tp6cnM7WflZWVVKGArJVfIyIi8iw3KSkJNTW1XMd3vLuyqKmpaZ7b3i9fXV2dxMTEgt6aIAiCIHzRRKVCEMq4Bg0a4O/vz5UrV3jx4gWrVq3KtQtTbnr37s21a9fo2rUrgYGBNG3a9JMMYM5vxdDcGBoakpCQQEpKSr5lZVc6ctv2fvlv3rzByMhI/uAFQRAE4QskKhWCUMZpaWlhb2+PpaWlzDSyTk5OpKWlceXKFWlbVFQUjx8/pmLFitI2S0tL+vXrx8aNGxk+fDgbN27M9TqqqqofXNvBycmJf//9l+fPn0vb7t+/T0xMjMw15eXi4gLAgwcPCl3Gu5KSkggJCaFatWpFUp4gCIIglHaiUiEIQq4qVKhAy5YtGT16NBcvXuTOnTsMGTIECwsLWrZsCcCECRM4efIkT58+5ebNm/z99984OTnlWp6VlRVxcXH4+/sTGRlJQkJCjmOaNGlClSpVGDJkCDdv3uTq1asMGzaM+vXrU7169ULfi7GxMa6urly8eLHQZbzrypUrqKmpUbNmzSIpTxAEQRBKO1GpEAQhTytWrMDNzY1u3brh5eVFZmYm27dvl7oHZWRkMH78eOrUqUPnzp1xcHCQVkx9X+3atenXrx8DBgzA0dEx11VAFRQU2Lx5M/r6+rRu3ZoOHTpgY2PDunXrPvpevv32W3bs2PHR5QDs2rULb2/vT7K+hiAIZZenpydjx44t6TA+W/7+/qioqBAdHV3SoQiIFbUFQSgjEhMTqVWrFuvWraNWrVqFLicyMpJatWpx6tQpbGxsijBCQfgylfYVtS9cuECTJk3w8vJi//79n/Tanp6euLq6smjRok963aLi5+fHuHHj8p1I42OkpKQQFRVVoIVWP2T37t2sXLmSGzdukJ6ejp2dHZ06dWLYsGEYGhri5+fHwIEDAVBUVERXVxdHR0datmzJyJEj0dPTk8rq378/f/zxB4MGDWLVqlUy1xk5ciRr1qzh22+/Zf369R8V86cgVtQWBEF4j4aGBqtXryYqKuqjynn27BkLFiwQFQpBKCM2bNjA8OHD+fvvv3nx4kVJhyOX9PT0D45lKw3yug9VVVXMzc0/ukIxZcoUevToQY0aNThw4AA3btxgwYIF3Lp1i02bNknH6erqEhoaSkhICGfPnmXgwIFs2rSJGjVq5PhsWFlZ8eeff8rMEpiUlMS2bduwtrb+qHg/V6JSIQhCmdGgQYMcq2rLq3r16nTs2LGIIhIE4XMWFxfHjh07GDJkCC1btsx1Ioq//vqLOnXqoK2tjbm5Od7e3tK+5ORkJkyYgJ2dHVpaWlSqVEnm7fSdO3do3bo1+vr6lC9fnj59+uT7Vj85OZnx48djY2ODnp4e9erVw9/fX9rv5+eHsbExBw4coFq1amhpafHs2TPevHlD3759MTExQVdXl9atW/Po0aMc5x08eJCqVauiq6tL165dSUhIYOPGjTg4OGBiYsLo0aNJT08vUDz+/v4MHDiQmJgYVFRUUFFRwcfH56Pu433vd3/KPu/YsWO4uLigr69Pq1atePnyZZ45vXTpEvPmzcPX15f58+dTr149bG1tadasGX/++Se9e/eWjlVQUMDc3BwLCwsqV65M//79OXv2LHFxcfz0008y5VavXh1LS0v27NkjbduzZw9WVla5LsT6JRCVCkEQBEEQhFzs2LGDihUrUrFiRXr06MHvv/9OZuZ/vcYPHTqEt7c333zzDZcvX+bo0aMyEzj069eP7du3s3jxYm7fvs2qVavQ1tYGIDo6mhYtWuDm5sbFixf566+/CAsLo3v37nnGM2rUKC5evMjmzZu5du0a3t7etGrVSqaCkJCQwIIFC1izZg03b97E1NSUAQMGcO3aNfbs2cPff/9NZmYmbdu2JTU1Vea8FStWsGnTJg4ePIi/vz/e3t4cOXKE/fv38/vvv/Prr7+ya9euAsVTt25dFi5cKL3dDw0NlcaHFPY+CiIhIYFFixaxYcMGTp06RWhoKOPHj8/z+K1bt6Ktrc3QoUNz3a+vr5/v9UxNTenevTt//fWXTIULoG/fvvj5+Unf//777/Tp06dA91EaiRW1BUEQBEH4pHoc7kFkYuQnv66RhhFbvtlS4OM3bNhAjx49APDy8mLgwIGcPXuWxo0bAzB37ly6dOnCtGnTpHNcXV2BrMU8d+zYwZEjR/D09ATA3t5eOm7VqlW4ubkxa9Ysaduvv/6KnZ0dDx8+zDGT3rNnz/Dz8+PJkyeUK1cOgLFjx3L06FH8/PykclJTU1m+fLkUx6NHjzhw4AD+/v7Uq1cPgI0bN2JnZ8e+ffuklpXU1FRWrFhBhQoVAOjYsSObN2/m33//RVtbmypVqtCkSRPOnDlDly5dChSPnp6e9Hb/Y++joFJTU1m5cqV0H0OHDmX27Nl5Hv/48WPs7OxyrH8kj4oVK/L27VsiIyNlKj89e/Zk8uTJPH36FIDz58+zefNmzp49W+hrfc5EpUIQBEEQhE8qMjGSsMSwkg4jXw8ePODy5cvs3LkTAGVlZTp37sz69eulSsXNmzcZMGBAruffvHkTJSUlGjVqlOv+W7ducebMmVzfhD958iRHpeLOnTukp6dTpUoVme3JyckyC3GqqqrKrKFz//59lJWVqV27trTNyMgIJycn7t+/L23T1NSUHsQBzMzMsLW1lVpWIOutfHh4uFzxvK+w91FQ79+HhYUFYWF5f9bebXkqrOwy3h/bYWJiInWby8zMpGXLlhgbG3/09T5XolIhCIIgCMInZaRRMqvRy3PdDRs2kJaWJjOoNjMzEzU1NZYtW4aenh4aGhp5np/fPsgar9G6dWvmzJmTY5+FhUWuxyspKREQEICSkpLMvncf/DU0NAo1cPn9N/UKCgoyC6Jmb8seMF3QeD6H+8iv4uDo6Mg///xDampqoVsr7t+/j66ubq6Vqb59+/L9998D5DqV+pdEVCoEQRAEQfik5OmCVBLS0tLYtGkTvr6+NG/eXGaft7c327ZtY8iQIbi4uHDq1Cn69u2bowxnZ2cyMjL4v/buPybLev/j+JNb5g9+SUqJICGiBB4YkpSmBg2YOE1+eewbTjCg4yCFvD0sHYHL2y38cVwOJV1CzFytvitJHSc7Gk07IYh864QLo9CJBiqIpohIt9zfP1z3ORwpfyBg9Hps/sHnuq7P/b4+m9v9uj+fz3UdOnTIuvzpPwUFBVFcXMzYsWNv+fLenUmTJnHjxg2ampqYMWPGHd+Lr68vZrOZiooK6/KnCxcuUFtbi5+f3x33cy/1DB48+JZ9Bvd6H73l+eefZ8uWLWzdupWMjIxbjl+6dOk391WcP3+e999/n6ioKAyGW7cqR0ZG0tHRgY2NDTNnzryfpT9wtFFbRERE5D+UlJRw8eJFkpOT8ff37/IvNjaWoqIi4OajSD/44ANWr15NTU0N1dXVbNiwAYCxY8eSkJDAX/7yF3bv3s3Jkyc5ePCg9SWcaWlptLS0sHDhQiorK6mrq+Mf//gHKSkpt3wRB/Dx8SE+Pp6kpCSKi4s5efIkR44cYd26dfz973//1XuZMGECUVFRpKWl8c9//pN//etfLFq0CHd3d6Kiou55jO6kHk9PT1pbWyktLaW5uZm2trZ7vo/eMmXKFDIzM3nllVdYuXIlhw8f5tSpU5SWlvL88893eeKXxWLh7NmzNDY2UlNTQ1FRESEhIQwfPrzbGSeAQYMGUV1dzTfffHPLzMxAo1AhIiIi8h+KiooIDw/v8kKzX8TGxlJVVcU333xDaGgo77//Pnv37iU4OJiZM2dSWVlpPTc/P5+4uDjS09Px9/cnNTWVq1evAuDm5sbBgwe5ceMGs2fPJigoiL/+9a84Ozt3+4s3QGFhIQsXLuSVV17hT3/6E3/+8585evQoHh4ev3k/BQUFBAUFERMTw9NPP43FYmHPnj092px8J/VMmzaNxYsXs2DBAkaPHs3f/va3Ht1Hb8nNzWXnzp0cOXKEOXPmEBgYSGZmJgEBAV0eKXv58mU8PDzw9PTk6aefZvv27SQkJFBZWdntkrVfODk54eTk1Be30q/0Rm0RERHpNb/3N2qL/JHpjdoiIiIiItJnFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpEREREfsXZs2cxGo34+vri4OCAu7s7ISEhbNu2jba2tv4uT+SBYdvfBYiIiIg8iE6cOEFoaCjOzs6sWbMGf39/hgwZwrFjxygoKMDd3Z25c+fedb8dHR0MHjy4FyoW6T+aqRARERHpRnp6Ora2tpSXlzN//nz8/PwYN24cUVFR7Nmzh2effZYXX3yR6OjoLtf9/PPPuLm58fbbbwMQHh5ORkYGy5cvx9XVldmzZwNw6NAhnnrqKezt7fHw8CArKwuz2Wzt56OPPmLSpEk4OjoyatQoIiMjuXr1qvV4UVERgYGB1uszMjKsx+rr64mLi8PZ2ZkRI0YQHx/PuXPnrMdNJhOTJ0/mrbfewsvLCycnJ+Lj4/npp5+63EthYSEBAQE4ODjg7+/P1q1b798Ay4CiUCEiIiLyXy5cuMD+/ftJS0vD3t6+23NsbGxITk7m008/pbGx0dpeUlJCW1sbzz33nLVt586dDB48mIMHD5Kfn8+PP/7I3LlzCQ4Opqqqii1btlBUVMTrr78OQGNjIwsXLuSFF16gurqaAwcOEBMTg8ViAWDbtm1kZGSQkpLCV199xa5du/D29gags7OTuLg4Wlpa+Oyzz/jkk084ceIECxYs6FJ/XV0dH374IcXFxZSUlPD111+zdOlS6/H33nuP1atXYzKZqK6uZs2aNbz22mu8884792eQZUDR8icRERHpU/XP/Q83LjT3+ecOGunCo//7wR2d+8MPP2CxWPDx8enS7urqSnt7OwBpaWnk5uby2GOP8e6775KZmQnAjh07mDdvHg4ODtbrxo8fz9q1a61/5+Tk4OHhQV5eHjY2Nvj6+tLQ0EBWVhbZ2dk0NjZiNpuJjY3F09MTgICAAOv1ubm5GI3GLrMTTzzxBAClpaUcO3aM77//Hg8PD+DfsxqVlZXW89rb2ykqKsLd3R2ATZs2ERUVxYYNG3B1dcVkMrF+/XpiY2MB8PLyoqamhu3bt5OYmHhH4yh/HAoVIiIi0qduXGjGfO58f5dxT8rKyujs7CQxMZHr168DkJSURGFhIZmZmZw7d459+/axf//+Ltc9/vjjXf4+fvw4U6ZMwcbGxto2bdo0WltbOXPmDIGBgYSFhREUFMTMmTOJiIhg3rx5PPTQQ5w/f56GhgbCwsK6rbGmpgYPDw9roACYOHEizs7OHD9+3BoqHn30UWugAJg6dSqdnZ3U1tbi6OhIXV0dixcvJjU11XqO2Wxm+PDh9zh6MpApVIiIiEifGjTS5YH/3PHjx2NjY0NtbW2X9nHjxgEwbNgwa1tCQgKvvvoqhw8fpry8HC8vL2bMmNHlul9bQvWrtQ4axL59+ygrK+PAgQPk5+ezatUqvvzyS1xcen/8WltbgZvLrJ588slbahP5bwoVIiIi0qfudAlSfxo5ciQRERG8+eabLFmy5DdDwciRI4mOjmbHjh2Ul5ezaNGi2/bv6+tLcXExFovFOltRVlaGo6MjY8aMAW7u2Zg+fTrTp08nOzsbb29vPv74Y4xGI2PHjqW0tJRnnnnmlr79/Pw4ffo0p0+fts5WfPvtt1y6dAk/Pz/refX19TQ0NODm5gZARUUFBoMBHx8fRo0ahZubGydPnrxlL4ZIdxQqRERERLqxefNmQkNDmTp1Kjk5OQQEBGAwGDh69CjfffddlyVNycnJREdHc+PGDRISEm7bd2pqKnl5ebz88su89NJL1NbWYjKZWLZsGQaDgYqKCj7//HMiIiJ45JFHOHLkCE1NTdZQkJOTw5IlS3j44YeZNWsWV65coaysjKVLlxIeHo6/vz+JiYls3LgRs9lMeno6ISEhBAcHW2sYOnQoycnJrFu3jitXrmA0Gpk/fz6urq4ArFq1CqPRiJOTE5GRkVy/fp2qqiouXryI0Wi8z6Mtv3cKFSIiIiLd8Pb2prKykrVr15Kdnc2ZM2cYMmQIfn5+LF++vMteg/DwcEaPHs3EiROtv/z/Fnd3d/bu3cuKFSuYPHkyI0aMICkpiaysLACcnJz44osvyMvL4/Lly3h6erJ+/XpmzZoFQGJiIu3t7eTl5bFixQpcXFyIi4sDbs5w7Nq1i2XLlhEWFobBYCAyMpJNmzbdcn8xMTFERUXR0tLCnDlz2Lx5s/V4SkoKdnZ2bNy4kZUrV2Jvb4+/v3+XzeEiv7BpaWmx9HcRIiIiMjB1dHTQ3NyMp6cnQ4cO7e9yek1rayuenp4UFBRYn5b0IDOZTOzevZuqqqr+LkUeYO3t7Zw6dQoXF5fbvrBRMxUiIiIi96izs5Pm5mbeeOMNnJ2d7+kN2yIDgUKFiIiIyD2qr69nwoQJjBkzhsLCQmxt9dVK/pi0/ElERER6zR9l+ZPIQHQ3y58MfVSTiIiIiIgMUAoVIiIiIiLSIwoVIiIiIiLSIwoVIiIiIiLSIwoVIiIiIiLSIwoVIiIiIiLSIwoVIiIiIiLSIwoVIiIiIr/i7NmzGI1GfH19cXBwwN3dnZCQELZt20ZbW1t/lyfywNBrH0VERES6ceLECUJDQ3F2dmbNmjX4+/szZMgQjh07RkFBAe7u7sydO/eu++3o6Ljti8REfm80UyEiIiLSjfT0dGxtbSkvL2f+/Pn4+fkxbtw4oqKi2LNnD88++ywvvvgi0dHRXa77+eefcXNz4+233wYgPDycjIwMli9fjqurK7Nnzwbg0KFDPPXUU9jb2+Ph4UFWVhZms9naz0cffcSkSZNwdHRk1KhRREZGcvXqVevxoqIiAgMDrddnZGRYj9XX1xMXF4ezszMjRowgPj6ec+fOWY+bTCYmT57MW2+9hZeXF05OTsTHx/PTTz91uZfCwkICAgJwcHDA39+frVu33r8BlgFFoUJERETkv1y4cIH9+/eTlpaGvb19t+fY2NiQnJzMp59+SmNjo7W9pKSEtrY2nnvuOWvbzp07GTx4MAcPHiQ/P58ff/yRuXPnEhwcTFVVFVu2bKGoqIjXX38dgMbGRhYuXMgLL7xAdXU1Bw4cICYmBovFAsC2bdvIyMggJSWFr776il27duHt7Q1AZ2cncXFxtLS08Nlnn/HJJ59w4sQJFixY0KX+uro6PvzwQ4qLiykpKeHrr79m6dKl1uPvvfceq1evxmQyUV1dzZo1a3jttdd455137s8gy4Ci5U8iIiLSpz5a939cu9LR5587zHEw81Y8fkfn/vDDD1gsFnx8fLq0u7q60t7eDkBaWhq5ubk89thjvPvuu2RmZgKwY8cO5s2bh4ODg/W68ePHs3btWuvfOTk5eHh4kJeXh42NDb6+vjQ0NJCVlUV2djaNjY2YzWZiY2Px9PQEICAgwHp9bm4uRqOxy+zEE088AUBpaSnHjh3j+++/x8PDA/j3rEZlZaX1vPb2doqKinB3dwdg06ZNREVFsWHDBlxdXTGZTKxfv57Y2FgAvLy8qKmpYfv27SQmJt7ROMofh0KFiIiI9KlrVzq4eqnvQ8X9UFZWRmdnJ4mJiVy/fh2ApKQkCgsLyczM5Ny5c+zbt4/9+/d3ue7xx7uGmePHjzNlyhRsbGysbdOmTaO1tZUzZ84QGBhIWFgYQUFBzJw5k4iICObNm8dDDz3E+fPnaWhoICwsrNsaa2pq8PDwsAYKgIkTJ+Ls7Mzx48etoeLRRx+1BgqAqVOn0tnZSW1tLY6OjtTV1bF48WJSU1Ot55jNZoYPH36PoycDmUKFiIiI9Klhjv2zSfluPnf8+PHY2NhQW1vbpX3cuHE3+xo2zNqWkJDAq6++yuHDhykvL8fLy4sZM2Z0ue7XllD9mkGDBrFv3z7Kyso4cOAA+fn5rFq1ii+//BIXF5e76utetLa2AjeXWT355JO31Cby3xQqREREpE/d6RKk/jRy5EgiIiJ48803WbJkyW+GgpEjRxIdHc2OHTsoLy9n0aJFt+3f19eX4uJiLBaLdbairKwMR0dHxowZA9zcszF9+nSmT59OdnY23t7efPzxxxiNRsaOHUtpaSnPPPPMLX37+flx+vRpTp8+bZ2t+Pbbb7l06RJ+fn7W8+rr62loaMDNzQ2AiooKDAYDPj4+jBo1Cjc3N06ePHnLXgyR7ihUiIiIiHRj8+bNhIaGMnXqVHJycggICMBgMHD06FG+++67LkuakpOTiY6O5saNGyQkJNy279TUVPLy8nj55Zd56aWXqK2txWQysWzZMgwGAxUVFXz++edERETwyCOPcOTIEZqamqyhICcnhyVLlvDwww8za9Ysrly5QllZGUuXLiU8PBx/f38SExPZuHEjZrOZ9PR0QkJCCA4OttYwdOhQkpOTWbduHVeuXMFoNDJ//nxcXV0BWLVqFUajEScnJyIjI7l+/TpVVVVcvHgRo9F4n0dbfu8UKkRERES64e3tTWVlJWvXriU7O5szZ84wZMgQ/Pz8WL58eZe9BuHh4YwePZqJEydaf/n/Le7u7uzdu5cVK1YwefJkRowYQVJSEllZWQA4OTnxxRdfkJeXx+XLl/H09GT9+vXMmjULgMTERNrb28nLy2PFihW4uLgQFxcH3Jzh2LVrF8uWLSMsLAyDwUBkZCSbNm265f5iYmKIioqipaWFOXPmsHnzZuvxlJQU7Ozs2LhxIytXrsTe3h5/f/8um8NFfmHT0tJi6e8iREREZGDq6OigubkZT09Phg4d2t/l9JrW1lY8PT0pKCiwPi3pQWYymdi9ezdVVVX9XYo8wNrb2zl16hQuLi63fWGjZipERERE7lFnZyfNzc288cYbODs739MbtkUGAoUKERERkXtUX1/PhAkTGDNmDIWFhdja6quV/DFp+ZOIiIj0mj/K8ieRgehulj8Z+qgmEREREREZoBQqREREpNdZLFoYIfJ7czf/bxUqREREpNfY2tpisVi4du1af5ciInfp2rVrWCyWO9orpN1EIiIi0msMBgN2dnY0NTUBMGzYMOsbpEXkwfTLDwFNTU3Y2dlhMNx+HkKhQkRERHqVs7MzAOfPn1egEPmdsFgs2NnZWf//3o6e/iQiIiJ9orOzE7PZ3N9liMgdsLW1vaMZCuv5vViLiIiIiJXBYLjtYylF5PdJG7VFRERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRHFCpERERERKRH/h/m9G7xkIRbAgAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -344,12 +392,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -364,7 +412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -429,7 +477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -448,7 +496,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -457,7 +505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -478,12 +526,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data saved to aaaa.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "barometer_clean.export_measured_data(\"aaaa.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -498,12 +563,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -513,7 +578,7 @@
     },
     {
      "data": {
-      "image/png": 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cdin5EUIcuK655hoUReGHH37gzDPPpHv37vTp04cbb7yRhQsXxrzfpk2bOOecc8jLy6Np06aceuqprF+/3rr9xx9/5LjjjqN58+bk5uYyatQofvnll5BzKIrCiy++yOmnn05GRgbdunXjk08+qXHM69at4/vvv2fy5Ml0796dDz74IOKYl19+mT59+uB2u2ndujXXXnutddu+ffu46qqraNmyJWlpafTt25fPPvvMuv27775j5MiRpKen0759e6677jrKyspijmffvn1cfvnl5Ofnk5OTwzHHHMOSJYHVo2YG48UXXwzZqG/jxo2ceuqpZGVlkZOTwznnnMP27dsj7vfyyy/ToUMHsrKyuOaaa/D7/Tz44IO0atWKFi1acN9998U9nunTp3P33XezZMkSFEVBURSmT59er8eRCEl7Zy0qKgKgZcuWIde3bNnSui2aqVOnkpuba321b98+oeNsSmDzwQrcKCgcb/uJdkpgv59T7AvopGxDUZSEjkUIcQDTNPCUNf5XnM0o9+zZw5dffsmkSZPIzMyMuD0vLy/q/bxeL+PGjSM7O5tvv/2W+fPnk5WVxfjx4/F4PADs37+fiy++mO+++46FCxfSrVs3TjjhBPbv3x9yrrvvvptzzjmHpUuXcsIJJzBx4kT27NlT7binTZvGiSeeSG5uLn/605946aWXQm5/9tlnmTRpEldeeSW//fYbn3zyCV27dgVAVVUmTJjA/Pnz+e9//8vy5cu5//77sdvtAKxdu5bx48dz5plnsnTpUt5++22+++67kEAn3Nlnn82OHTv44osv+Pnnnxk8eDDHHntsyOMoLCzk/fff54MPPmDx4sWoqsqpp57Knj17mDdvHrNmzeKPP/7g3HPPDTn32rVr+eKLL/jyyy958803eemllzjxxBPZvHkz8+bN44EHHuBf//oXixYtims85557LjfddBN9+vRh27ZtbNu2zfqZdXkciXLA7fVz2223hWwBXlJSktBgpYWyz/o+DQ8vz1/HRfYKAGb4DyeXMo6y/87RtqW8sq81Pr+KQzIrQohw3nL4d5vG/7n/2AquyMAjXGFhIZqm0bNnz1qd/u2330ZVVV588UXrw9q0adPIy8tj7ty5HH/88RxzzDEh93nhhRfIy8tj3rx5nHTSSdb1l1xyCeeffz4A//73v3niiSf44YcfGD9+fNSfraoq06dP58knnwTgvPPO46abbmLdunV06tQJgHvvvZebbrqJv/3tb9b9DjvsMAC++uorfvjhB1asWEH37t0B6Ny5s3Xc1KlTmThxItdffz0A3bp144knnmDUqFE8++yzEVmE7777jh9++IEdO3bgdusZ+IcffpiPPvqI9957jyuvvBLQp0leffVV8vPzAZg1axa//fYb69ats97PXn31Vfr06cOPP/5ojVdVVV5++WWys7Pp3bs3Y8aMYdWqVXz++efYbDZ69OjBAw88wJw5cxg2bFhc48nKysLhcNCqVat6P45ESdo7qvmkBKe2zMvBT1g4t9tNTk5OyFcije8Y+D5L0Yt8nfgBGNgxnx9tAwA4yrYMgN+2FCd0PEIIkQh13QZkyZIlFBYWkp2dTVZWFllZWTRt2pTKykrWrl0L6H/Xr7jiCrp160Zubi45OTmUlpaycePGkHP179/f+j4zM5OcnBx27Ijd8XvWrFmUlZVxwgknANC8eXOOO+44Xn75ZQB27NjB1q1bOfbYY6Pef/HixbRr184KUqI9tunTp1uPKysri3HjxqGqKuvWrYt6fGlpKc2aNQu5z7p166znAqBjx44hb+4rVqygffv2IR+6e/fuTV5eHitWBNpiFBQUkJ2dbV1u2bIlvXv3xmazhVxnPmfxjqehHkeiJC2j0qlTJ1q1asXs2bOtiuOSkhIWLVrE1VdfnaxhRWhtDwQemeiZFIcRqLRtlsPYPqfB/96gv03/z5PpHyFEVM4MPbuRjJ8bh27duqEoSq0LZktLSxkyZAivv/56xG3mm9jFF1/M7t27+c9//kPHjh1xu90MHz7cmhqyhup0hlxWFAVVVYnlpZdeYs+ePaSnp1vXqarK0qVLufvuu0Ouj6am20tLS7nqqqu47rrrIm7r0KFD1ONbt27N3LlzI24LnjqLNrUWj2jPT3XPWbzjCZfox1FbCQ1USktLKSwstC6vW7eOxYsX07RpUzp06MD111/PvffeS7du3ejUqRO33347bdq04bTTTkvksGrF4Q8slc40MipmoILNQXmTXqiaQktlH80pxi6BihAiGkWJawomWZo2bcq4ceN4+umnue666yLehPbt2xf1zW3w4MG8/fbbtGjRImaGe/78+TzzzDNW5mPTpk3s2rUr6rHx2r17Nx9//DFvvfUWffr0sa73+/0cddRRzJw5k/Hjx1NQUMDs2bMZM2ZMxDn69+/P5s2bWb16ddSsyuDBg1m+fLlV01KTwYMHU1RUhMPhoKCgIO7H0qtXLzZt2sSmTZusrMry5cvZt28fvXv3jvs8dRmPy+XC7/fX+n6NKaFTPz/99BODBg1i0KBBANx4440MGjSIO+64A4BbbrmFv/71r1x55ZUcdthhlJaW8uWXX6bU0jJFC/wHZoVlVLA70VyZrNP0qao+tvX4qon+hRAilT399NP4/X4OP/xw3n//fdasWcOKFSt44oknGD58eNT7TJw4kebNm3Pqqafy7bffsm7dOubOnct1113H5s2bAT1b89prr7FixQoWLVrExIkTa8xm1OS1116jWbNmnHPOOfTt29f6GjBgACeccIJVVHvXXXfxyCOP8MQTT7BmzRp++eUXq6Zl1KhRHH300Zx55pnMmjWLdevWWcWqALfeeivff/891157LYsXL2bNmjV8/PHHMYtpx44dy/DhwznttNOYOXMm69ev5/vvv+ef//wnP/30U8zHMnbsWPr168fEiRP55Zdf+OGHH7jooosYNWoUQ4cOrfNzFM94CgoKrCTCrl27qKqqqvPjSJSEBiqjR49G07SIL3P5k6IoTJkyhaKiIiorK/nqq69izhUmi6IFAo9MKgENh2JmVJw0z3Lxu1YAQB9lvbU3kBBCHGg6d+7ML7/8wpgxY7jpppvo27cvxx13HLNnz+bZZ5+Nep+MjAy++eYbOnTowBlnnEGvXr247LLLqKystDIsL730Env37mXw4MFceOGFXHfddbRo0aJeY3355Zc5/fTTo063n3nmmXzyySfs2rWLiy++mMcff5xnnnmGPn36cNJJJ4V0QH///fc57LDDOP/88+nduze33HKLlWHo378/8+bNY/Xq1YwcOdL6oN2mTfSiaEVR+Pzzzzn66KO59NJL6d69O+eddx4bNmyIWOEafr+PP/6YJk2acPTRRzN27Fg6d+7M22+/Xa/nKJ7xnHnmmYwfP54xY8aQn5/Pm2++WefHkSiKVtcKqhRRUlJCbm4uxcXFCSms/ejpWzlt53PW5R6V07nB8T5/cXwKw6+Fcffx63//yaDCp3jPfzQtL3qZkd0SX1wkhEhdlZWV1sqTVMoQC9HYqnstxPv+Letoa6KFZkiyqMCBT79g00t8Bg0cAkCBUkSVVzIqQgghREORQKUGNi20yChTqQypUQGgqb7uvqNShMcvgYoQQgjRUCRQqUlYRqUJ+xlmM9a1u41UlRGo5CslqBWJbekvhBBCHEokUKmBEpZR+YfzDXrZNkFGMxhgbJyYlkOxLQ8AV8n6xh2gEEIIcRCTQKUGSlhGZZjNaIZ08hOQFaha3+XUq8Dd+0M7LQohhBCi7iRQqUF4oAKwps0p0OukkOuKXfqSLVd57A0VhRCHlgN8UaUQ9dYQrwEJVGoSNvWzWWvO4j63RRy236VnV5atWM6eMk/E7UKIQ4fZ1ry8vDzJIxEiuczXQHir/9o44HZPbmxmRqXS3YytFU5u9v6FG1pE9kmpSNe707ZW9nDGM/OZ+/fIds1CiEOD3W4nLy/P2hwuIyND9gEThxRN0ygvL2fHjh3k5eVht9vrfC4JVGpgFtNubH8a6wfdwjHb93NU1+YRxw3u2wc2QytlD+t3y6coIQ515i7w1e3+K8TBLi8vz3ot1JUEKjWwYdSo2Owc36cVx/eJ/oS3aNcFgNbK7sYamhAihSmKQuvWrWnRogVerzfZwxGi0TmdznplUkwSqNTAzKhoSg1Pdo6+6qclewPBjRDikGe32xvkj7UQhyoppq2BterHVsMfmqyW+DUFh6LSjOLED0wIIYQ4BEigUgMrUKkpo2KzU6zonWqbK9KdVgghhGgIEqjUwJz6UWrKqAAZTfT6lc7pUkwrhBBCNAQJVGqgmPUmSs1PlZapL1vO8u1N5JCEEEKIQ4YEKjWwdk+OI6OiZBmBin8vXtlFWQghhKg3CVRqoBBnMS1gM/b+aa6U8Ois1YkclhBCCHFIkEClJqoeqNhsNa/kVsxAhWLeWCSbEwohhBD1JYFKDcxiWpu95qfKZkz9NFNKqPD4azhaCCGEEDWRQKUGZqBijyOjYss2p36K8UiNihBCCFFvEqjUwOyjotjjmPrJ1AOVZtJHRQghhGgQEqjUxJr6iaMFdqa+WWFzSgAtgYMSQgghDg0SqNTAzKg44sioYPRRcStesqhI5LCEEEKIQ4IEKjUwA5W4MiquDCo1JwC5lCVyWEIIIcQhQQKVGigYxbTxZFSAfWQBkKdIoCKEEELUlwQqNTAzKvEGKsVaJgC5SmnCxiSEEEIcKiRQqYEdc9VPHFM/BGVUkEBFCCGEqC8JVKqhaRo2M1CJo4U+BDIqMvUjhBBC1J8EKtXQtKCMShwN3wD2aZJREUIIIRqKBCrVUIMyKtjie6rMqR+pURFCCCHqTwKVamgEMirxbEoIsM+Y+mnllD4qQgghRH1JoFKNkIxKnMW044b2BKCVSwIVIYQQor4kUKlGcI2KLc5iWiWjKQCZ6v6EjUsIIYQ4VEigUg1V04KKaeMLVFR3HgBZEqgIIYQQ9Zb0QOWuu+5CUZSQr549eyZ7WACoGrVenqym5QESqAghhBANIb4K0QTr06cPX331lXXZ4UiJYaGFZFTii+nMqZ9sTVb9CCGEEPWVEhGBw+GgVatWyR5GBFUDm6IBoCjxPVWuLD1QceMBbyU40xI2PiGEEOJgl/SpH4A1a9bQpk0bOnfuzMSJE9m4cWPMY6uqqigpKQn5SpSQjEqcq37cGTmBC1Uy/SOEEELUR9IDlWHDhjF9+nS+/PJLnn32WdatW8fIkSPZvz/6m/zUqVPJzc21vtq3b5+wsQXXqMS76icjzcV+LR2Ad+YvS9jYhBBCiENB0gOVCRMmcPbZZ9O/f3/GjRvH559/zr59+3jnnXeiHn/bbbdRXFxsfW3atClhY1PrsNdP00wX+9EDlVfnSqAihBBC1EdK1KgEy8vLo3v37hQWFka93e1243a7G2UsddnrJ81pp1RLBwWyFWn6JoQQQtRH0jMq4UpLS1m7di2tW7dO9lBCalSIM6MCsJ8MAHIoT8SwhBBCiENG0gOVm2++mXnz5rF+/Xq+//57Tj/9dOx2O+eff36yh2bUqOirflDif6pKjRqVLBomo6KqGsu2FOPxqXU+h6Zp/LJxLz9v2IumaQ0yLiGEECLRkh6obN68mfPPP58ePXpwzjnn0KxZMxYuXEh+fn6yhxbSmbYuGZVspWEyKi98+wcnPfkdN7+7pM7nmLNqB2c88z1nPvs9s1fsaJBxCSGEEImW9BqVt956K9lDiCkkUFHiD1T6d2kP6xc2WEbluXlrAfhkyVaeOH9Qnc7x/i9brO8//HULY3u3bJCxCSGEEImU9IxKKtOClifXJqOSk6c3fWvmrGyQcTji7IpbraDZHkWp/+mEEEKIxiCBSjWCV/3UJqOipOlN3zLVsgYZh8te/8hCDapLsUmkIoQQ4gAhgUo1VFW1WujXJqNiBirpWv1rVDw+la3F9c/MBAcq0eKUS6b9QMHkGWzaU/sx+/wqN76zmLd/jOwovGDtbv7y2s8UNcBjEEIIceiRQKUaquoLXKjFqh97ei4A2VTgV+u3wua9nzfX6/6m4GGEZ1T8qsbcVTsBOOu572t97i+WFfHBL1u49f3fIm47//8W8uXvRfzjw8jbhBBCiJpIoFINVfUHLtQio2IzAxWlvF5LigH2lnvqdX+TVk1GxacGxri9pKrW567w+ms8pi6ZGiGEEEIClWoowYFKLWpUHEagkkUFHn/9AhWbonC67VtmuG6ji7Kl5jvEUFNGpT4yXDU/N9K5RQghRF1IoFKNumZUHBkNl1GxKfCY61n62DYwyfFxtcdqmsaa7fvxRQmOgmtUwgOThgxUgs9VXWO5HSWV7C6tffYmFvOxhz+WWNfX5ryrt+9HredzFMumPeWUVvlqPrAe/Kr+HMT63UiUbcUV7CnzsHr7/pRqMmg+H/GMSdM0CnfU7XnbW+Zhy76KuH+WECI6CVSqodWxRkVx68W0WVTgrecbg0MN9GLppWysdgrltYUbOO6xb5j8QWQ9SPAb9Vcrtse8rS7SnYF2POWewHP25g/RN4ws9/g4/N+zGXLvVw32B/yl79Zx3GPfcNsHS0Ouf3pOIcc99g13flK3DSKfmF3I8Y99w70zVjTEMEOs31XGyAfnMHzq7AY/d7A7P1nGcY99w3GPfcPf3lqc0J9lKi73Mnzq1wy+ZxbHP/YNT8+JvndXMvzrI/35eGbu2hqPfeenTYx99BuufePXWv+cQffMYsT9X3PcY9/w2sINdRmqEAIJVKql+us29UOaGahU4vHW79Nyk4pAMa0THz+u3xPz2P98tQaIXoAbnNlp3yQj5DZfPQMVlyPwaxT8c56ZG/3NKXgFUFU9M06mR2etBuCdn0If+8Mz9ev/uzByRVI8HvtKv//L89fVY3TRfVu4C4D9lYnNqAQ/9hm/bUvozzIV7iwNuWz+P6SCN3/Qnw/zd6Y6z3/zBwBf/l5Uq58RHvw/M6fmoEgIEZ0EKtXw++s29YORUbEpGv6KknqNIcOzy/o+TykNCQrCVdcepTKo4DX8j2h9pzWCf25w4BErWeK0Bx5DuafmQtx41DfYSoqDeDrAGdb7x2FLvd498WTz6jrq8ALzNKf8qRWiruTVUw2/X/+kq6LUrp2rw43X2J3AV89AJc1XbH2fRylue93+yyq9gQDCq4ZmMRryTT6empzgQCl4qqg+ElVDIurGHhaYOOv4e5tsdW2OGP577XbU4oOOECLEgfnXo5FoRkZFre3TpCiUoe+grFYW13Bw9XbuCKScHYoas4mcz6+yqzT2UuZKX+AT3h87Qzvm/ral7mPcW+bhjGcCvVfMVU5+VWPLvkB9jfnp1edXQzZXPOqBOdw3YzmapvH+z5v5x4e/sXxrCX+e/iPv/BiocXl1wXoKJs+gYPIMHv8qNGXv9ashwVasoOXOjwN1KvMLd3HD24t556dN3PTOEirCMjtFxZUUTJ4Rcl34J/DdpVUUTJ7BWc9G7z2zcXe5NeY5q6JsBFnDm+CG3WUUTJ7BOc8viPrp/3+/FzH20XkUTJ7Bn6f/GJEpe+enTVz3ZmRtxZfLQqd/zJ9TMHmG9X/xwS/6/0XwOX9cv4e/vfUrj85abf0/XPfmr/y8YW/Ezwj+v4Pql7Dvr/Ty5+k/MmjKTOYX7op5nGnm70XWeI99ZC7//PC3GgPVCo+fm95Zwj9r0c9HVTXW7AhMYZ305LfV1nP9unEv1735K1v3VUT8PtU2o7KqaD/Xvfkrf4RNodWHqmrc/tEy3vkpeu2YEKlKApVqBDIqtX+aKhQ9UPFX1q+N/uYtoUuSgzMswT5duhWAwcpqWhD5xtGxWWbI5R37A3Uid3xct0JTgIdmrgq5XGVkbr5cFn1O//1fNvNT2Bvb/327jt+3lnDTu0t4Y9FGTnjiW75euYNb3g8Uxt7x8e/W948btTimd8PqUpZvi57FemVBoKBx4ouL+PDXLdzy3lLe/2Uz079fH3LsC0ZtQrDwN+T7jALbnzbsZePuyABy/H++sb6/dNqPUcdUnctf+QmAH9btYeEfkbVJV732M4XGG+nXK3fwmfE7YLrlvaV8smRrxP3+8t9fQi6Pfniu9f3/fbuOxZv2ceM7+v/FF0FBzdnPLeDjxVt5Yrb+/D/+1Ro+WbKVM6MEasHPtWlPWfRA+qk5hXy9cgd7y71MfHFR1GOCXfnaz9b3a3eW8fqijXy+rPram+nfr+f9Xzbz+qJAvU5NObivV4YGl8u2lDBreexaldOf+Z5PlmzlxncWR0xp1jajdNZz+rkuqcPvTSyzVmzntYUbuOW9pTUfLEQKSfruyalMU+uYUQEqlXTQQKuq3yeiPCX0/rbKfVGP213qYbRtMdNdD7JY7Qz8KeT2JhnOkMvBUzR1afJm3TesNb7HyELtKQs9p2JkD7bui95Kv7KaT9w1fVouKg7dpbouy313hS2V3rw3MvAIzwoEf9qOljGob/1N8PnL4nhMu6vJqFUnPFmzr9wb9fv6qvJFfz4aYnuFmn6Hd+6v/e94SWXkYy+Jo/B53a6yegcqZoH1xgZslLi9RLaxEAcmyahUoz4ZlSqbnlHRPPvrNYZcJSwj44meobEpCsfb9E/gA21/QFiA5PM3bO8UU3hxr1VMG2Naw6dGr2EJr2mIes4YvGGPJTztHg9HWPFntGcnvM4geOm5muDC2Oqen4YeQ/DzHc/PjZfXF3189gbYJDNWEGRyOiJ/Rk1PV7TgwhVnwBH+Oxj++5UMVd7G66EjREOSQKUa5vJktRY9VEyVRqDiKa9foJJHWEbGG/0TlqKAWwn6RF0SOmUU3s8l3kCl0uunqLiSrfui94RxhwUqVmYk7F2gcEcpXr+K1x/958YazaY95ZRFKbgNbhbnDQtkzE+zxVGyAbGyMxt3l7NpT7lVCxLtTSw4yNI0jZVFgf9b82fu3F9FucfHsih1P1uNmh2/qrFhdxnfB9VjhGcVtu4LzRJt3lte4//Z5r0V1d4er+AMVUMu1okVTGzfH/rYVxXtj/npP1bx9YZd5SE1UaD/H23cXU5xuZelm+Kvw9pT5qGk0huxcglqDogA/Cp8F1Zr89uWYtZs38+24oqYj2HTnnJUVYuYRqxrw0FV1SjcUcrWfRVs2lMekrVctqU45JzbSyqrzWqCnqncXVpFpdfPj+v34PWrbN5bTuGOUrYV1/93b1txRb0bZCZCaZUvIuMqGpdM/VQjUExb+4r9HZUOsMGHi1Yz9JS6jyF86ueTH9cw+NjI42yKQltld+CKsl2Q38O66PWrdFM2M872I6/7j407UDnpye+sOohBHfL48JoRIbenOUOfm1veW8pP/zqOeat3Rpzr0mk/0q1lVtSf82pYjYhp5INzOKpr84jrh9z7FWv/fQJ2mxIRQJV7fHj9KgOmzIy437Pz1jJpTNeI679YVsQXy4q45MgC7jqlD/4omZ8L/m8R6+8/EYD/zA6tk6nw+NldWsVh930V9XEAHHn/13w8aQTPzl0b0ZfjiKmz+fqmUXTOz2LrvgqOvP/rkNtv//h3vivcxfMXDgXg65WhTftAr8O4enQXWuakxRyDSdM0azou3F2fLre+N1e91PQmtnVfBW3yjLqsGL9b985YwSt/PjzkusWb9jG/cHfIdeMe12t75tw8mk7NQ2urDr8venO8t3/axNs/beKdq4ZzeKemgN4n5cmvq28098aijVwwrIN1udzjY/A9swB48aKhEcff+v5vnHtYh4jrg+0qreK5eaF9U/aVeznuMf1xZbkdLLt7XMjtH/26hevfXhz1fMc/9g3XjunKzeN6RL09lrs//T1qrRDor+uzh7TjobMHsH5XGaMfnkvbvHTmTz4m5vkG3j2z2hWCn157FP3a5dZqjKbfNhdz8lPf0at1Dl/8bWSdzpEo5uP+9fbjaJLpSvZwDkmSUamG3+hMW5eMyn7NDUAm9fuk0dSu379K02tM9pdELxS1KZDPvsAVVaGZHJ+q8ajzGW52vsv1jvdD/uAc3T0/5s8vDKqT+HXjvojbu7YIDTzMlUe56ZEv6O8Kd8X8ZPjR4siiz+D7RWO+eYZP/VR6/TGbqD30v1VRrzeZRbUZ7upj+PCC3nKPjyWb91V7H4APf90Ss3mYeX2s7sP/+z0QnDw/L7LYF2DhH7ujXh8u3kZ75tTPjhpqQNbvDkxJxvpUHC14rW4FylfLI4OxmuqP3voxUCxbU5AC8Ois0N+H4KxUonrzRHsMT9XQubem26OJFaSY3jUaQ5qdqsMzUuFqej4++LXuO71/+KueAV4RoxA+mczH/fvW1BvboUIClWrUeXkyUK7pn2ozlfqlDLOM++9E/6SSHuN8iqKQE1zPUhX6ovL4VPrZ1gMw1v5LtRmV2rS1j/WpvCJGR96G/NNv1mREm/qpb91DrDqXWM9NhdePEkd7sOoa9pl1RA1RPxTPct14mIGKv4bfieAaqIZK34fX3MQ1/VHLp666hxVrmicRPXsaok6nruJ5ucfzNyG8Du5g05D1WqJ2JFCphrkpoVaHjIrZRyWD+lXauzX9/ru0nGrPZwNyCPokHta/JXhTNb9mC3kzDH+jr80bpfkHrLOylRwCgVKsN8KGLDo1Z2fCP+mVe/xo9QyJYtURVMYoSIx3hU91xZjmFFZDfJKv6RzlNUzlmMypn2hTYcGCMzRV/vqtdjKFB0fV9WKpq+p+H2NNd4U3TGwItiS+CcbzmoznVzJWofyBLPhvoQQqySM1KjG889MmXv/fcka561ajUmZN/VTiV7U6/5K71QpQYJemZ1QyYmRUCrftwq0E3lx37N5Fi6DbHb5AEKEQ+ibgU1Xy2I8DlV3k4te0mL8YBZNn0LVFFteM7sKiP/bw9k+b6KBs52v3zfg0Gz2qXqGk0sucVWaa3/w5+uOv65470fhUlTmrdlhpY9N/Zq+JqCEJdvKT39V47liB1sJ1u/n7u5F9KG6LshFkNL9vjV3U+eTXhdwwtnu1DfiqfH7cDjuL1kXf8+nv7y7l/779g2Vbqk9TFxVX8NXy7azZUX2x91/f/JXXFmyIqBUJd8fHyxjbqwXLtpRw8lOxn9+CyTM4tmcL2jfNiOhdE+7BL1fhdtj5Y2cpt5/Uu8bjAT74dQtTz+wXdyfYvWEF11/8FpiWu/X96P+nPf71JVPP6Mfpg9pyz2fLGdu7Jb9trl3TxILJM1hw2zG0ztU/0MSzmMhsQPi3Y7vRvWU2P67fw+0n9cZuU9ixv9Kq33np4qFxL4f+9+crovYMem3hBnbtr+KaMV2465Pl/LoxsjdTuA9/3UKVT2Xzngp+WL+Hb/4+hg7NMmIcu5nlW0v4xwm9YmZlQZ8GfeDLlTTPcrPRKAi+ZXxPBrbPi3rOFdv2c9uEntWeE+DRmatolZtOyxw3T8xeQ+f8LI7p2YLv1+7ithN6ke60M+XT5SwImkpNZpyyY38lj/xvNROP6ED/dnnJG0iSSKASw/pdZdjRPyGUe2v/CbdTm5awEzKVSrx+FXtt9goyeD2VuBT9DXO3EaikEz1Q+XTRCu4IqqFcsW5zSKDi8gcCFbfiDfmk4PP5meH+B80pZkzVozVmVAp3lHLjO4Husm+57gH0zrk9lY3c/8VKADop23jPdRfrtNZc4PknHpxRz1dXflWrUyO1eDrxxsqQ3Pre0nqtAAgEcLFu31FtHc1/F27ksqM6xbzd41drDFJAn2+/85PfazwO4If1e/ihms0wAbYVV7KyaH+1QYpp9sooXXpjuOczvbC3TV56jfVFple+X8+VR3eJ+2cEe+yr+DZPvO2D39hdWsXrizaGNJGrjfNfWMjcv48BarekPjgIH9Qhj1MHtuWaoCZ+l73yE9lp8f1pjxakANz+kd4E0mlXrE0ca1LpVfngl8CHhste+ZFZN46KeuwNb+t/P0Z0bc7oHi2iHgN6R+rPloY28zvt6flWUXusc46qpu5uVdF+ngirX1qyudj6wOOy2+jWMjtix+tkZr0mv/8bX6/cwds/bYr62A92MvUTg8Nuw2YEKnZH7eO58YP1P5QZVNY5lV9eFvi027Wz/ubULS/6f1mOElqA6fCGflJ2+wKXcygLmU9O85fSVtmNW/ExzLai1uNtowTexAbb1rBmu/6zrrZ/QjNlP0NtqznaFshC2FD5t+NFXnHeTx6Rn+ifOaMAhTj2DEpg7xIzUPl72EqLHbVoHNYmt+bVN+Fqatq2Y39lg9RIlFU1/DRKIneBjlboecbgtlGPNQtia8oC1de6XfVrxrY+aBmyJ8rS/3iYjeyWhgXf9fm/CP792rSn7osBghsWxlJcUX1DwdI6/J7uruGDRE37i/2xqyxqE8Jk1hGtKqpfm4sDnQQqMThtCnZj2kKpQzYkLVPPgGRSGVEDEq+qMv2TsUdz4M7Qz2fXor+wQ+pTALs/9MWa5g/80UhTvGi+wAsx0x/4I9dMKanXG2FHZbs1n32kPfCJfYQt0KZ/tG0xFzi+ZpR9KX+yhy7nPcs+jwmfj+BZ538izn1GhwpudLxjrW4KL94L775bH2Y9xNheLet8jr+N7Vb7O9Xwt9BltzVIrUa0rqv1Vd0bwIAoqfraiPZhNtanZjMjGO19Jd5MQzzi6akSr1i1T/GqTQF8TYJrcBryMUZT06aPrjo0yqvpg1ZN04KqpiV1mieaRDeUTHUSqMRgsynYFP0Fq9XhabK59WW7GUplnYvvzEClQnGDQ695wRf900L4aiC7P/QTQXCgAoQU22b5A/PPOUqZ9UKPp6jWFpb5aKvs4vetxeRQSjslsKy4pxJYhjraFpg2GmsP3XfmKvtnKGiMt/9IRyVQL+DGwz933cp1jo+Y4pwGBN5sFVQedDzPx9p19FAi09RNKaG/spZ4l4Rs3Vdh7UuT4ar7rrfprtq/Ke4rrz6jsmlPedRl4rX1Uw1TOXUxt5pprbq84QSL1gI/VvPAP3aW8dvm4ojNNyH6/+eG3WXsKfPUus1+rGXktT2HX9Xq1OIf9OyRX9UarNP0mu37Qx5XPFmR6qiqxg6jeZ+maazbVcbeoD2fdu6vYtOeckqrAoHz5r3lbN1XwZrt+2MuCf5+7S72lHko9/jYXlJp/QwIZB92l1bh9asUl3ut15WmaTH3nDLtKKkKaeZo2rinnCqfP+T+O/ZXsnTzvoheTjtKKkOCx3KPL64PB5qmhTyWnfur8Kta1Gabe8o8KdkgLxGkRqUaZo1KXVb94NLTzplUsWZ7KS2yaz8N8L9f13I5UEE6ihGolJVHb6EfXrtiV0Mvu9WwP6rewHmy/IE/BtlUWBmV8O6o0bQi9A2vnbKTSo9KNyW0DqGLLdAnpYctELT0VDZix48fO/nso5stMMd9pO13NvhbATDMtoJmqh74TLD/SJa3nBOf0Oshjrb9xjmOeaDBPxxvcLF3snWOHMr4n/sW8pUS7vH+iZf8J4SM60jbMs63f83Lvgn8qukZkOBma+l2FRtqnZaopztrH+T8+/OV1d7+0eKt1facideP62sujqyt6opd6zOFAKE9ZGqy4I/dMWtlWuemR+wLNOqhuXUa05JaFtBGM/LBOfW6//Tv11Pu8cW1KiceZlM6U317h3T+x+cAvHDhEBZv2sczc0Mb4U35bDlTPlsect1RD9T8nFzwf/rmlc0yXewOCzxe+m4dRSWVzFi6jS75mewoqcKvaSz6x7E88OXKGgv61+wojRqg/TVoJ/JvbxmD3aZYfyvG9mrBixcfBsCnS7by1zd/5cIjOnLPaX0B6H+X3jRuxZTxpFfz4eeh/63imblr+ffp/ejRKpszn/2e0T3yrf5Upm3FFQyf+jWdm2fy9c2jq308BwPJqFTDZgUqdfhUbQYqSkWN87CxqMa+PuWk0SwvGwA33qhp3pbpodc51OoDF19lIHDJVgN/jHKUciujEs+GaB1toW8gbY0sSoGRDSlv2guAFso+a/lyp6BMSZripbOiF8t1tYWu3ukVlB053Bb6Bt5HCRS6mXscAQy3/R6yhPtU+3zyFf3xXe74nOCsSjqVPOV8gpPtC3nB9QhuQv8Y9FA20uy5fizLu5nWRDZSy6SCdw8vpIMS/U00z7eTj4aton2M21uxm384XucoW/TVJXb8THa8yb8dL9KU6G8Yo1pU8ILzEe5yTMdJ9KmXfPbxlutefu02jdzwLRmCHK6s4Jm81+mlbIh5DGhcav+CWa2eZrit+mLc7somnnL+h7873mJnSU27iGscm7465nMZ7fiBeRVx1TKZBiiFPD+ygto2W5k0pgvDOzer1X0ARnRtRlujW28ivfNT3RutNZYnvl4TEaQ0hPAgxTTDKMBdu7OM/VU+yj1+tpdUNtiqwy+XFTFnVeDD2FcrAt9P/VzfVd0sxvWrmvU3dVOUzU6Dmc/RnZ8s4xUj8I+WqTR39v5jV02vq4ODBCrVsNUno+LWA4tMKqOm7eLh9Om/1JnZueRl6+dz4Y3aVbRVetgmaGGBiVMNfUF7K8uCbgscm01gT5l4ViJ0CMucNFVKyaCSjsYbTkWzvpDdGoAuylYyqaCFsg+AVWo7AHor663bg/W2Bd4we4VN6fSzBVYr9LcF/gC6FD8Dgi4fZgusFGmt7An5GYfbVtHU2KIgXykJKfgFuN75AUrFHjIqi/ir48OIxz6/4EUOW3oH77vuihIAaPSd82cGLrmbN133kR7R/0bjBdejXOmYwX/THuLR0ZGdfC+1f8lfHJ9ygeNr7nO+FHF7uybpvNL8vxxv/5lLHDO5zP55xDEAdzmnc4RtOU02zeKltjOiHtNZ2crrafdzQuUM3nT/O2ZAc4ztV+50vka3ffN5M+sJumVGz5S48fCy6yFOsi9ikuMTrrZ/EvU40/oRX/GSdhfz0v4eM3AzNUtTWN/zObq+NpR1aX+qMWACWDBqOR+776DlB2dyp+PVGo83rb53An8f15M3rzyCI7vULlg577AOzJ98DGvum1Cr+x2MUqHEwhNjU8y68KpqzFqX8MLouvz917TqFwukwvPZmCRQqUZDTP1kUFXnYlq7Xw9UfPZ0nG79k5lL8UVdOmvWpHgVfYooPDAJD1x8VYHI3qEFByoVVqAST1OwaJ+AWyu7KTAyLd6cAmjaxTq2wDi+zNGEn1R9RY053WMFEd30fVB6KJswP/1a00Vd9I2O+trW6WPHR3dF/0T5h6MzAL2DMgL9lNDll8NtgTTzIFtor5Ujg97wFFSOUALHTrD/EPLpvS07yStaAEC+UsxZ9nkh5zpcWUn6Xj1Iaqfs4iT7wpDbhyir6W88BlQfAza9RrgL7bOs74+3/URzQqcaeti3wR+BNPmfHF8Rni3IpZQJtsAS7v57/xd1W4dL7P/DaRRq57E/4vGYrnJ8Frjg2c+J6tdRjzve9lNIjdLljs9xET2z2EdZBz/rdUeK5uMex8s4YmSHAI53/ATrv7Uuv+m6r9rMSmt20+qH+63Llzr+x2AlvmXIzg3fwIdXw6IXrL8H8TILIOPtaSISqyEb0nl9Wswu0+G7VNdlRZeqadUWSDdk8fSBQF5B1TD/MNWl4ZsZqDgVP35v3QrlXEag4ndkYHfqNS5uPFH7eDiMQKXSqa8Ocmqhx7jCLv+xNfAm4gxaSZStlFtLcJdu2lfjGDsqkT0xWil7rEJYb15HaKovrS5QttPJmObZm9aOQq0NAF2NAMUKVLqPQ1UcZCsVtGIPWZQH3vT6nQVADyM46aZswa34KNEyWOQeDkAvm559yaGMTubU1OFXAqHByWBF/365sx8AQ2yBN69uyhaaKKVgd4HdTROl1AqIAI6yB1YxAYyz/xRy+XR7aI3EOFtov5fRdqOgOFff4K7D9q9DCpPbKTvpaNuBV7OzWm2LXdEYZw89x1Haz/o3HY6kSkmjnbKLvsq6kGOOsC3HpmjQvDs07YJLrWRUUDEz6FNMp9rn6xd66TtonmGPrPFoRjHDzCm4UXod0InqNxHHAZxmnO8J32nstTcjTyljtG1x1GMn2o2NBrtPwJfWjE627Rxj+zXqsQB/Uj8FoKLlkKDHuSLm8Rc5ZqJoPigYCQP/BMCVjuiZpWDH2H5Bee00WPIGfPF3Jha/UON9TAoq7TZ+AjNugpUzaNjNI0RdnPLU/AY712Nfrea6N0N/Rwsmz+CfH/7G/qC9nAomz6D/XYHNUW//aBnXv/UrI+7/mpEPfs0nS7Zy9INzGP/4NyElAqoGnwc1Hwz24/o93P5x4ENVweQZ1pLs1dv3c/tHy2LuPn6gkkAlht6tc7AZf1xyMty1P4Ez0MNB8dRtDbzDr3/y9dkzwKFPDbjxsSxKwzKnqv9ielx5+uWgwERVNVxh9Rc+T2DqJziIyaLCava0M47GZu2jBCptlN1W5sSb0wma6pmOjrbtVu2KI78bO9OM3jBGANDZZjR2atmH0kz9DbybbQvdFD3jUu5uAR30YKSzshU7fiuzslzrSJse+s68Zkalj7G3EXkdoOtxAAwwMiwKKgONKaJ9A6+07mdO0Qwz3/g6Hql/EVonM9Kcnuh/LgCDlMKQ2pijzOXYY+8C4Ejb8pCMwhFmZufom8Cdg9O3P6Q2xJzO+MPVnS9sI41zhAZHR6iL9W96n8LuVvoxY8KCAWscncdA93HGdaFTK/2VP8hVyilTsuDER9BQ6GPbQD6hBbfmYy5v2huO+AsoNropmyLqd5z4rMf3hX8YO9rrUx/Rgw+NMXZjzIddRmmPMwAYHxaUmdqwiz7qakDBe9arvO0bDcBxtp+jHq+gcqbdyL4M+wsceS0Ax9p+qbZex4GP+5wvAxq0GaSPqfRD+oZl6GKZ4pjOkF8mw48vwlsX8Df7B3HdL5RGC/ZGmTY88BTWc/XQgaKm5n+L1u3ho8Vb2bKvgk17KrjuzV/ZuKeclUX7uXTaD3H9jLOfWxBx3Q1GA86Tn/yO1xZu4G9vxQ70D0QSqMQwqns+Fw3TG0o1y65DQZzdgUfRgwvNU7eCJ6cRqPgdGeDQMyqx0ucOI1DxuZvox2mBwMSrqrjD7ucOut0R9H2GUsUqo2Fb+ILS8w5rzw1juwddo9HdGVno1UXZSr6iB1OV2R2sQKVAKaKTTQ9UWhb05p7LzwT03ishy5mbd6ckS58u6qZsobtND2TS2/aBvI6Ua27cio8CpcgKSrr0P5KjR+pdPrvZtuDER3/zTaXNIGg7GICutq1kU04XZSs5Sjl+RzpHjr+AyrQWOBSVvka9zNUFxqeZjkdZwZEZqNw6rivj0o2gZeif8WW3w6n4rdvbKTtpb9sJih0OuxxfRksylCqGGvUy6VQy2G6MrfNoKxAKnpYyMwQFQ8dz0XkTARjhWI35yfyWYzvS02MEIV2OpdVgfTVTeKbH6l/TeTR0OQaAo+2/EfwJ3wxclrkHQFYLtNYDjOtDz3VNO33MGb3HQ3oTaKtnNJ4/MjRwHqgUkqlUoaY355aLz6DbkacBMDLs54IeHLZW9oAzAwpGUtZF77o51vZz1OJgK4DpeCQ5+e0YNk4PFM/Ijp5R6aOs12uiXFnQ7Tho0Qtv8944FT/Hh2XBgt3aZaM+rsx8uPRLKyC9yfFuzPuYjrP9xIWOr0CxQXc9SLvB+T5DlPg66wI8ckwGP7ecyg9pk1ieeTXXO96rVeEw6M0Kbx3fk69vGsVTFwziP+cN5ONJI3juT4M5vnfd+wMB3H9Gv6j7VsWq44l3t+5D2S9xtB1Ic0Z/y/7ZaDdgPs9LG2BFWiqRQCUGm03hyM5Ngbo1fAOosun7XCh1DFRcqhmopINdz+q4FW/UhkYuI1Dxp+mBSvAKFp9fI43YNSvBQU1wVsDr13DhtaZx7j+zf0gTs3+NzCHdH5ktMj9N79Gy8LtyQwIVM6OiNOtCk1YdwZ2DQ1E51vy0ndEMMpqyL0u/T1dls1GrAkqL3mCzsUbTA8huyhar4Da/61CUvA6QlosTH3cdYaefWQPSeiBkNremWfra1jHIprfQtrcdAnYHaQV6NmagrRDQaLPP+IReMAI6HAHoXXcBru5eitOzD9w50HYIjq6jgUAWxMqWtB0M7mwcXceEXD/Etga75oPc9pDXEQqOCr0fmvW9u+vRNOk6DBxp5Gn7rOmxizrsRvFXQVZLaN4NW1c9CBmsrLFqUNqwi862Iv0Ns2CEHhDZnLRTdoUUQY8wGvMtdenBnM0IaPTAwqTRrcx4TrqO1f81jutf9TNHdW1uHWkGS7YuoxjTsxW2ghF4cNBW2W2t8DJZGaBOo8CZhrf1UHZqueQoFRweZTpnvN341GlMURUcdiLYHORVbIi6usr6veo82upF5Ox3OgAn2BZFHG+6ItOY+hpwPjjTYPRkVBTG2JeE9PcJp6Byq+Mt/cKRf4UL3oJBFwJwt/MV4pkCasVuTvj5CpoV68+j4q/iescH/Mvxeo33NfVslc2kMV25enQXOqdXcBLfcao2hwFZxYzv25oXLhrK4+cOjPt8/zqxF11bZFmXzzu8A0dECUqOq2cAJKoXq4A3vAnkwdYgTgKV6hi7J1OX5cmAx6ZnYjwVdetFYDdW/fidGdYfWTfeqJ1jzUCFdD24Cs6YeP1qZKDiDxRUOkMClSrMP6Zbiyt42vkf5rlv5AL7bL3U/Ku7ecL5JPnsJb8s+sZ/A40VOeu01voLxqhRaaqUMkgx9tho1lVvHZqvF9SeYL4BNdczNnsz9UBFn/oxakNa6EudVxurhXoom+hprgZq2Vc/X6v++sXy1YFCWiN1b2ZVBiprrfoU2g0N+XeQrVAPBsp26lmstkOg7RBUxU5bZbc+zbHWKGAtGAl2p/4mSyAjYtVLFOjTMXQ0MzKrjNuNgKTgKH3MHUdYt9tQ6aDsoK2yG83mhPZH6P/37Q4zjtGzNq6tRnFuh+H6OZoUoDXphFPxW9NWI8zsStshkJar100Zj9MKhPAwyHguljj1544uemClT/XovwtdlS0oZTvBkW6NxQxU+GMeTlvgdzIkiwPgymCJ0ivonAHH2I1AwpiWstvtfO3X/7+ODZsqymcfQ80i2F4n6/+m5UL7YQCMClu1BTAm7PwA9D7NGmd2WEdngBbshTVGXYERZNC0M7+n68/dBWZNTRSjbEvoattKGRkw8mb9yuOmoLmy6GtbHzE1F809zumkV+2E/F5w40o45SkALnN8wYRqgqtgTrtNf70uegH+0x8+uAI+ngRPDIQv/wF+L+4YxaCxhHdrjda9taEaz4noYrW6UDW9UZ7J41Oty/vKPVR6/azfVUZxuddqKFfp9VPh8VNc7qWsyhezeVxNTSgbgwQq1VGN1HMdMypeu55R+fKXtTG3jK/Ovn37AKhS0q1AxUX0jIrbqDOxZegZFSc+Sir0XzCvXyNNCf1lC+6rElxMa1M08pwq36/dxfqNGznO6Bz7J/tXsGE+fPcop9gX8LDzedpWVJ/KXq+10ltku7PZoeVZ5wdFD1TAClSOsxuf1o1gpCw7MPXT01zxYwYqmh6ojLIvIVcpB5vDOg+t9MLYgpKf6GgzsgbGVIYZqPS3rbWyI9abrvHvQFthoBal3WH68+7OojhHP/9g25pAoGK8oZsBSV9lPTmUhgYiYAUig5RCXHgDUzxmINOqP7iyyVHK6alstO5f1XIQuDJCzmEGQY5NC0OuB1BCAowoAUPQmIZb2Z3VuBUfRVoTitP1jBPth+GxpZGvFFvZLCv46jDMqpei7RB9SqViDz2NKbgsyhloBqNBP3eRMsAYWyCYaEpJIHDtdjygv8HOVs1A5ReCMxDj7D9iUzS0tkMhN2ifn676SrDwQKU5xVbQbJ4fgPzu0Lw7LsUfNXA4y/4NaKoeJOYHpjoXNTvduj3WFOwVxhLxrzMmQFqOfmVGU5TDLgPgOseHVJdVGWH7jePsP6MqdjjnFchpDYMv5BmfnkGa4pxu9SOqTrMsF3x9L3zxd/CW64F8+yP0x7XwaXhrIlmO+Kdj3E47CgoKKmfYvoGXjueFjSex1H0505wPcLRRoO1Itd7zh5DgRnmqpl8ecf/XDJwyi563f8noh+cyYMpMDv/3bN5YtJEjps6m1x1fMmDKTPrc+T/GPDw34pwvfLOWgVNm8VacG1MmSkoEKk8//TQFBQWkpaUxbNgwfvghvqKihPMZWQdn3Zo2VSn6/TKpjKt5WrgMRY98t5TbQzMqYWk9j0/FbXSmzW2ip+BtisbWvXoBm9cfqFFRjeyQ2TtF0yILbc8f0IQHv1wVCBAwepr8+l/r8ij7Uoaue77a8ZdndaRPG/2PdVrLroEb8toH3oDze4beqUVv/fzDh+PXFPKUMqvexQpqRulvyION6Rua9whsMWBkVLoW6as69mQUQIaeZTJrKo51LKWHUfdifhqn9UBUbLRR9nBNU6N2ISgIyO6mf391u3WwyfhUa2YUclpTmdsFm6LxJ/ts2im7qMJpTRnRrCu7ycWteBlhW2YV8dLJCFTsDj0AQM+YjDCmkNxdjw48L53070c5fuecwa2wbTZeI0a2BtALZglkQszzhAYq+s/UAw/NCliWuwdw7+l6kIfDjWLUzZh1KlavEjP4Aj2bZFy+ur3+h2yYbQUORdWn+/I6WIcusA00zhMoKh5lW4JN0die0c0KPFrmuMnqfRxVmoOOth10VQJNACfY9Mes9D6FEMb/w1GO5SHLmq1sSuuBkN0q9D49TwLg+IiiXY3Ls4zVIYMvDLnl5LMuZpetGc2U/VzaLLJ3y9lt9zLC/jt+bPQ/69bQG4dfi1dxMchWyNHO6PU0dvzc7tBfY+rQywLBN1B+5N/Z4mhPvlLM3x1vR71/sEe6LYdvH9YvjL0brvoWLvsfnPeGnhVb8z9GLL+LeFcjnTW4HU21vbzh/DePup6DTYtwaVXkKOWMsS/hVdcDvJH7NGf3zWXisA41nzBOzbPcXD1a/9ByztB21vV5GU4y67G9BcCEvq1qPugAF20zT4D7v1jBvnJvjceanbInf1B9b6NES3qg8vbbb3PjjTdy55138ssvvzBgwADGjRvHjh3xbwWfMF4zUMmo093dmfqcbjpVNe01F0HTNDKNepFK3FaNigsfvrAUXYXHT7oRbDgzmwTO4dWv8/k1K1DxO/XGcTbVCFw0Igpt0xUPflULTLmYlryp/9ukIHCdzcleJS/ocmBXhgtPGmttjZ7TJmgX4uZBBbnNQ3cnNgOV9MwsNmiB+e51Snurid7hw0aE3sfIlADQun/ITU17BL2xth4AKIFVTi16Q5axsZ07C1tL/We3328s3zVrMQBHJ/08fXd8CqpX7w1j1N4ApHXTp39ucepvIutzhlpL1FEUltr0c9/ieEtf9t6sW8gbuVlQe1ffXZyapf9xUIxMAaBnd5yZ5GnFPFjwC3hK9WkP4/kC9GBGsdHVtpVjbb/oAZ4zI5A1Amh/ONhdtFb2UKAUWb1jjhl/Jh2bBVaqObsZb/6231BQOcppZM/MLJDJCI5ytn7H+vtP5KUj94Vcb1qldWSHlkemUsUQ22rG9mrJsUYg8UeToKyQovDon0bg7jYagK9OLGf9/Sey/vYjGOEwMl29wgKVVgMgoznpWgWFf2muH3//iTzU36iHCZ72MfXSA5XRtiUh9VzDlJU0rdqsZ4qMKSJTy7wsmh+lZ0ZuaxHaF+eJ8wfxUFt9dZG97+l07Bz2e53VAufQiwF4tdt31hhN3VpksfbMnfqHg/QmOMbcFnL3m0/oT9uJzwJwoWM2669txdtXHhHxsG4Z34P113eg2VwjUDr6FjjqerAZf+p7ngjn/RcUO7bf3mH98UusscwNa8V+XO+W1m3ppRt4tPQWhtuXU6654Zjb4dqfmFA1lZd8E/ApDo6smk/mK2O57yh3yGMLF3zb4QVNrZ+x/v4TWX/HcH4du4pXnVP51vU3FrknceuGq1h/9Fxu67MPM7D6/LqR/D5lfMTzGK/195/Is38aYt3/s78eVfOdgLOHtLPu07oOu6OnirI4mnmmkqQHKo8++ihXXHEFl156Kb179+a5554jIyODl19+OdlDCwpU6pZR8RtTP+lKVdSdXKujavoKHIDyoKkfm6Kh+UMDi3Kvz9qU0JGZZ12vGTsoe/yqtYLC79DHZDcawvmirAiyefWNCZubmYxgjjS49IvAm/SoW9ijBIIjs7kboKeaTcHBRPCn8uDrFVugZgRYoPaxvv/VERSA5LYNTB1BaMYgvxdkBX1SCn7DdGfrKXCTmRGJdjmjeejYuh0fsuScPqeHbs/b5/SQUy3NHhVy+XuH/rh6mVmq4KkIsBrZsepzqNijF+oGBxgOVyAD87lR+9B9fOi0ZHoetNHHrBduGo/JzDaB/rvcTi8cPtc+NzD1Ev5cdDYLgFcwwvY7uWoxuLKt8weOG63/u2GB/noxazvCgwNF4VtVz9iMsi3FoVZZfVX+aBr6XFmPDWDVl/q/Kz4Bza9P7Rk1TxabLTANt9aoH/FWQqHRjK5HlM6wbQazTWtGllIZsrP3uQ4jfd73DHBnRd5v8IWAAuu+CSmqTasogmXv6xeGT4q8H8CI6/RA/o+5sCV0OXUOZTDnPv3C6H8EsoDBOo3Ui3vR4LO/ofojV0XZKovh7T+Br1Jfkj/6tsjzdB0LJz+uf//Ng7BY/wASnqm1fru3/w4vjaO1WsQGtQUnev4NR98MzbuxQuvIPb4LearTM3px+J618OLYwPRoTcwf4vfp9TRPDqbJd3dztP032tt2Yi8rgm2L4YcXaPL2KXzhmsxY28/Uc4/LOrMHTW3Favh2IIhVS5SqNUZJfaY9Hg8///wzY8cGPrnabDbGjh3LggWRa8UBqqqqKCkpCflKiGXvB/5w1DGj4rPrEbdeoFq7V9b+Sq+1AqeSNGt5MgD+0P4m5R5/YFPCtFzresWnByA+VcWh6BG0arzZ2jX9j5yqElG/YvOV41dVmqGv6NnrbhO4scuxkNMG/jIfbloNo24JHbj5ht12iD6/bl1/BuS0g7Q86Htm4PrM5tbSTw6/MuRN9XX/sVRpTio1JzPcoZsJWm8GTbsECitBf9MyemWQ20H/BBlyv2v0fx1pYNQNWA67TA8QwHhTCQoCXBl67xDQH8Nhl4fet2AkK9P0OozValt+yj425Ob5ziMp0fSAV0OBwReF3r/1AGgRCMzod5Y+tRJs4AWhl3ufSgTjDdta6h3++AH6nAbA1Y5PsSkamzJ6Q2670GNa9oFmXUlXPEx3PqBf131coD7FlN8Dctrqv5Nzp0LxJn1qodPRIYdpGszz68/PeNsP9Kn4kSylkm1aU7Zn9yaCGahs/gHKdsNvxrLgfmdHHguBQK/QCFTWf6dvvJndWp/6CacofM1QYzz69E8TSjjRLFYdfHH0n5PXwcq0nWcPvBl3KXxFz7R1PMqaYox6337n6N9/+2jITRdVvQHlu/Wp0KF/jn5/gOPv1X//in6j9YppITfZUBm38p+wd72+muyMFwKZlHCDL4KjbtC//+SvsH5+RAdVm6LA1sUw/UQo28Ef9k6c5bmLdVrriNNtTu8JV87VP5xUFcN/z+RPQZ2VY1FA/z97boReT1OxF7V5T+72XsgZVXex7dz/wVnTYOCf0JwZ9LJt4kXXIzR5+2TY1HAlApqmP3/NKKa9sp2W7InY+wtCA5XaFiMfCLr843MKJs+gYPIM3vs5dfaQSuozvWvXLvx+Py1bhi5pa9myJUVF0ZcATp06ldzcXOurffv2iRlcUVAPifD57Tj57fobU/iKm3g8Omu1EeBAt/Yt9Q6pJl9ooBI89YMzE6+xKbbqN4ppfRouI6OiGkGXXQtkVByEpgHt3nJ6tc6hqbGZ367u5+vTPUpQEODKgOwoSxGPvhkmvg8XhPWbyGgK1/4I1/8WOuUBcNqzcPX3MG5qyNXLtQLGeh7kOM+DDBw0LPQ+Q/+sz7tf/lVoxgBg+LVw2Sz4y7eR2bAB58Pls+GahSFTN4D+GCf9ABd9AkdeF/nYjrkdLv4U/vJdaBAGoCgsOfpFLvRM5gzP3Qzr3ibk5uMHdeUa7/UsUntSOeExaNEz4v5MeEAPlJp11T9Vh+t5UuBNt+2QwJt52OOr1PQApzKjdUSmB9CDRlcgW7C33+WRxyiBYMqhGG9gQ6K8eStKIICa/x/9314nRTzvpw5syyx1MCVaOgW27fx1x50AfOY/gqEFUXpv5LWHlv304s+Z/9QLuVFCg9xgZkZo22Io3gzLjb2Zuo8jVjqzspse4J5oX0gupZxnn4tb8epBY6xgA6znYaLja/LYT2t202m9UTdy1PWx72fdrsDKz2C9XgszUCnkpCqjU+74+/WapVgym8NxUwDouPhhhirGNCEqdzleodO+BXqgeO5/o2dlgh1zhz6Npnrh7Ym02h+6i/H5zVbDK6dAxV5oO4Q5R7zMTvJCNlo0n9oRXZvpY7v4E/01pvm51zmNuxzTsRM5zZCf7aaTso2HvP+G/54BO1fqKxZPeBj+8h3T/BP4RetORschenbrtKfxXLeMp32nUKG5cG39EV46Dt69RA/MajCwfV7gYfdsoX/j9+rZrc9voeuHE1juvpSf067mW/cNLEq7llVplzDHdQNPOJ/kLPs88tgfsgz/lAGhr/GDzc3vLqn5oEZSzSsiNd12223ceOON1uWSkpLEBCvdx0FWC326INof+zhYGRWlstZTPyu2lZBpFNOO6NURbDZ8ihOH5o0IVLx+1Zr6wZmOFwdOfGhmoKIGpn7CMyp+VcMZ9ofE5iunZ6scmi7XMypde/SFE67T6yLCP3kDSnBBnt0J3cZGHAMECmjD2ez6J/gw3/x9DAvX7SbL7YjenyGsHiUwIEWvxYh1W9D0UoSc1pFBSPB9wzIFwc46ohuVnM/xCpw2sG3IbZPGdOVR32mUdLiU9Fi9JjqNhFv+0JfDR/skbLPDpZ/DH/P0cURbjdasC8XnfcLW37+g03F/iT5tmdkMznwJz6x72Jx/FP3GXRp9PEMuxbv0A5zbF6MN+wtKrMd+2BV6B9aKvYACR1wTccgt43swtKAJ7709ij879Okczeai9+m3MqJ7fvTzHn4FfHpdoDaq7xlRf/8APWguGKnvAfTto7DM6AQ74PzoxwMTzzmffU89SV7JKr7u/iEZW74DP3oH2+pesD1OgJZ9ydm+jPdb/5emzipsOyr0bELXGL/7pvwe+vTRL6/C+5dzhu0U/u58R69b6ntWYAqrOoMvgrWzUZZ/zNsZD7Gs3Xm0r1xN0+3z0VBQTns69msjmM0Gpz8PJVtgy8/kvXUK3w+9lD05vWiyZS5tfvgI0PQl8Be8w0XOLNq0as1hnQIB0PeTj2Hp5mKO62X8Tjvc+geP5t1h9t1c4pjJyS33cGfJqfyR0Y/plx4OW3/lm54f4l72JrZdfn067PAr9exsehNswGd/PYpKr5/cjEBW0Z3djBFXPUlhWRH9Vj0Jv74Ov38IK2fwUbdzuXjNSIrRA/Anzx9Et5ZZrNtZhqrBoA55HHn/12RSwT3dCuGD/4PVX0KlPr2dDlbSu1xz48KLQ1HpZNtOJ7Zzin0BmtMGS48D15+h23FcNaoLXfKzSHPauXR6aFH2aQPb8NHi0E1W43V4p6b8sE5v4DauT0uKK7ws/GNPnc51sEhqoNK8eXPsdjvbt4c2atq+fTutWkXPYrjdbtzuOrS0r60ORwRWbdSRmVFJx1On3S7NqR97mv7iMwMVJWzqx+NTgzIqGXhxApUoVkZFJcMIRjQjUHGo5rSQZn3i0VBQ0LD7K6hSVZqhZ1SUzOZ6/UN6Xu0fRD10aJZBh2Z1m3ZLBrtN4eIjC6Le5rTbuHV8z6i3hZ7EWf3trkzoeUK1h7TsdST0OrL68/QYj6vHeDpXd0xaDs6rvoaqEpT0JrGPy24Jf54Jv7yi19UE1/aYp3LaOaFfa/q/fiY9lE30dhXR5NT7GdF/YOzzDpwIy96Ddd9Adht99Up1DrtMD1R+MnaabtUvsKor2sNzOUg74U546wKabfwicB9zKjIWmx1OfASmn0iXvUZ7fmcGnPRY9QGO6fh79WmLnSv1FTTAZnt72p30aA13NCiKHgxUlmD/Yw4DNhhTQHYXyilPxs46RePKgAs/gg+uhNVf0GbZc4TkCYZcqmf6HG6cwIR+oUF869x0WueGBcOKAiNvhObd4IMrabb7J57iJyh1wZMK+Kuw7tF9PBx3T8gycIC+bXOJRs+M5EHPp/WAcua/4I+5DNz0Gj+432KmOoS5/oGc3LIDpGv0bFMJxZuoWrqYV53vcYRtOa5ZQR/MMppDj/H80WQEl35RwSatBSo2QGPWVX3opq6DjQth5eco23+DNf/Tv3La4RxyMRMGX8TS4sidzyce0bHOgcqT5w9i2L/1KcypZ/Tnf78XSaCSzB/ucrkYMmQIs2fP5rTTTgNAVVVmz57Ntddem8yhNQifFahU1b5ToKZZUz9moOK3uUAtj6hR8fo10ghkVHyKAzSsjIpP1ayMihWoGFM/flWzpn48zmzc3hIcvnL8KtbUDxnNqY5W6zVN4oBhs+vt8muS3x3G3VfjYSVkMtH7T0Z3zmd6/xhZL5PdAX/6EIqW6tNhZl+SWHqerNeIbPhOXyV34qM1Bw49T4Rj74BvH4PmXeHsV+Lrm9ThCDjvTZj7b/1nHXc3tIxSaxNNWi5c/BnM/BdrF8/jF7Ubn+dfw7S06G/OUbkyYeJ7eiC3do6e/R18sf4YaistB85/U988cenbULpdX5U25BJof1iNd4+p18lwzQI9w7X8Y6jcp1/vSNcz1kdcYy3Lr5NW/fQgq/Aryj6/g8y9yznZvpCT7QvhuedCDnUDRxv/rd7cTjj7nAQ9TtQzrzY7ezfsZYP2fdA9FPzpzaBVJ31accw/YNca+Hk6LH4dSjbrNYzzHqBjx+MZbhvEArU3ZlqmPvUrwW8VdpuSMl1mPT41aQXESZ/6ufHGG7n44osZOnQohx9+OI8//jhlZWVcemmMdPQBxMqoKFW1rqZ2aF6rNkAxlrmqiv7fFb7qx+P14DKKZXGk4TP/W316MOLxB+pQNONcZr+J4CDG69ADFae/AtXvoalibCSWWX2gIkRtxf2H3O6ImqGJeeyFH+h1B827R64OimXkTfpXbXU/Xv+qi6x8OON5jv1Br0053JFX+3PYHTDgPP2rvhRFry0ylm03mCYFcMoTerapZIv+Lpzbrs5NNCMoCnQ7jsLTh/KPZ1/nZPtChtpWMTR7L5Tv0ac+M/NRW/blvt9y+FodzLQLz6egeWbIaaL1qbOFB7nNu+nB+DG364HXTy/BpkXkrvucN12fs1Ztzbv+UcxSh5DeQG/oNgWcsQqiG1mFx3/oBirnnnsuO3fu5I477qCoqIiBAwfy5ZdfRhTYHoiCV/3UNlBxa0HNd4wsiN8IVGz+8J2QgzIsDpeVUcEIaHx+DadiLGU0AxWjG63fr2E3AiKfKxsqwOkvx1m1L3DO9OqL8pQ4m0YJMfWMfrz03Tr+dWKc2Yfacrij901JcfbaFrEdaGz2yCL6BtSvXR65nYdy/9pOTBzWgaFm80LzxwM7tV8pqPTSMcp0cv92eRzZpRntm2TgVVV2lXroFrS3UQhnGgw4V/8qWsbuec/iXv4eXWzbmGx7i8m8hfb2M7zerAtFmb3JatOD9wv9tG/Tjg+X7sCHjTS8ZCvlNHV4OLyNk8JN28iigjP75tBy8XKebbkGt+Ij+5uFnKE4KW+6l1/2pbODJkw84VimL63g54376NEy29pENtGq/H6ghqnpBEl6oAJw7bXXHhRTPeF8Qat+apu9S9OMpcmakzRjFYBq039JNLO1v8HvDdoG3u4OZFSMKSKfXw0UzBqBilMzMyoqacZtPqeeenaoFbi9ewEot+eQUd0qBCFq4fzDO3D+4Yl7wzpQ2aX1fL3YbApvXFF9TeET5w+KeZs9jvtH1aovRSP/zTm/juEU+/fc12MdtvXfouxdxwjWQdlXsAPGAayG26P1iNsOmGUuq/Uvq/PP9/qb9CXAJeYxX93LyRnNoXc/fQqy09HQdmhE64CCyTMiftT6+0/ktYUbuP2jZRG31cTrT94HUnkHSiC/teqnCn8tIxUzUCkjDfN325z6USIyKsGBihOfYkS9/sDUjzm9oxjLUh0EalTMYlqfS68BcPkrSKsyAhVnEw6cclYhDkwHe0LlYFdGOm/6j+WeiROw+cpgw/ew9Ve9D03xJijZglpRgs38wKjY9YaC7hy9VUBajr7C1PrK0Qvr/cYqz8pi2L9Nnz7bux7Kd8Efc/SvuVP1Yu7OY/TeSj3Gh/TTCuesY1DsC+uz05gkUEkgn9EFNoMqtu6vquHoUGnG1E8FgRVOZkaFsIyKaixX9ipOnIoSlFEJTP2YNSqKW8+omH1V/FpgebJqNDsr3V/CwmWrudAFFc6aCymlmFaI+pGMyoEruJbFbtM3YaX7uIgpyAe/WMnz89ZgR6Vw6il1j0495bBzhR4Erf9OXxVXvgtWzdC/bE7oMoaTbd2ZqQ6litBMi8NetzqTmb9v54qjq10nmDASqCRQ2xZ6I6s0qrj5vSUsviP+wrvOOcAeKNMCuULNFj2johoZFZ/iwgkRGRVv0NSPYrQFd5hTP0FBjCNDj8IzlCprxU+pPS/uMQshaifNaaPSq3J0txi9ZETKy88OfJhUqgk+BnfIQ8OGD1v9UmiuDL0hYdsh+pJ8VYXtv8GKz/Qi312rYM1MnnTNpETL4FP/cN7zH82vmr4irFfr7Dr92GVbo2yp0kgkUEmgrm30Pz4ZSlXETpU16Wj8LqlB7ftVRY+MFTX0XGZGxQxQfNYUkX6cN2hljzn148KLX9VCpn7ym+sdGzOopLkRqGQ2rbmoWYpphaibr28azY/r93BiWH8SceBonuXm9cuHkV7Dbs7H9W7J0xcMpnebGpbZ15bNpndTbj0Ajvkn7FwFv72L79c3yNm/hYmO2Ux0zMaT1wW+XU2fAefx4kVDaZOXTvMsF7d98BvXjOnKqwvW8/HirfzfRUNZv6uM+z5fgcthw2NsguusYyamIUigkkhG4aq1D08tOPzlANjdgejXyqhEFNPq5/dbgYpRdGtO/Xi92BQ9mLClGcW0ig+fqhrLk41si9EvI0OpoommV5LbMuWTnhCJ0iYvnVPDuhiLA8+IrjW3cFAUhRP7N0JAmt8DjvkXjtH/0HsKLX4Dln+Ma99amH03fH0PYzuP0be+yD+Rly7Re+UM6diE/5wXKDg2p3nMolxnsnaCRAKVxHIGGr7Vlt2nByoee2Dqx6xRUcL6qGhGRsVv0zMuZo2KYuyQrAa13Le7zYyKT8+o+P1WEGMWYGVQSVNFD1R8aTXsFyKEECL12Gz6iqBOR8MJD8HvH+nbUWyYr+8yvnY2uHP1rSkGTtS3FqlmSkoyKgcrY9rGpfitBmvxchiBitcWaE+tmYGKFhaoeEMDlZ0VGthh6Yad9AH8vsDxNndg6sfr1/AH7xtkBSpVNDXa5/tr6KECUkwrhBApzZ2t7zE1+ELY8wcseQsWvwnFG+HnafpXs24w8Hx909IozRLTnQ3UpK8OUqPl3cEqqL6kubt2S7scfn3Vj8ceOIdmj5FRMfqlmBkXc/fkwm36/hCqL1B860jTp5LMjIoaFMRYgYpSSRMjo1LQLkG7UwshhGh8TTvrWwL8bYm+G/yA8/X3qt1rYPYUeGIgPHcUzHsQdqzg+mO7UtAsg6tGdUnakCWjkkgON5piQ9FUWqZHbnVe7V2NGhVPlIyKTQ3PqBhTPEZGxavp/61uc8dkI1BRsWFz6edz4aPE50f1B2V6gjIqZrdae1Ycc69STCuEEAeW8Kmh5R/D0nf0Jc9Fv+lfc+7j+qadub7PcbA7AzLrsTdTPUigkkiKgupIx+4tw63Wrk7FmvqxBwcqRgt9LWwaycyo2I1AxfhvtTYiNLImfsWBzTjGpmj4/D5Ub3BGRa9Gz6DS2rlZ9vkRQoiDnDsbBv1J/yrfA6u+gBWfwNqv9amiH57XP8jWZxPJepBAJcFURwZ2bxkurbLmg4OUl+pr1iuV4D4q0Zcnm5sPmrd7zEDF2N/Hb2ZUbA6wB5r/qN4qVONcfmzYzaXLSlD2J44aFSGEEAeJjKYwaKL+VbUf/pgHhbP0ncaTRAKVBNMceqDhrmWgsq+4GOzw/aYqTjCvNGpUbGHFtGZGRbPrjYfCMypmh1pVceqbthl8ngprCbMfO3ZX6I6i5ZqbDFfNDfSlmFYIIQ5C7uzE7KpdS1JMm2Bmwza3WrtAJdOYeinXAoGFFaiEZVTMTrWakS3p20GfrunSVL+sBWdUbIHYVPV5rWJav6JnW/wEKrv3ULcOhkIIIURDkUAlwTRjvx93LXupZChGoELw1I+ZUQmtUbFa6huBSk6GXtdiN45TgzMqimJNDfl9HiujomLXbwsq3t2jxReoSDGtEEKIRJFAJcE0h/7Gn1bLqZ8sArsnW4yMij2sM63NKNTVzGkde1gti/GvFrZ8WfVWhWZUgKqgQGVvnIGKEEIIkSgSqCSYZk79aPFnVKp8fmvVTfCmhIoZqGjRp34Uo0bF5jCniIyAJnjqh0DnWr/Pg2Yc41f0KZ8yR551Xpn6EUIIkWwSqCSYZrTRdxN/RuWn9XvJNKZ+xg0KarJTw9SP4jBW9JhLkI3jzOkdsz7F2gvIVxWY+jEClWYt21nnjTejIsW0QgghEkUClUQzMippteyjYhbTDu0e1BnWCEDs4cuTjUDF7jSmfoyAxMq8mHv+GIGOWTDr9wbVqBhTP2l5gU2ztmjNajVmIYQQoqFJoJJg5tRPWm2KaVU/6YoRXDizAtc7zExJaJdbxViebHfp00SaNUVkHGd2n7WF7a7s86AZt5kZFbJaWOfdqLWMa7hSTCuEECJRJFBJNGftV/1s2r7T+t4XtF+QWaPiCKtR8Vbp2ReHEagoZubFPM5avmwEKkaNiub3BPVYMZYtN+9unXed1iruMQshhBCJIIFKgpk1Kum1KKZ9bMavAHg1O6oS6CRrBSBBOzFvK67AZXSgTUszVuyYUz/Gcdbqn7CMihpSTGsEKj0msCejM3P8AyjU2sb3GKVGRQghRIJIZ9oEU4xur7WZ+slS9J2Ty3ETvOdyYNVPIFApqfDhQg9EsjL1n6U5zIxK2NSPcX8zKNF8XiujopmBSkZTsm78mU0/buTrrrLPjxBCiOSSQCXRjKmb9Fqs+skwgppS0lGDyj/MVT2OoEDF61etXZKt/im20CkiK6MSFqjgDyqmDepY63LYuGh4QdzjFUIIIRJFpn4SzZz6oQpNi6/o1MqoaGmoQfdRHKHLjkEPVKw9fYyGb1bmBT2jEj714zf+1fweMKZ+NCXQOr+2pJhWCCFEokigkmjm1I/iYU+ZJ667ZAR1pQ0ObswARFE9eP36pJDXr1lTP9bOyGFFt+Ymhmag4w9e9aOaq34kuSaEECL1SKCSYIqRUcmgktcXbYzrPplBXWmP7BKoE8nP1ZcqO/CzvUQ/xudXrWLaQEYltEbF6lBrZFJUI1AhOKNiq3ugIsW0QgghEkUClQRT3HpGJYMqfH61hqN1ZlfaMtJIcwamZFwuPRBx4kM1TuXxq0EZldC9fqxVP1pYMa0tcnmyJhkVIYQQKUjenRJMMfuoKN6QwtjqZEbbkBCsAMSFD78xJeTza7isGhWjmNau/7eatSsOo0bFzLSYGRXF70UxBlWfjIrUqAghhEgUyagkmhGoZFAZUhhbHTNQKdeiByoO/PiNAMMbJaOiWMuT9UDFLL41a1zMVvr61I8+PVSfQEUIIYRIFAlUEsxuTP2k48HtiG9ljTn1UxqRUTEyJYrPKrL1qlpQjYqZUdEDETOjYgYsirGrshWU+L3WiiCZ+hFCCJGKJFBJMHe6XgCbrnjIdMVXdGpmVMYP6hp6g5FRceK3pn68PhV3rIyKsTzZHiujogZnVJy1elzBpJhWCCFEosjH6EQzVv0A4Iuv6VuuXW/4lpWTF3qDLZApMad+fGrQ1E/Yqh9HeKBiBDCqzci8+H0oZn2vre59VIQQQohEkUAl0YI3FfRWxHWXdK0CFLAZ00aWoCmdwKqfoGJaI0CxOcxiWj2AsVb/2M2pn0BGxQxU6pNRkWJaIYQQiSJTP4lms+E1Nha0+eIMVIypH1tadugNZiM3/FZhrs8fLaOi/2tHw+P1WZkVmxHImEGJTfWiGL1WFLtkVIQQQqQeCVQagdemF8UqcQQqqqqRgX6czR0eqOiBhlvx4TdSKj6vB7uihdzeqkngfht37rOKas2pH80evDzZKKatR0ZFCCGESJSkBioFBQUoihLydf/99ydzSAlhBio2X3nNx6oqmcamhLa0rNAb7YFgQjV2RFZ9QW35jUAlze0OnM9ThcMIVGwOs5jWqFFRvShGMS3SmVYIIUQKSnqNypQpU7jiiiusy9nZ2dUcfWDy2tPAC/Y4imm9fo1MY1NCR/jUT1DWQzMCFNUbdE5HaGdaAJ/Pi8uc+nGE7gWkT/2YGxYm/VdBCCGEiJD0d6fs7GxatWqV7GEklM/MqPhrzqhs3ltOa6NGxR5RoxIIQFSj9T1GwKKhoJjBRtAKHl9IRiW0RkVRPdjU0OClLqSYVgghRKIkvUbl/vvvp1mzZgwaNIiHHnoIn8+X7CE1OJ/dnPqpOaMy/vFvrD4q9mqmfvAbAYpxTp/iBMWYglEUPEYM6vdWBYppzYZwZp8V1WcV00pGRQghRCpK6rvTddddx+DBg2natCnff/89t912G9u2bePRRx+NeZ+qqiqqqqqsyyUlJY0x1Hrx2fReKnZ/zYGKGy8OY82wEl5Mqyj4sOPAb039eD36Of02F8E5ER8OXPjw+TxW59rA8mRjFZLmjWivL4QQQqSSBs+oTJ48OaJANvxr5cqVANx4442MHj2a/v3785e//IVHHnmEJ598MiQQCTd16lRyc3Otr/bt2zf0Q2hwPrseqDjimPoxsykAuDIjbvcRtPMx+tQOBApkA8fZrdvNjIpV4xJco6LWP1CRYlohhBCJ0uAZlZtuuolLLrmk2mM6d+4c9fphw4bh8/lYv349PXr0iHrMbbfdxo033mhdLikpSflgxW9M/TjiyKhkGPv8VGgu0qN0i/UpDtCq0IwaFZ+RUVHt4YGK/l+r+rzW8mSzxsUMSvSMitlHRaZ+hBBCpJ4Gf3fKz88nPz+/TvddvHgxNpuNFi1axDzG7XbjDlp+eyDwO/RAZcXGHZxUw7FZBDYkTI9yuxmAEBaoaGEZlSrNDgos2bCTsWZGxQxGjBoVm+qL2AeoLqSYVgghRKIk7WP0ggULWLRoEWPGjCE7O5sFCxZwww038Kc//YkmTZoka1gJUezVg4AMpZIqn7/aXZQzjEBFc0ZO+wD4FSdo4PfqUz9+rz71o4VlVLxGoPL171sY7zQDFTOjYhTTBmdUpJhWCCFECkrau5Pb7eatt97irrvuoqqqik6dOnHDDTeETOscLMwalXQ8eP0a7mqe9a55GlRAZnZe1NtVRb+zp8qY8vEZ9TyO0CyT1/ivdeAPTP1YNSpmoOKTYlohhBApLWmByuDBg1m4cGGyfnyjUo2pnzSqqPL6yaomUnH69WZvsTIqqs0BfvAamRTVawYq0YtpnYoPhxI69WN2qLUHrfqxhd2/NqSYVgghRKIkvY/KocDKqCgePH612mNdxsogzZ0V9XbVyIrs3FdqnFwPVJQYGRUn/ojdlc1NCx2aD7u1YaFM/QghhEg9Eqg0grzcHAAyqMLjqyFQUfVARYmyNBmMxm7Auu17jSuMfYHCAhUro4LP6kxrTv1YDd80L3azhb697hkVKaYVQgiRKBKoNIJBXdoCkE4VVTUFKsbUD+HN3gwOI8jIcerBgU3Vi2rDMyqekBoVc+onNFBxaD4cRjGt3XlgraQSQghxaJBApRHYXBkApCmeGjMq6VqFcZ/oGRWnuTRb1TMhZqASXkzr0wIZlUAfFaM2xTjWgRc7+nmkmFYIIUQqkkClMTj1QKWmjIrPr1qBihK+IaHJ6Jei+L1ommZN3VQ/9RO2PDlqRkU60wohhEg9Eqg0BqdeTJtBFVU+f8zDPH41sCFhjGJac+WOonrxqxrOGIGKOfXjUnzW3kFmjYrNGRSoUP9VP0IIIUSiSKDSGJzxTf1UelWrhb49PXpGxWzspqhGTxZzw0FneEZFD1TSCdo3yQhyWubp57YpGi48xk1STCuEECL1SKDSGIKmfqoLVCq8fquFvj1GMa3ZVRa/D49PxWXUmNic4cuT7dbPtBj3zc8NZGvMDI6ZZRFCCCFSiQQqjcEZ6ExbXY1KhcdnZVSi7ZwMgNHq3qZ58fhVq0dK+NSP2UclQwkKVMKmfvQx6bfXJ6MihBBCJIoEKo3BzKgoHjxeX8zDiit8VkaFWDUqRkBRUlqO1x/IqIQvTzZX/ZgZExVbUGfaQFDiMrrWSmdaIYQQqUgClcZgLE8G8FWVxzxs4R+7rU0JcUUPVBxOc2mxn+IKb0TXWZM3rEbFpwQ6z9ptdn3TwiDOevRRkRoVIYQQiSKBSmNwpFvf+qrKYh6maRqZitHwLUagkpupBz0uxcfecg8uxegsG5ZR6dgiFwhM/fiCtnWy2RQrkLGukxoVIYQQKUgClcZgs+FV9EDAVxk7UCn3+Mk0i19j1KiYPVCc+KjyBqZ+sIcGKvnGyh4zQ+NXQvukmMW2JofUqAghhEhBEqg0Eq9Nz6r4KktjHlNR5QkUv8ZY9WN2l3Xgp9IbtOFgeKBhFN1mGIFPZKASmlFRJFARQgiRgiRQaSQ+exoAi1ZviXmMPzjbEmvVjz0oo+JTg2pUwmpMjBU+5ioivy00MAkPVMzj60KKaYUQQiSKBCqNxGvTA5UmrtirflSPnm1RFTs40qIfZAQULnzVZlQ0I/NiTiVVqeGBSlhgIrsnCyGESEESqDSStAy9OFbxVsQ8xm4EKj57BigxshRGAOI0AxUleo2KZgQ06cZUUnp6aODji8iohNasCCGEEKlAApXGYvRSUbyxlyfbfPptPkdGzGPMzIdD8VMRXEwbtupHVcyMij71o4VN7XiDlit7cMQOjIQQQogkkkClkShGL5XK8tjFtIWbtwHgd8SoTwEro+LCR5XPH7OPihpWTKvZQm8Pzqj4w7MrQgghRIqQQKWR2F2B7rQ79ldG3P7b5mKcfn1ayO+sOVDRp36qyagYgYrbmBoya1ZMvqDlycHN4OpCimmFEEIkigQqjcRt1KikU8nuUk/E7T9v2GO1z1erDVSMqR9zebISI6MSthxZC7vdF3S7Ws9ARYpphRBCJIoEKo3F2kHZg1+N/sZuLiXWnNXUqNgCGRV96idWjUpY8BEeqARN9/iUui9NFkIIIRJJApXGYm1MWBUzUMlEn/rRYrTPBwI1Koo+9eOO0UdFDe+LEj71ExTI1DejIoQQQiSKBCqNxal3pk3Hgy9moFJ9+3wgZOrnty3FuGNkVDRb/BkVvwQqQgghUpQEKo3FmvqpJqNibEioxGqfDyGdaQt37LeKZWua+nG7Q/uo+IMyLhFBTS1JMa0QQohEkUClsbjimfrRa1SUaqd+9KDChS+wNBkiApXwlvmZGaF1L8F9VSKmiWpJimmFEEIkigQqjSVo6id2RsUopnVXF6gEMipWIS1E1qiEZVRs4S32g/qqaFJMK4QQIkVJoNJYgqZ+fKoacXOVTw10kY1zebI7OFCJ0ZnWpITv5RNUXKvWY58fIYQQIpEkUGksZkZFqULVIjMqC/7YTYYRqDjTq6lRMaZ0nEpg6senOCNa4GdlpIfeL2zVjxKUYfHZw46tJalREUIIkSgSqDQWI0uSjgefPzJQaZrhIsuY+snNbRL7PEb2w4UPt6I3jvPbIjMigzvlR72fKTjDotpj7NQshBBCJJkEKo3FqlGJXkxb7vFbGRXiqFFxENjnx29zRxymOMKCj/BAJSijojrql1GRYlohhBCJIoFKYzEClTTFgz/K1E+5128V01bfR8WY+sFn1aioUTIqRAQqoVM/tgYMVIQQQohEkUClsRjFtBlU8dTXhRE3V3h8VjEtrvj6qLjRp35Ue2RGxQyMwu9nsgUX34YfK4QQQqQICVQaiyuw6mfD7vKIm8urggOVmlf9OPFbzd6irtoJz6iEBSOqOyfmbbUlxbRCCCESRQKVxmJkVNIUL5rmj7jZ56nCqRjXVxeoGKt+bIpGhtlyP56MSvhGh2m51retmjWtfuxCCCFEkkig0liCAge7vzLydk9p4PtqO9MGsidWBsYRJaNid6EGZzrCA5egQMWeVs1uzXGQYlohhBCJkrBA5b777uPII48kIyODvLy8qMds3LiRE088kYyMDFq0aMHf//53fD5f1GMPeEEFq2la5MqfstJiwFgqbK9m752gQCXL2BsoYpoHQFHwEBTAhGVUfEF1MM60agIjIYQQIokSFqh4PB7OPvtsrr766qi3+/1+TjzxRDweD99//z2vvPIK06dP54477kjUkJLLZkNzmE3fPHj9ge60O/dXkYkRdFQ37QMhq3eyjPvYnFGmfgBf8LJlV2ig4kgP9GpxZsnUjxBCiNSUsEDl7rvv5oYbbqBfv35Rb585cybLly/nv//9LwMHDmTChAncc889PP3003g8nkQNK7nMJcpU4QvKqGwvqbSmcWzV9VABUBR8ip4pyVb0otzszOj3Sc8Iuj5s6mdY327W9/acNvGNPwYpphVCCJEoSatRWbBgAf369aNly5bWdePGjaOkpITff/895v2qqqooKSkJ+TpgWPv9ePD6AhkVr18N9FBxV7M02eA3pn9y0AMVxRE9o2J3BQUnYVM/aXkt4agboccJ0HZw3A8hGqlREUIIkSjVFEMkVlFRUUiQAliXi4qKYt5v6tSp3H333QkdW6IorkAvFW/QxoQ+VQt0pa1p6gfw29KAUnKMjErUGhUIzaJEW4I89s54hi2EEEIkTa0yKpMnT0ZRlGq/Vq5cmaixAnDbbbdRXFxsfW3atCmhP69BBW1MuHxrIBPk9atBPVRqLmw19/bJoUy/ItqqHwgNesKXJwshhBAHgFplVG666SYuueSSao/p3LlzXOdq1aoVP/zwQ8h127dvt26Lxe1243ZHn+pIeWYvFTws/GMPo3u0AMDr1+Jrn29QnGlQSc0ZFVtQ23wJVIQQQhyAahWo5Ofnk5+fX/OBcRg+fDj33XcfO3bsoEUL/Q171qxZ5OTk0Lt37wb5GSnHyKhkUIkatN+PLzijEkeNSmZmFuwP1KgQo0YFNWipdxwBUF1JMa0QQohESViNysaNG9mzZw8bN27E7/ezePFiALp27UpWVhbHH388vXv35sILL+TBBx+kqKiIf/3rX0yaNOnAzZjUxCymDVueHFJMG09Gxcig5CjG1E+0zrQAihL9+wYmxbRCCCESJWGByh133MErr7xiXR40aBAAc+bMYfTo0djtdj777DOuvvpqhg8fTmZmJhdffDFTpkxJ1JCSz5r6qaIqKFCp8tWuRgWnEajUlFEZ8TfYuAB6n1bXEQshhBBJlbBAZfr06UyfPr3aYzp27Mjnn3+eqCGkHrOYFg9l/kAWYs7KHQyvxaofsyYlXTH6zcQKVLqPhyvnQX7POg9ZCCGESKakLU8+JBkZlQylCk9QRiUn3UmWWRgbvKtxLOGBSaxARVGgzcA6DFQIIYRIDbIpYWNymQ3fqvAFZVS8fo2sWhTTBu8bpF+OseqnkUgxrRBCiESRQKUxWS30I4tprQ0Ga2qhD5EZlCQvPZZiWiGEEIkigUpjslb9VPHFMr37bkmll/d+3mxtMBhfRiUsg5LApcdCCCFEMkmNSmOy+qhUAbBuVxlvLNoAEJRRiSNQcYYFKtLMTQghxEFKMiqNyalnPtKNQMXjU9m8Vw9QrIyKqy4ZFQlUhBBCHJwkUGlMrsCqHwC7Te+hAlr9pn6cyZ36kWJaIYQQiSKBSmMymrmZzd0URaHc4yOdKuyKUZBapxoVKaYVQghxcJJApTEZQYhZj2Iz2tqbS5M1lPgKY8MDkyRnVIQQQohEkUClMZmBijHNo2kaA9rlBQppXVnx7ckT3hROalSEEEIcpCRQaUwhUz8aqqZ/mYGLkhZHV1qAtNzA9zZH0hu+CSGEEIkigUpjMpq5ORU/brz4VfCpWmhGJa7zBAU06U0SujNyPKSYVgghRKJIoNKYggKRTCop9/iYNn997Vb8QGhGJb1pAw6wbqSYVgghRKJIoNKYbHZUY5+eTKWCF775A6AOgUpYRkUIIYQ4SEmg0shsRpCRRSXrdpUBkKmYGxLGOfUTnFGxOxtyeEIIIURKkUClsRnTP1lUGM3eINvKqMRZTBu8hNmZHvs4IYQQ4gAngUpjM7ImmUoFZVU+ALKUcuO2OKd+APqdo/876E8NObo6kWJaIYQQiSKbEjY2l9lLpZId+/VW+man2rhX/QCc9iwcdQO06NXQI6w1KaYVQgiRKBKoNDYja2LVpQDZtdk52WR3QMveDTkyIYQQIuXI1E9jcwdqVEy1XvUjhBBCHCIkUGlsrshAJVMCFSGEECIqCVQam1VMG5j6yVX0Zcohy46FEEIIIYFKo3OFbkwIkIsZqOQlYUBCCCFE6pJApbFFKaZtajeClvS8JAxICCGESF0SqDS2sGJaBZVMTTIqQgghRDQSqDQ2IxjJMepSsikP9CGRjIoQQggRQgKVxmZsIphn1KVYhbSOdHC4kzUqIYQQIiVJoNLYzEBFKQWgudSnCCGEEDFJoNLYrIxKKaDx+CkF+vVSnyKEEEJEkBb6jc0IVJyKn0wqcfm8xvV5yRuTEEIIkaIko9LYnOlodr0WJY9SXN4S/XrJqAghhBARJFBpbIoSVKdSRpam16pIRkUIIYSIJIFKEihGoPLEaR1xe4v1K43rhBBCCBEggUoyGEFJlywvlO7Ur8tsnsQBCSGEEKlJApVkMLMnFXuhbIf+fVbL5I1HCCGESFEJC1Tuu+8+jjzySDIyMsjLy4t6jKIoEV9vvfVWooaUOjKMQKV8N5QagUpmi+SNRwghhEhRCVue7PF4OPvssxk+fDgvvfRSzOOmTZvG+PHjrcuxgpqDSlYr/d/92wOBSlZ+8sYjhBBCpKiEBSp33303ANOnT6/2uLy8PFq1apWoYaSmnDb6v8WbocyoUZGpHyGEECJC0mtUJk2aRPPmzTn88MN5+eWX0TSt2uOrqqooKSkJ+TrgmIHK9t9B8+vfZ0pGRQghhAiX1M60U6ZM4ZhjjiEjI4OZM2dyzTXXUFpaynXXXRfzPlOnTrWyNQcsK6OyUf83qxXYnckbjxBCCJGiapVRmTx5ctQC2OCvlStXxn2+22+/nREjRjBo0CBuvfVWbrnlFh566KFq73PbbbdRXFxsfW3atKk2DyE1ZLcJvdykICnDaCgaSrKHIIQQ4iBVq4zKTTfdxCWXXFLtMZ07d67zYIYNG8Y999xDVVUVbrc76jFutzvmbQeMzObgzoEqY9rqAA9UFKqfrhNCCCHqqlaBSn5+Pvn5iaulWLx4MU2aNDnwA5GaKAq07Asbv9cvt+6f3PEIIYQQKSphNSobN25kz549bNy4Eb/fz+LFiwHo2rUrWVlZfPrpp2zfvp0jjjiCtLQ0Zs2axb///W9uvvnmRA0ptRQcFQhUOgxP7liEEEKIFJWwQOWOO+7glVdesS4PGjQIgDlz5jB69GicTidPP/00N9xwA5qm0bVrVx599FGuuOKKRA0ptRxxNWz5CfJ7QZtByR6NEEIIkZIUrab1wCmupKSE3NxciouLycnJSfZwDklrpwyki7pOv3BXcXIHI4QQ4oAQ7/t30vuoiAOfFNMKIYRIFAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMpKWKCyfv16LrvsMjp16kR6ejpdunThzjvvxOPxhBy3dOlSRo4cSVpaGu3bt+fBBx9M1JCEEEIIcYBxJOrEK1euRFVVnn/+ebp27cqyZcu44oorKCsr4+GHHwagpKSE448/nrFjx/Lcc8/x22+/8ec//5m8vDyuvPLKRA1NCCGEEAeIhAUq48ePZ/z48dblzp07s2rVKp599lkrUHn99dfxeDy8/PLLuFwu+vTpw+LFi3n00UclUBFCCCFE49aoFBcX07RpU+vyggULOProo3G5XNZ148aNY9WqVezduzfqOaqqqigpKQn5EkIIIcTBqdEClcLCQp588kmuuuoq67qioiJatmwZcpx5uaioKOp5pk6dSm5urvXVvn37xA1aCCGEEElV60Bl8uTJKIpS7dfKlStD7rNlyxbGjx/P2WefzRVXXFGvAd92220UFxdbX5s2barX+YQQQgiRumpdo3LTTTdxySWXVHtM586dre+3bt3KmDFjOPLII3nhhRdCjmvVqhXbt28Puc683KpVq6jndrvduN3u2g5bCCGEEAegWgcq+fn55Ofnx3Xsli1bGDNmDEOGDGHatGnYbKEJnOHDh/PPf/4Tr9eL0+kEYNasWfTo0YMmTZrUdmhCCCGEOMgkrEZly5YtjB49mg4dOvDwww+zc+dOioqKQmpPLrjgAlwuF5dddhm///47b7/9Nv/5z3+48cYbEzUsIYQQQhxAErY8edasWRQWFlJYWEi7du1CbtM0DYDc3FxmzpzJpEmTGDJkCM2bN+eOO+6QpclCCCGEAEDRzKjhAFVSUkJubi7FxcXk5OQkeziHpD+mDKCzul6/cFdxUscihBDiwBDv+7fs9SOEEEKIlCWBihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCKEEEKIlCWBihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCKEEEKIlCWBihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCKEEEKIlCWBihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCLqrXm2O9lDEEIIcZCSQEXUW06aM9lDEEIIcZCSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFSGEEEKkLAlUhBBCCJGyJFARQgghRMqSQEUIIYQQKUsCFVF/nUfr/7qykjoMIYQQBx9HsgcgDgLH/AuadoJuxyd7JEIIIQ4yEqiI+nOmw2GXJ3sUQgghDkIy9SOEEEKIlCWBihBCCCFSVsIClfXr13PZZZfRqVMn0tPT6dKlC3feeScejyfkGEVRIr4WLlyYqGEJIYQQ4gCSsBqVlStXoqoqzz//PF27dmXZsmVcccUVlJWV8fDDD4cc+9VXX9GnTx/rcrNmzRI1LCGEEEIcQBIWqIwfP57x48dblzt37syqVat49tlnIwKVZs2a0apVq0QNRQghhBAHqEatUSkuLqZp06YR159yyim0aNGCo446ik8++aTac1RVVVFSUhLyJYQQQoiDU6MFKoWFhTz55JNcddVV1nVZWVk88sgjvPvuu8yYMYOjjjqK0047rdpgZerUqeTm5lpf7du3b4zhCyGEECIJFE3TtNrcYfLkyTzwwAPVHrNixQp69uxpXd6yZQujRo1i9OjRvPjii9Xe96KLLmLdunV8++23UW+vqqqiqqrKulxSUkL79u0pLi4mJyenFo9ECCGEEMlSUlJCbm5uje/fta5Ruemmm7jkkkuqPaZz587W91u3bmXMmDEceeSRvPDCCzWef9iwYcyaNSvm7W63G7fbHfd4hRBCCHHgqnWgkp+fT35+flzHbtmyhTFjxjBkyBCmTZuGzVbzTNPixYtp3bp1bYclhBBCiINQwlb9bNmyhdGjR9OxY0cefvhhdu7cad1mrvB55ZVXcLlcDBo0CIAPPviAl19+ucbpISGEEEIcGhIWqMyaNYvCwkIKCwtp165dyG3BZTH33HMPGzZswOFw0LNnT95++23OOuusRA1LCCGEEAeQWhfTppp4i3GEEEIIkToSVkybasw4S/qpCCGEEAcO8327pnzJAR+o7N+/H0D6qQghhBAHoP3795Obmxvz9gN+6kdVVbZu3Up2djaKojTouc0eLZs2bZJppSSQ5z+55PlPLnn+k0/+DxJL0zT2799PmzZtql0VfMBnVGw2W0SxbkPLycmRX9Ikkuc/ueT5Ty55/pNP/g8Sp7pMiqlR9/oRQgghhKgNCVSEEEIIkbIkUKmG2+3mzjvvlJb9SSLPf3LJ859c8vwnn/wfpIYDvphWCCGEEAcvyagIIYQQImVJoCKEEEKIlCWBihBCCCFSlgQqQgghhEhZEqjE8PTTT1NQUEBaWhrDhg3jhx9+SPaQDhl33XUXiqKEfPXs2TPZwzpoffPNN5x88sm0adMGRVH46KOPQm7XNI077riD1q1bk56eztixY1mzZk1yBnsQqun5v+SSSyJeD+PHj0/OYA9CU6dO5bDDDiM7O5sWLVpw2mmnsWrVqpBjKisrmTRpEs2aNSMrK4szzzyT7du3J2nEhx4JVKJ4++23ufHGG7nzzjv55ZdfGDBgAOPGjWPHjh3JHtoho0+fPmzbts36+u6775I9pINWWVkZAwYM4Omnn456+4MPPsgTTzzBc889x6JFi8jMzGTcuHFUVlY28kgPTjU9/wDjx48PeT28+eabjTjCg9u8efOYNGkSCxcuZNasWXi9Xo4//njKysqsY2644QY+/fRT3n33XebNm8fWrVs544wzkjjqQ4wmIhx++OHapEmTrMt+v19r06aNNnXq1CSO6tBx5513agMGDEj2MA5JgPbhhx9al1VV1Vq1aqU99NBD1nX79u3T3G639uabbyZhhAe38Odf0zTt4osv1k499dSkjOdQtGPHDg3Q5s2bp2ma/vvudDq1d9991zpmxYoVGqAtWLAgWcM8pEhGJYzH4+Hnn39m7Nix1nU2m42xY8eyYMGCJI7s0LJmzRratGlD586dmThxIhs3bkz2kA5J69ato6ioKOT1kJuby7Bhw+T10Ijmzp1LixYt6NGjB1dffTW7d+9O9pAOWsXFxQA0bdoUgJ9//hmv1xvyGujZsycdOnSQ10AjkUAlzK5du/D7/bRs2TLk+pYtW1JUVJSkUR1ahg0bxvTp0/nyyy959tlnWbduHSNHjmT//v3JHtohx/ydl9dD8owfP55XX32V2bNn88ADDzBv3jwmTJiA3+9P9tAOOqqqcv311zNixAj69u0L6K8Bl8tFXl5eyLHyGmg8B/zuyeLgM2HCBOv7/v37M2zYMDp27Mg777zDZZddlsSRCdH4zjvvPOv7fv360b9/f7p06cLcuXM59thjkziyg8+kSZNYtmyZ1MSlGMmohGnevDl2uz2ionv79u20atUqSaM6tOXl5dG9e3cKCwuTPZRDjvk7L6+H1NG5c2eaN28ur4cGdu211/LZZ58xZ84c2rVrZ13fqlUrPB4P+/btCzleXgONRwKVMC6XiyFDhjB79mzrOlVVmT17NsOHD0/iyA5dpaWlrF27ltatWyd7KIecTp060apVq5DXQ0lJCYsWLZLXQ5Js3ryZ3bt3y+uhgWiaxrXXXsuHH37I119/TadOnUJuHzJkCE6nM+Q1sGrVKjZu3CivgUYiUz9R3HjjjVx88cUMHTqUww8/nMcff5yysjIuvfTSZA/tkHDzzTdz8skn07FjR7Zu3cqdd96J3W7n/PPPT/bQDkqlpaUhn87XrVvH4sWLadq0KR06dOD666/n3nvvpVu3bnTq1Inbb7+dNm3acNpppyVv0AeR6p7/pk2bcvfdd3PmmWfSqlUr1q5dyy233ELXrl0ZN25cEkd98Jg0aRJvvPEGH3/8MdnZ2VbdSW5uLunp6eTm5nLZZZdx44030rRpU3JycvjrX//K8OHDOeKII5I8+kNEspcdpaonn3xS69Chg+ZyubTDDz9cW7hwYbKHdMg499xztdatW2sul0tr27atdu6552qFhYXJHtZBa86cORoQ8XXxxRdrmqYvUb799tu1li1bam63Wzv22GO1VatWJXfQB5Hqnv/y8nLt+OOP1/Lz8zWn06l17NhRu+KKK7SioqJkD/ugEe25B7Rp06ZZx1RUVGjXXHON1qRJEy0jI0M7/fTTtW3btiVv0IcYRdM0rfHDIyGEEEKImkmNihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCKEEEKIlCWBihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCKEEEKIlCWBihBCCCFSlgQqQgghhEhZEqgIIYQQImVJoCKEEEKIlPX/XSPAPAtqwL8AAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -523,7 +588,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -557,7 +622,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -566,13 +631,13 @@
        "(0.0, 4.0)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -593,12 +658,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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GhXnPt4ezrQoHz+fhf2uPmuywHpEl4O8XmRJ9/X1k+bBwhy7kAQBaBbjq7TmDPRzw5eB2UEjAmv0X8PEfnIBKpG81231fu3ZN5iREN5SXlwPAv+5Ae7c44dSCFZVV4nRWEQCgdYB+t8nt2sgLM55qidd+PII521IQ4umAZ8MD9foaRNZMqVTC1dUVWVnVS+Xt7e31cumU6F5ptVpkZ2fD3t4eKtX91QeWDwt29GI+hAD8XWzh7az/TYoGdAjCxbxSfLHlNP639ihCvRzRPli/y9uIrJmvry8A6AoIkdwUCgWCgoLuuwizfFiwmvkerfU03+NWJvdoiOTMAvxx7DLGLtuP9RM7wc/F8CcxElkDSZLg5+cHb29vVFRUyB2HCDY2NlAo7n/GBsuHBTt8IR+Afud7/JNCIWFW/zZ4eu4enMwsxJhv92PV2GjY2dzf9UAiukGpVN73NXYiU8IJpxYsSTfyYcBjkQE4aFRYMDQcbvZqHLmYj/+tO8IZ+kRE9K9YPixUdmEZLuaVQJKAlvUMWz4AINDdHrOHVK+A+enARXyfcN7gr0lEROaJ5cNCHb6+xDbMyxFOtmqjvGbHME+89kgTAMDb64/h4PmrRnldIiIyLywfFurQ9fkerQ043+NWxnQJxSPNfVFRJTD+uwPcgp2IiG7C8mGhbuxsavhLLn8nSRI+frYVGng7IrOgFCOX7EVRWaVRMxARkWlj+bBAQgiD7Gx6t5xs1Vg8vAM8HW1w/FIBJi4/gMoqrdFzEBGRaWL5sEDpuSXIu1YBG6UCTfycZMkQ6G6PBUPDoVEpsDU5G2+vP84VMEREBIDlwyIlXR/1aOrvDI1Kvr0B2ga54fOBbSBJwLL4c1i0K022LEREZDpYPiyQbr6Hns9zuRePtPDD/x5tCgB4//cT2HDkksyJiIhIbiwfFqimfMgx3+NWRj0QguejgiEEMHllEpfgEhFZuTqXjx07dqBPnz7w9/eHJElYt25dra8LITB9+nT4+fnBzs4OPXv2xOnTp/WVl+6gskqLoxnXl9ka8EyXupAkCW/2aYYHm3ijrFKLF5buw/kcHhNORGSt6lw+iouL0bp1a8yePfuWX585cya++OILfP3110hISICDgwN69eqF0lLu92AMpy4XobRCCyeNCqGeDnLH0VEpFfhyUFs093dGTnE5RixJRP41HpRFRGSN6lw+evfujffeew9PPvnkTV8TQiA2Nhavv/46+vbti1atWuHbb79FRkbGTSMkZBg1S2xbBrhAobi/I4/1zUGjwjfDO8DPxRYp2cUY+90+lFdyCS4RkbXR65yPtLQ0ZGZmomfPnrr7XFxcEBkZibi4OH2+FP2Lmm3VTeWSyz/5ONvim+Ed4KhRIT41F//98TCX4BIRWRm9lo/MzEwAgI+PT637fXx8dF/7p7KyMhQUFNS60b1LSpdnW/W6aOrnjNlD2kGpkPDTwYv4fAvnBBERWRPZV7vMmDEDLi4uultgYKDckczWtfJKnLpcCABoY6IjHzW6NvLCe/1aAABiN5/Gj/svyJyIiIiMRa/lw9fXFwBw+fLlWvdfvnxZ97V/mjZtGvLz83W39PR0fUayKscyClClFfB20sDXxVbuOHc0KCII47qGAQBe+/EwtiVnyZyIiIiMQa/lIyQkBL6+vtiyZYvuvoKCAiQkJCA6OvqW36PRaODs7FzrRvemZn8PU53vcSuv9mqMJ1r7o1JbfQruAe4BQkRk8epcPoqKipCUlISkpCQA1ZNMk5KScP78eUiShMmTJ+O9997DL7/8giNHjmDo0KHw9/dHv3799Byd/unQher5HqZ+yeXvFAoJnzzbGl0beaGkogovLN2Hs1eK5Y5FREQGVOfysW/fPrRt2xZt27YFAEydOhVt27bF9OnTAQCvvvoqJk6ciDFjxqBDhw4oKirCxo0bYWtr+pcBzN2xi9Xlo0U9+bdVrwsblQJzn2uHVgEuyC0ux7DFicgpKpM7FhERGYgkTGydY0FBAVxcXJCfn89LMHVQXFaJFm/9ASGAvf/rCS8njdyR6iy7sAxPzd2N9NwStAl0xYrRUbCzke9gPCIiunt1+fyWfbUL6cfJzAIIAXg7acyyeACAl5MGS0ZEwNVejaT0PEz64SCqtCbVjYmISA9YPizE8Yzq/VGa+5v3aFGYlyMWDA2HjUqBTccv4531x7gJGRGRhWH5sBDHrpePZmZePgCgQ313fNa/DSQJWBp3DnO3p8gdiYiI9Ijlw0Icv1Qz8mFek03/zWOt/PD6Y80AADM3JmNF4nmZExERkb6wfFiAyiotTmZW72zazM/8Rz5qjHogBOO7VW9C9r+1R/D7kUsyJyIiIn1g+bAA53OvobxSC1u1AkHu9nLH0atXezXGoIhAaAXw0g8HsfN0ttyRiIjoPrF8WIC065tyhXg6QqGQZE6jX5Ik4b1+LfFYSz9UVAmM+XY/9p/jLqhEROaM5cMCpGZXl49QLweZkxiGUiFh1oDW6HJ9F9QRixN1q3uIiMj8sHxYgNTrIx+hnpZZPgBAo1Li6+faITzYDQWllRj6TSLO5XAbdiIic8TyYQFSs4sAWO7IRw17GxW+GdEBzfyccaWoDM8vSkRWYancsYiIqI5YPizA3+d8WDpnWzWWjOyAIHd7nM+9hmHf7EV+SYXcsYiIqA5YPsxcYWkFsgqrD2Gz9JGPGt5Otlg2KgKejhqcuFSAUUv2oqS8Su5YRER0l1g+zNzZK9cAAJ6OGjjbqmVOYzzBHg5YNioCzrYq7Dt3FWO/24/ySq3csYiI6C6wfJi51CvX53tY8GTTf9PUzxmLR0TATq3EjlPZmLySB9EREZkDlg8zl2Lhy2zvpH2wG+YPbQ8bpQK/H8nEq2sOQ8sCQkRk0lg+zNyNyabWWT4AoHNDL3wxqC2UCgk/HriA/607ypNwiYhMGMuHmbuxzNbyV7rcziMtfPHZgDZQSMCKxPN4e/1xFhAiIhPF8mHGhBAc+fibJ1r7Y+YzrQEAS/acxYcbT7KAEBGZIJYPM3a5oAzXyqugVEgWd6DcvXqmfQDef7IFAGDe9lTEbj4tcyIiIvonlg8zVrPSJcjdHjYq/ihrDIkMxvTHmwEAPt9yGvO2p8iciIiI/o6fWGas5kA5XnK52cgHQvBKr8YAgBkbTmLhzlSZExERUQ2WDzOWZgUHyt2PmO4NMPHBBgCA9347wQJCRGQiWD7MWM1KlxAr3ePjbkx9qBEm/a2ALNjBAkJEJDeWDzOWqhv5sO5ltrcjSRKmPNQIk3o0BAC8//sJzN/BOSBERHJi+TBTZZVVSM+tPtfFWnc3vVuSJGHqQ43w0vUC8sHvJzkJlYhIRiwfZupczjVoBeCkUcHbSSN3HLMw5W8FZMaGk/iaBYSISBYsH2YqJev6zqbejpAkSeY05mPKQ40wuWd1Aflww0nM3cYCQkRkbCwfZirl+mTTMF5yqbPJPRthSs9GAICPNp7EnG1nZE5ERGRdWD7MVM1ptmFWfqbLvXqpZ0NMfai6gMzcmIzZW1lAiIiMheXDTN0Y+WD5uFeTejTEf64XkI//YAEhIjIWlg8zJITQzflo4M3LLvdjYo+GePnhGwXkq794FgwRkaGxfJihzIJSFOsOlGP5uF8vPthQtxX7J3+ewpdbWECIiAyJ5cMMpWRVz/cI9uCBcvoS072BroB8uukUvmABISIyGH5ymSHO9zCMmO4N8Ooj1QVk1qZT+HwzCwgRkSGwfJihk5kFAICG3iwf+jahWwO89kgTAMBnm08hdvMpmRMREVkelg8zdPRidflo7u8icxLLNL5bGP7bu7qAxG4+jc82nYIQQuZURESWg+XDzFRUaZGcWQgAaFHPWeY0lmtc1zBMu15APt9yGh9tTGYBISLSE5YPM3MmqwjlVVo4aVQIdLOXO45FG9s1DK8/1hQA8PX2FLz5yzFotSwgRET3i+XDzBy9mA8AaObvDIWCZ7oY2gudQ/HBky0hScC3cefw2o+HUcUCQkR0X1g+zMyxDM73MLbBkUGY1b81FBKwev8FvPTDQVRUaeWORURktlg+zMxxXfngfA9jerJtAGYPbge1UsKvhy9h3LL9KK2okjsWEZFZYvkwI1qtwLGM6ssuLepx5MPYerf0w/yh4dCoFNhyMgsvLN2Ha+WVcsciIjI7LB9m5FzuNRSXV0GjUiDMi9uqy6F7Y28sHRkBexsldp25guHf7EVRGQsIEVFdsHyYkZpRjyZ+zlAp+aOTS1SoB5aNioCTRoXEs7l4bmEC8ksq5I5FRGQ2+AlmRm5sLsb5HnJrH+yO70dHwsVOjaT0PAyaH4+cojK5YxERmQWWDzNSM/LB8mEaWgW44ocxUfB01OD4pQIMnB+PrIJSuWMREZk8lg8zIYTQrXRpwWW2JqOpnzNWjY2Cn4stTmcVYeD8eGTms4AQEd0Oy4eZyCwoRU5xOZQKCY19neSOQ38T6uWIlWOiUc/VDqlXitF/XhwuXL0mdywiIpPF8mEmjl28cZKtrVopcxr6pyAPe6wcG4Ugd3ucz72GAfPicS6nWO5YREQmieXDTJy4VF0+mvpxvoepCnCzx6qx0Qj1dMDFvBI8+3UcTl0ulDsWEZHJ0Xv5qKqqwhtvvIGQkBDY2dkhLCwM7777Lk8EvU8nr59k29SPl1xMma+LLX4YG4XGPk7IKizDwPnxurk6RERUTe/l46OPPsLcuXPx1Vdf4cSJE/joo48wc+ZMfPnll/p+KatyIrP6A6yJL0c+TJ23ky1+GBOFlvVckFtcjsEL43UHAhIRkQHKx549e9C3b1889thjqF+/Pp555hk8/PDDSExM1PdLWY2S8iqcvVI9f4CXXcyDm4MNvnshEm0CXZF3rQKDF8QjKT1P7lhERCZB7+WjY8eO2LJlC06dOgUAOHToEHbt2oXevXvf8vFlZWUoKCiodaPaTl0uhFYAno428HLSyB2H7pKLnRrLRkUgPNgNBaWVeG5hAvafy5U7FhGR7PRePv773/9i4MCBaNKkCdRqNdq2bYvJkydjyJAht3z8jBkz4OLiorsFBgbqO5LZO8lLLmbLyVaNpSMjEBnijqKySjy/KBFxKTlyxyIikpXey8eqVavw/fffY/ny5Thw4ACWLl2KTz75BEuXLr3l46dNm4b8/HzdLT09Xd+RzN6JS9WTTZtwfw+z5KBRYcmICDzQwBPXyqswfHEitiZnyR2LiEg2ei8fr7zyim70o2XLlnj++ecxZcoUzJgx45aP12g0cHZ2rnWj2pKvr3Th5mLmy85GiYXDwtGzqTfKKrUY++1+bDp+We5YRESy0Hv5uHbtGhSK2k+rVCqh1Wr1/VJWI+36ZNMG3o4yJ6H7YatWYu5z7fFYSz+UV2kx/rv92HDkktyxiIiMTqXvJ+zTpw/ef/99BAUFoXnz5jh48CBmzZqFkSNH6vulrEJxWSUyrx9WFuLpIHMaul9qpQKfD2wDlVLCz0kZeHHFQcRqBfq09pc7GhGR0ei9fHz55Zd44403MGHCBGRlZcHf3x9jx47F9OnT9f1SVuHs9S263R1s4GpvI3Ma0geVUoFZ/dtAqZDw04GLeOmHg6jUavFk2wC5oxERGYXey4eTkxNiY2MRGxur76e2SqnZ1eWDox6WRamQ8MkzraFWKLByXzqmrjqE8kotBnQIkjsaEZHB8WwXE1cz3yOU5cPiKBQSZjzVEs9FBUEI4LUfj2DJ7jS5YxERGRzLh4mrKR8hXiwflkihkPBu3xYY0yUUAPDW+uNYuDNV5lRERIbF8mHiUjnyYfEkScK03k0w8cEGAID3fjuBOdvOyJyKiMhwWD5MmBACadlFAIAQTy6ztWSSJOE/DzfGlJ6NAAAzNybj882nZU5FRGQYLB8mLLe4HAWllZAkINjDXu44ZAQv9WyIV3o1BgB8tvkUPv0zGUIImVMREekXy4cJu3C1BADg42QLW7VS5jRkLDHdG+B/jzYFAHz51xl8uOEkCwgRWRSWDxNWUz4C3OxkTkLGNrpLKN7q0wwAMG9HKt5ef5wFhIgsBsuHCUu/eg0Ay4e1Gt4pBB882RKSBCzZcxb/t/YotFoWECIyfywfJuyCrnxwvoe1GhwZhJlPt4IkASsSz+OVNYdRxQJCRGaO5cOE1Vx2CXTnyIc1ezY8ELEDqrdj//HABUxZmYSKKh7USETmi+XDhN2Y88GRD2vXt009fDWoLVQKCb8cysCE7w+grLJK7lhERPeE5cNECSH+dtmFIx8E9G7ph3nPt4eNSoFNxy9jzLf7UVrBAkJE5oflw0TlFJejtEILSQL8XFg+qFqPpj5YMrwD7NRKbD+VjReW7kNJOQsIEZkXlg8TlZ5bPerh62wLGxV/THRDxwaeWDKiA+xtlNh15gpGLElEcVml3LGIiO4aP9VMFPf4oNuJDPXAslERcNKoEJ+ai2HfJKKwtELuWEREd4Xlw0TpVrpwsin9i/bB7lj2QiScbVXYd+4qnluUiLxr5XLHIiK6I5YPE8XJpnQ32gS6YvnoKLjaq3EoPQ8D58fjSlGZ3LGIiG6L5cNEcZkt3a0W9Vywckw0vJw0OJlZiIHz45FVUCp3LCKif8XyYaK4tTrVRWNfJ6wcEwVfZ1ucySrCgPnxuJRfIncsIqJbYvkwQUIIXOTIB9VRqJcjVo2NRj1XO6RdKcaAefG6y3dERKaE5cMEZReVoaxSC4UE+Lnayh2HzEiQhz1Wjo1CsIc9zudew4B58Ui7Uix3LCKiWlg+TFDNfA9fZ1uolfwRUd0EuNlj5ZhohHo54GJeCfrPi8Opy4VyxyIi0uEnmwniZFO6X74utlg5JhpNfJ2QXViGgfPjcSwjX+5YREQAWD5MEpfZkj54OWnww5gotApwQW5xOQbNj8eh9Dy5YxERsXyYoovc3ZT0xNXeBt+9EIn2wW4oKK3EkIUJ2Hc2V+5YRGTlWD5MEC+7kD4526rx7cgIRIW6o6isEs8vSsTO09lyxyIiK8byYYJqLrvU48gH6YmDRoXFwyPQtZEXSiqqMGrJPmw+flnuWERkpVg+TIwQAhfzeNmF9M/ORokFQ8PxSHNflFdpMe67/fjt8CW5YxGRFWL5MDE5xeUordBCkgA/F5YP0i8blQJfDW6Lvm38UakVmLjiAH46cEHuWERkZVg+TMzf9/iwUfHHQ/qnUiowq38b9A8PgFYA/1l9CN/Fn5M7FhFZEX66mRjdfA9XjnqQ4SgVEj58qhWGRQdDCOD1dUexcGeq3LGIyEqwfJiYC1xmS0aiUEh464nmGNc1DADw3m8n8NVfp2VORUTWgOXDxPBAOTImSZLw2iONMaVnIwDAJ3+ewqd/JkMIIXMyIrJkLB8mhrubkrFJkoSXejbEtN5NAABf/nUG7/12ggWEiAyG5cPE1Fx24R4fZGxju4bhnb7NAQCLdqXh/9YegVbLAkJE+sfyYUKEENzdlGQ1NLo+Pn6mFRQSsCIxHS+vPoTKKq3csYjIwrB8mJCr1ypQUlEFAPB3tZU5DVmrZ8MD8fnAtlAqJPx08CJe+iEJFSwgRKRHLB8mpGa+h4+zBhqVUuY0ZM36tPbHnCHtoFZK+O3IJYxbth+l14sxEdH9YvkwIedzuccHmY5ezX2xYGg4NCoFtpzMwsgle3GtvFLuWERkAVg+TEhqdjEAINTLUeYkRNW6NfbG0pERcLBRYk9KDoYuSkRBaYXcsYjIzLF8mJDU7CIAQKiXg8xJiG6ICvXAshci4WSrwr5zV/HcwgTkXSuXOxYRmTGWDxOSeuX6yIcnRz7ItLQLcsOK0VFws1fj8IV8DJwfj+zCMrljEZGZYvkwEUIIpGRVj3w08ObIB5meFvVcsHJsNLycNDiZWYgB8+NwKb9E7lhEZIZYPkxEVmEZisuroFRICHJn+SDT1MjHCavGRqOeqx1Ss4vRf14c0q9PlCYiulssHyaiZtQj0M0ONir+WMh0hXg6YOXYKAR72CM9twT958Xp5isREd0NfsqZiJTr8z3CuNKFzECAmz1WjY1GA29HXMovRf95cThxqUDuWERkJlg+TARXupC58XG2xcoxUWjm54wrReUYOD8eSel5csciIjPA8mEiUrI58kHmx8NRgxVjotAuyBX5JRUYsiAeCak5csciIhPH8mEibox8sHyQeXGxU2PZqEhEh3qguLwKwxYnYltyltyxiMiEsXyYgNKKKlzMq16yyMsuZI4cNCosHtEBDzbxRmmFFqO/3YffDl+SOxYRmSiDlI+LFy/iueeeg4eHB+zs7NCyZUvs27fPEC9lEdKuFEOI6n9BejjYyB2H6J7YqpX4+rn2eLyVHyqqBCauOIBV+9LljkVEJkil7ye8evUqOnXqhO7du2PDhg3w8vLC6dOn4ebmpu+Xshg3znRxgCRJMqchunc2KgU+H9gWTrYqrEhMx6trDqOkvArDOtaXOxoRmRC9l4+PPvoIgYGBWLx4se6+kJAQfb+MRUmpme/BbdXJAigVEj54siXsbVRYtCsNb/5yDEVllZjQLYzlmogAGOCyyy+//ILw8HA8++yz8Pb2Rtu2bbFgwYJ/fXxZWRkKCgpq3axNzWTTMG6rThZCkiS8/lhTTOrREADw8R/JmLHhJIQQMicjIlOg9/KRmpqKuXPnomHDhvjjjz8wfvx4TJo0CUuXLr3l42fMmAEXFxfdLTAwUN+RTB4PlCNLJEkSpj7UCK8/1hQAMH9HKv637iiqtCwgRNZOEnr+p4iNjQ3Cw8OxZ88e3X2TJk3C3r17ERcXd9Pjy8rKUFZ243TMgoICBAYGIj8/H87OzvqMZpKEEGjx5h8oLq/Cpild0NDHSe5IRHq3cu95/PenIxACeKK1Pz7t3xpqJRfbEVmSgoICuLi43NXnt95/+/38/NCsWbNa9zVt2hTnz5+/5eM1Gg2cnZ1r3axJrQPlPOzljkNkEAM6BOHLQW2hUkj45VAGxi7bj9KKKrljEZFM9F4+OnXqhOTk5Fr3nTp1CsHBwfp+KYvw9wPlNCqlzGmIDOfxVv5YMCwctmoF/jqZhaHfJKKwtELuWEQkA72XjylTpiA+Ph4ffPABzpw5g+XLl2P+/PmIiYnR90tZhJoD5bizKVmD7o29sWxUJJw0KiSm5WLwggTkFJXd+RuJyKLovXx06NABa9euxYoVK9CiRQu8++67iI2NxZAhQ/T9UhZBt9KFO5uSlehQ3x0rxkTB3cEGRy7m49l5cbodfonIOhhkxtfjjz+OI0eOoLS0FCdOnMDo0aMN8TIWISWbIx9kfVrUc8HqcdHwd7FFanYxnpm7B2euX4IkIsvH6eYyuzHywfJB1iXMyxFrxndEmJcDLuWXov+8OBy+kCd3LCIyApYPGfFAObJ2/q52WD2uI1oFuCC3uByD5sdj1+krcsciIgNj+ZBRzYFyzrYqHihHVsvdwQbLR0ehUwMPFJdXYcSSRGw4whNxiSwZy4eMag6UC/N25JkXZNUcNSp8M7wDHm3pi4oqgZjlPBGXyJKxfMiIB8oR3aBRKfHloHYYEB4IrQBeXXMYC3emyh2LiAyA5UNGNZNNOd+DqJpSIeHDp1tiTJdQAMB7v53AzI08kI7I0rB8yKjmQDmudCG6QZIk/N+jTfHaI00AAHO2peD1dUeh5YF0RBaD5UMmQgjd1urcYIzoZuO7heH9J1tAkoDvE85jyqokVFRp5Y5FRHrA8iGTmgPlFBJ4oBzRvxgSGYzYAW2gUkj4OSkD43ggHZFFYPmQSc2oR5C7PQ+UI7qNvm3qYf7Q9tCoFNhyMgsjFu9FUVml3LGI6D6wfMikZr5HiCcvuRDdyYNNfLB0ZAQcNSrEpeZgyMIEXC0ulzsWEd0jlg+ZnNWVD042JbobUaEeWD46Em72ahxKz8OA+XG4XFAqdywiugcsHzI5m1NTPjjfg+hutQpwxaqx0fBx1uDU5SI8+3UczudckzsWEdURy4dM0q6PfNTnZReiOmno44Q14zoi2MMe53Ov4Zmv9yA5s1DuWERUBywfMqis0uJ8bvW/1up7sHwQ1VWguz1Wj41GYx8nZBWWof+8OBw4f1XuWER0l1g+ZJCRV4qKKgEbpQL+rnZyxyEyS97Otlg5Ngptg1yRX1KBIQsSsPN0ttyxiOgusHzIIO36fI9gD3soFTxQjuheudrb4PsXItGlkRdKKqowask+nohLZAZYPmRwlvM9iPTG3kaFBUPbo3cLX5RXaRGz/AC+iz8ndywiug2WDxmkcY8PIr3SqJT4anA7DIqoPhH39XVHEbv5FA+kIzJRLB8y0K104WRTIr1RKiR88GRLTHqwAQAgdvNpvPXLMR5IR2SCWD5kcC6n5rIL9/gg0idJkjD14cZ4+4nmkCRgadw5TFxxkOfBEJkYlg8jq9IKXMwrAQAEc+SDyCCGdayPzwe2hVop4bcjlzDsm0Tkl1TIHYuIrmP5MLLLBdXLbFUKCb7OtnLHIbJYT7T2x9IREXDSqJCQlosB87gdO5GpYPkwsvTrm4v5u9pxmS2RgXVs4ImVY6Ph5aTBycxCPDVnD85kcTdUIrmxfBhZ+tXqSy6B7txcjMgYmvk746fxHRHi6YCLeSV4as4exKfmyB2LyKqxfBjZhavVIx8BrpxsSmQsge72+HF8R7QLckVBaSWGLkrEz0kX5Y5FZLVYPowsPZcjH0RycHewwfLRUbrNyF76IQnztqdwLxAiGbB8GFn69ZGPQHeOfBAZm61aidmD22FkpxAAwIwNJ/F/a4+iokorczIi68LyYWQXr8/5CHBj+SCSg0IhYXqfZnj9saaQJGBF4nk8vygBV4vL5Y5GZDVYPoyookqLS/nXL7u48bILkZxe6ByKhUPD4WCjRHxqLvrO3o3Tl7kShsgYWD6MKCOvBFoBaFQKeDlp5I5DZPV6NPXBTxM6IcDNDudzr+GpOXuwNTlL7lhEFo/lw4hqJpsGuNlBkrjHB5EpaOzrhJ9jOiGivjsKyyoxasleLNyZyomoRAbE8mFEumW2nO9BZFI8HDX47oVIDAivPhX3vd9O4LUfD6O8khNRiQyB5cOIMq6f6VKP8z2ITI6NSoEPn26JNx5vBoUErNp3Ac8tTEBOUZnc0YgsDsuHEWXkV58r4e/CM12ITJEkSRj1QAgWDe8AJ40KiWerJ6ImZ3IiKpE+sXwYUc1KFz8XjnwQmbLujb2xNqYjgj3sceFqCZ6asxubj1+WOxaRxWD5MKJLedUjH36uHPkgMnUNvJ2wbkInRIW6o7i8CqOX7cPX3BGVSC9YPoxECIGM6yMf/hz5IDILbg42WDYqEoMjgyAE8OGGk/jP6kMoq6ySOxqRWWP5MJK8axUoraieOe/LOR9EZkOtVOD9fi3w9hPNoVRI+OnARQyaH4/sQk5EJbpXLB9GcvH6ShdPRxvYqpUypyGiupAkCcM61seSER3gZKvCgfN56Dd7N45nFMgdjcgssXwYyaXrK1042ZTIfHVu6IV1MZ0Q4umAi3kleHruHmw8mil3LCKzw/JhJDdWuvCSC5E5C/NyxLoJnfBAA0+UVFRh3Hf7MXvrGU5EJaoDlg8jybi+0sXflSMfRObOxV6NxSM6YFh0MADg4z+SMXllEkorOBGV6G6wfBgJRz6ILItaqcDbfVvgvX4toFRI+DkpAwPmxyOroFTuaEQmj+XDSG7s8cGRDyJL8lxUMJaNjICLnRqH0vPQ56td2H8uV+5YRCaN5cNIavb4qMcNxogsTscGnvg5phMaeDvickEZBs6Px7K4s5wHQvQvWD6MoEorkMnVLkQWrb6nA9bFdMJjLf1QUSXwxs/H8Mqaw5wHQnQLLB9GcKWoDJVaAYUEeDtp5I5DRAbiqFHhq8FtMa13EygkYM3+C3h67h6cyymWOxqRSWH5MIKM6xuM+TjbQqXkW05kySRJwtiuYVg2KhLuDjY4llGAx7/cxYPpiP7G4J+EH374ISRJwuTJkw39UibrxgZjnO9BZC06NfDEb5MeQLsgVxSWVuKFb/fh0z+TUaXlPBAig5aPvXv3Yt68eWjVqpUhX8bk1Yx8cKULkXXxc7HDD2OiMbxjfQDAl3+dwbBvEnkuDFk9g5WPoqIiDBkyBAsWLICbm5uhXsYs1Ix81GP5ILI6NioF3nqiOWIHtIGdWoldZ67g0S92IiE1R+5oRLIxWPmIiYnBY489hp49e972cWVlZSgoKKh1szTcYIyI+rWth/UTO6GRjyOyC8sweGEC5mw7Ay0vw5AVMkj5+OGHH3DgwAHMmDHjjo+dMWMGXFxcdLfAwEBDRJJVzdbqLB9E1q2BtxPWxXTCU23roUorMHNjMoYv2YsrRbwMQ9ZF7+UjPT0dL730Er7//nvY2t75w3batGnIz8/X3dLT0/UdSXbc44OIatjbqPBp/9b46OmWsFUrsONUNh7jZRiyMnovH/v370dWVhbatWsHlUoFlUqF7du344svvoBKpUJVVe0NdzQaDZydnWvdLElllRZZhTVbq3Pkg4iql+MO6BCEn2Me0O2KOmhBPL7YcpqrYcgq6L189OjRA0eOHEFSUpLuFh4ejiFDhiApKQlKpVLfL2nSsgrLoBWASiHB04EbjBHRDY19nfBzTCc81a4etAKYtekUnluYgMs8nI4snErfT+jk5IQWLVrUus/BwQEeHh433W8Nala6+DjbQqGQZE5DRKbGQaPCrP5t0CnME2/8fBRxqTl49POd+OTZ1ujexFvueEQGwe02DaxmpYs/L7kQ0W083T4A6yc+gCa+TsgpLseIJXvx9vpjKKvk2TBkeYxSPrZt24bY2FhjvJTJqZls6svJpkR0B2FejlgX00m3Kdni3Wfx5Ow9SM0ukjcYkZ5x5MPAuMyWiOrCVq3EW080xzfDw+HuYIPjl6rPhlm59zyE4GRUsgwsHwaWWcANxoio7h5s4oMNL3VGVKg7rpVX4bUfj2Dssv3ILS6XOxrRfWP5MDAeKkdE98rH2RbfvxCF//ZuArVSwp/HL6NX7A5sP5UtdzSi+8LyYWCX8rjBGBHdO6VCwriuYVg7oRMaeFdvzT7sm0S8s/44Sis4GZXME8uHAdXaYIwjH0R0H1rUc8GvEx/AsOhgAMA3u9Pw6Bc7sf/cVZmTEdUdy4cBZRfd2GDMw5EbjBHR/bFVK/F23xZYNCwc3k4apGYX45mv9+D93zgKQuaF5cOAala6+DjbQskNxohIT3o09cGmKV3xVLt6EAJYsDMNj36+E/vO5sodjeiusHwYUCYnmxKRgbjYqzGrfxssGhYOH2cNUq8U49l5cXj31+MoKecoCJk2lg8Dqtnd1Jflg4gMpEdTH/w5uSueaR8AIYBFu9LQ+/MdSEzjKAiZLpYPA6pZZuvvypUuRGQ4LvZqfPJsaywe3gG+zrY4m3MNA+bH4e31x3CtvFLueEQ3YfkwIN3W6s4c+SAiw+vexBt/TOmC/uHVoyCLd59F7893IiE1R+5oRLWwfBhQRj53NyUi43KxU2PmM62xZEQH+LnY4lzONQyYH4+3fuEoCJkOlg8D0k045WUXIjKybo2rR0EGdggEACzZcxaPxO5EXApHQUh+LB8GUr3BWBkAjnwQkTycbdX48OlW+HZkBPxdbHE+9xoGLYjH9J+PoriMoyAkH5YPA8kuKkOVVkClkODJDcaISEZdGnnhjyldMCgiCADwbdw59IrdgT0pV2RORtaK5cNAala6cIMxIjIFTrZqzHiqJb4bFYl6rna4cLUEgxck4PV1RzgKQkbH8mEgNQfKcY8PIjIlDzT0xB9TumBIZPUoyHfx59Erdgd2n+EoCBkPy4eBXOJKFyIyUY4aFd5/siW+f+HGKMiQhQn4v7VHUMRREDIClg8D4dbqRGTqOjWoHgV5Pqr6pNzlCefR67Md2HWaoyBkWCwfBnJjjw8usyUi0+WoUeHdfi2wfHQkAt3tcDGvBM8tSsC0nw6jsLRC7nhkoVg+DOTC1eryUc+N5YOITF/HME9sfKkLhkVXj4KsSExHz1nbsf5QBoQQMqcjS8PyYSAXa8oHNxgjIjPhoFHh7b4tsGJ0FOp72ONyQRkmrjiIkUv24sLVa3LHIwvC8mEAJeVVyCkuBwAEutnLnIaIqG6iwzywcXIXvNSjIWyUCmxNzsZDs3Zg/o4UVFRp5Y5HFoDlwwAu5lWPejhqVHC2U8mchoio7mzVSkx5qBF+f6kzIkLcUVJRhQ9+P4nHv9iF/edy5Y5HZo7lwwBqykc9VztIEjcYIyLz1cDbET+MjsLMp1vBzV6N5MuFeHpuHKb9dAT51zghle4Ny4cBXORkUyKyIAqFhP4dAvHXf7qhf3gAAGBF4nl0/3QbVu1Lh1bLCalUNywfBnAxr3piFiebEpElcXOwwcxnWmPlmCg09HZEbnE5Xl1zGP3nxeHEpQK545EZYfkwAI58EJEliwz1wO8vdca03k1gb6PEvnNX8dgXOzH956PIL+GlGLozlg8D+PucDyIiS6RWKjC2axg2T+2KR1v6QiuqT8vt8ek2/HTgAi/F0G2xfBhAzchHAEc+iMjC+bvaYc6Q9lj+QiTCvBxwpagcU1cdwlNz9+BQep7c8chEsXzoWUWVFpkF1ee68LILEVmLjg08seGlLnj1kcZwsFEiKT0P/ebsxrSfjiD3+r5HRDVYPvQsM78UWgHYqBTwdNDIHYeIyGhsVApM6NYAW1/uhifb1oMQ1atiun28FYt3p3GDMtJh+dCzC3/bVl2h4B4fRGR9vJ1t8dmANlg5JgpN/ZxRUFqJt9cfx2Nf7MTO09lyxyMTwPKhZ5xsSkRULTLUA79OfAAfPNkSbvZqnLpchOcXJeKFpftwLqdY7ngkI5YPPeOBckRENygVEgZHBmHby90xslMIVAoJm09cxkOzduD9345zl1QrxfKhZzUbjHGlCxHRDS72akzv0wwbXuqMzg09UV6lxYKdaej2yVYsizuLSs4HsSosH3qmu+zC8kFEdJOGPk74dmQEFo/ogIbejrh6rQJv/HwMj3y+E1tPZskdj4yE5UPPeNmFiOj2JElC98be2PBSZ7z9RHO42atxJqsII5bsxdBvEnEyk1u1WzqWDz2q0grdyEeAu73MaYiITJtKqcCwjvWx7ZXuGNMlFGqlhB2nstH78514efUhZOaXyh2RDITlQ48y8kpQUSVgo1LAz9lW7jhERGbBxU6N/3u0KTZNqd6qXQhgzf4L6P7JNsRuPoXiskq5I5KesXzo0bmc6smmQe723OODiKiO6ns6YM6Q9lg7oSPaB7uhpKIKsZtPo+vHW7F0z1mUV3JSqqVg+dCjc7nV69aDecmFiOietQ1yw5px0fhqcFvU97DHlaJyvPnLMTz02Xb8fuQShOChdeaO5UOPakY+gj0cZE5CRGTeJEnC4638sWlqV7zXrwU8HTU4l3MNE74/gH6zd2P3mStyR6T7wPKhR2evVI981PfkyAcRkT6olQo8FxWM7a90w6QeDWFvo8ShC/kYsjABQxbG4/CFPLkj0j1g+dCj87k35nwQEZH+OGhUmPpQI+x4tTuGd6wPtVLC7jM5eOKr3Rj/3X6cySqSOyLVAcuHngghcPb6WQX1edmFiMggPB01eOuJ5vjrP93wVNt6kCRgw9FMPPzZdryy+pBuuwMybSwfepJVWIbSCi2UCom7mxIRGViguz1mDWiDjS91wUPNfKAVwOr9F9D94214Z/1xZBVyjxBTxvKhJzWTTeu52kGt5NtKRGQMjX2dsGBoOH6a0BHRoR4or9Lim91p6PzRVrz7K0uIqeKnpJ7UXHIJ9uB8DyIiY2sX5IbloyPx7cgItA1yRVmlFot2VZeQt9cfQ1YBS4gpYfnQk3MsH0REspIkCV0aeeGn8R3x7cgItLteQhbvPovOM7firV+O4TJLiEnQe/mYMWMGOnToACcnJ3h7e6Nfv35ITk7W98uYnJrLLpxsSkQkr5oS8uP4jlg2KgLtg91QVqnFkj03SgjPjZGX3svH9u3bERMTg/j4eGzatAkVFRV4+OGHUVxcrO+XMincYIyIyLRIkoTODb2wZlw0vhsVifBgN5RfLyFdPt6KN38+yhIiE0kYeJ/a7OxseHt7Y/v27ejSpcsdH19QUAAXFxfk5+fD2dnZkNH0RgiBVm//icLSSvw5pQsa+TjJHYmIiP5BCIE9KTmI3XwKe89eBQDYKBUYGBGI8d3C4OfClYr3oy6f3ypDh8nPzwcAuLu73/LrZWVlKCsr0/25oKDA0JH0Lu9aBQpLq09d5AZjRESmSZIkdGrgiY5hHohLyUHs5tNIPJuLb+PO4YfEdAzoUF1C/F1ZQgzNoBNOtVotJk+ejE6dOqFFixa3fMyMGTPg4uKiuwUGBhoykkHUrHTxdbaFrVopcxoiIrodSZLQsYEnVo6NwvLRkYgIcUd5lRbL4s+h28fb8Pq6I8jgZmUGZdDLLuPHj8eGDRuwa9cuBAQE3PIxtxr5CAwMNKvLLmv2X8DLqw+hY5gHlo+OkjsOERHVUdz1yzEJabkAALVSQv/wQEzo3gD1OBJyV0zissuLL76IX3/9FTt27PjX4gEAGo0GGo3GUDGMouZMgQbejjInISKiexEd5oHosGjEpeTg8y2nEJ+ai+8TzmPVvnQ8Gx6ICd3CEODGy+r6ovfLLkIIvPjii1i7di3++usvhISE6PslTE5N+QjzYvkgIjJn0WEe+GFMNH4YE4XoUA9UVAksTziP7p9sw7SfjuDC1WtyR7QIeh/5iImJwfLly/Hzzz/DyckJmZmZAAAXFxfY2Vnm0FVqNkc+iIgsSVSoB6LGeCAhNQefbzmNPSk5WJF4Hmv2p+OptgEY2zUUofwH5z3T+5wPSZJuef/ixYsxfPjwO36/uS21La/Uoun0jajSCiT8Xw/4ONvKHYmIiPQsMS0Xn285hd1ncgAAkgQ82sIP47uFoUU9F5nTmQZZ53wYeNsQk3M2pxhVWgFHjQreTuY9d4WIiG4tIsQd378Qhf3ncjF3Wwo2n8jCb0cu4bcjl9CtsRfGdQ1DZIj7v/4DnGoz+D4fli6lZr6HtyP/0hERWbj2we5YOMwdJzMLMHdbCtYfysC25GxsS85G2yBXjO8ahp5NfaBQ8PPgdniw3H26MdmU26oTEVmLJr7O+HxgW2x9uRuGRAbBRqXAwfN5GLNsPx6O3YFVe9NRXqmVO6bJYvm4TymcbEpEZLWCPRzw/pMtsfu1BzGhWxicNCqcySrCqz8eRpeZW7FgRyoKSyvkjmlyWD7u05ma8sFZz0REVsvLSYNXH2mCPdMexP892gQ+zhpkFpTi/d9PIOqDLXj/t+O4XMBD7GqwfNwHrVYgJat6a/UwjnwQEVk9J1s1xnQJw45Xu+Ojp1uiobcjisursGBnGjp/tBWvrTmMU5cL5Y4pO044vQ8Z+SUoqaiCWinxQDkiItLRqJQY0CEI/cMDse1UNuZuTUHi2Vys3JeOlfvS0b2xF8Z3a4AO9d2scrECy8d9qGmvIZ4OUCs5iERERLVJkoTujb3RvbE39p/LxYIdafjzeCa2Jmdj6/UVMqMeCEHvFn5QWtEKGZaP+3Ays7p8NPY1/c3QiIhIXu2D3dH+eXecvVKM+TtTsWb/BRw8n4cXlx9EsEcyRncOxTPtA6zidHT+c/0+JF8vH018nWROQkRE5qK+pwM+uL5CZlKPhnC1V+NczjW8vu4oOn74F2I3n8LV4nK5YxoUy8d9qCkfjX1YPoiIqG68nDSY+lAj7Pnvg3izTzPUc7VDbnE5YjefRscP/8I764/jYl6J3DENguXjHlVUaXV7fDTmyAcREd0jexsVRnQKwfZXuuHLQW3RzM8ZJRVV+GZ3GrrM3IpJKw7iZGaB3DH1inM+7lFqdjEqqqrPdAlws8zTeomIyHhUSgX6tPbH4638sOP0FczbnoI9KTn45VAGfjmUgZ5NvTG+WwO0D3aTO+p9Y/m4RzUttJEPz3QhIiL9kSQJXRt5oWsjLxy9mI+521Pw+5FL2HwiC5tPZCEyxB1THmqEqFAPuaPeM152uUfJXOlCREQG1qKeC2YPboctU7uif3gA1EoJCWm5GDg/HkMWxmP/uVy5I94Tlo97dJIrXYiIyEhCvRwx85nW2PFqdzwXFQS1UsLuMzl4em4chn6TiKT0PLkj1gnLxz06lpEPAGjmz5EPIiIyDj8XO7zXryW2vtwNgyICoVJI2HEqG/1m78aoJXtx9GK+3BHvCsvHPbhSVIbLBWWQJKCpH8sHEREZV4CbPWY81Qp//acbnmkfAIUEbDmZhce/3IWxy/bhxCXTXh3D8nEPjmVU/1BDPBzgqOGcXSIikkeQhz0+ebY1Nk/tin5t/CFJwB/HLqP35zsRs/wATpvoIXYsH/eAl1yIiMiUhHo5InZgW/w5uQsea+UHAPjt8CU8HLsDk384iLQrxTInrI3l4x4cu1g98tHc30XmJERERDc09HHC7MHtsOGlzujV3AdCAOuSMvDQrO344PcTKCytkDsiAJaPe1Iz8tGiHkc+iIjI9DT1c8a858Px68QH0K2xFyq1AvN3pKL7J9uwal86hBCy5mP5qKPC0gqczbkGgCMfRERk2lrUc8GSERFYPLwDQj0dcKWoHK+uOYzBCxKQXyLfKAjLRx3VTDb1c7GFu4ONzGmIiIjurHsTb2yc3AX/7d0Eturqj35nW/kWTHCpRh3VbOTSOsBV1hxERER1YaNSYFzXMDzawg+SBFmPBmH5qKOk83kAgLZBrrLmICIiuhdBHvZyR+Bll7o6mH4VANAm0FXeIERERGaK5aMOLuWX4HJBGZQKCS0DONmUiIjoXrB81MHB65dcmvg6wd6GV6yIiIjuBctHHdRMNuUlFyIionvH8lEHB89Xz/doG+QmcxIiIiLzxfJxlyqqtDh8oXpnU650ISIiuncsH3fpeEYByiq1cLZVIcTDQe44REREZovl4y7FpeYAACJCPKBQyLcxCxERkblj+bhLcSnV5SM6zEPmJEREROaN5eMuVFRpsfdsLgAgOpTlg4iI6H6wfNyFwxfycK28Cm72ajTxdZI7DhERkVlj+bgLNZdcokI534OIiOh+sXzchV1nrgDgfA8iIiJ9YPm4g4LSCuw7W725WJeGXjKnISIiMn8sH3ew6/QVVGoFQj0dUN+T+3sQERHdL5aPO9h6MgsA0L2Jt8xJiIiILAPLx21UVmnx1/Xy8SDLBxERkV6wfNzGnpQc5BSXw93BBhEh7nLHISIisggsH7ex/lAGAKB3C1+olXyriIiI9IGfqP+irLIKG49lAgCeaO0vcxoiIiLLwfLxLzYezURhaSV8nW3RoT4vuRAREekLy8e/WLLnLABgUEQQdzUlIiLSI5aPWzh8IQ8Hz+dBrZQwKDJQ7jhEREQWheXjFr766wwA4LGWfvB2spU5DRERkWUxWPmYPXs26tevD1tbW0RGRiIxMdFQL6VX8ak5+PP4ZSgVEmK6N5A7DhERkcUxSPlYuXIlpk6dijfffBMHDhxA69at0atXL2RlZRni5fSmtKIKb68/DgAYFBGIhj5OMiciIiKyPAYpH7NmzcLo0aMxYsQINGvWDF9//TXs7e3xzTffGOLl9Obt9cdx4lIB3OzVmNyzkdxxiIiILJJK309YXl6O/fv3Y9q0abr7FAoFevbsibi4uJseX1ZWhrKyMt2fCwoK9B0JAHClqEw3l0MIAQFAKwSEAASAcznF2H0mB5IExA5sC09HjUFyEBERWTu9l48rV66gqqoKPj4+te738fHByZMnb3r8jBkz8Pbbb+s7xk3ySyp0y2dv53+PNkXXRl4Gz0NERGSt9F4+6mratGmYOnWq7s8FBQUIDNT/8lY3exvEdA+DBAmSBEgAIEmQqv8PJEhoE+TK4kFERGRgei8fnp6eUCqVuHz5cq37L1++DF9f35ser9FooNEY/hKHu4MNXunVxOCvQ0RERLen9wmnNjY2aN++PbZs2aK7T6vVYsuWLYiOjtb3yxEREZGZMchll6lTp2LYsGEIDw9HREQEYmNjUVxcjBEjRhji5YiIiMiMGKR8DBgwANnZ2Zg+fToyMzPRpk0bbNy48aZJqERERGR9JCGEkDvE3xUUFMDFxQX5+flwdnaWOw4RERHdhbp8fvNsFyIiIjIqlg8iIiIyKpYPIiIiMiqWDyIiIjIqlg8iIiIyKpYPIiIiMiqWDyIiIjIqlg8iIiIyKpYPIiIiMiqDbK9+P2o2XC0oKJA5CREREd2tms/tu9k43eTKR2FhIQAgMDBQ5iRERERUV4WFhXBxcbntY0zubBetVouMjAw4OTlBkiS9PndBQQECAwORnp7Oc2NkwPdffvwZyIvvv7z4/huWEAKFhYXw9/eHQnH7WR0mN/KhUCgQEBBg0NdwdnbmXzwZ8f2XH38G8uL7Ly++/4ZzpxGPGpxwSkREREbF8kFERERGZVXlQ6PR4M0334RGo5E7ilXi+y8//gzkxfdfXnz/TYfJTTglIiIiy2ZVIx9EREQkP5YPIiIiMiqWDyIiIjIqlg8iIiIyKqspH7Nnz0b9+vVha2uLyMhIJCYmyh3Jarz11luQJKnWrUmTJnLHslg7duxAnz594O/vD0mSsG7dulpfF0Jg+vTp8PPzg52dHXr27InTp0/LE9ZC3elnMHz48Jt+Jx555BF5wlqYGTNmoEOHDnBycoK3tzf69euH5OTkWo8pLS1FTEwMPDw84OjoiKeffhqXL1+WKbF1sorysXLlSkydOhVvvvkmDhw4gNatW6NXr17IysqSO5rVaN68OS5duqS77dq1S+5IFqu4uBitW7fG7Nmzb/n1mTNn4osvvsDXX3+NhIQEODg4oFevXigtLTVyUst1p58BADzyyCO1fidWrFhhxISWa/v27YiJiUF8fDw2bdqEiooKPPzwwyguLtY9ZsqUKVi/fj1Wr16N7du3IyMjA0899ZSMqa2QsAIREREiJiZG9+eqqirh7+8vZsyYIWMq6/Hmm2+K1q1byx3DKgEQa9eu1f1Zq9UKX19f8fHHH+vuy8vLExqNRqxYsUKGhJbvnz8DIYQYNmyY6Nu3ryx5rE1WVpYAILZv3y6EqP77rlarxerVq3WPOXHihAAg4uLi5IppdSx+5KO8vBz79+9Hz549dfcpFAr07NkTcXFxMiazLqdPn4a/vz9CQ0MxZMgQnD9/Xu5IViktLQ2ZmZm1fh9cXFwQGRnJ3wcj27ZtG7y9vdG4cWOMHz8eOTk5ckeySPn5+QAAd3d3AMD+/ftRUVFR63egSZMmCAoK4u+AEVl8+bhy5Qqqqqrg4+NT634fHx9kZmbKlMq6REZGYsmSJdi4cSPmzp2LtLQ0dO7cGYWFhXJHszo1f+f5+yCvRx55BN9++y22bNmCjz76CNu3b0fv3r1RVVUldzSLotVqMXnyZHTq1AktWrQAUP07YGNjA1dX11qP5e+AcZncqbZkeXr37q37361atUJkZCSCg4OxatUqjBo1SsZkRPIYOHCg7n+3bNkSrVq1QlhYGLZt24YePXrImMyyxMTE4OjRo5xjZoIsfuTD09MTSqXyppnMly9fhq+vr0yprJurqysaNWqEM2fOyB3F6tT8nefvg2kJDQ2Fp6cnfyf06MUXX8Svv/6KrVu3IiAgQHe/r68vysvLkZeXV+vx/B0wLosvHzY2Nmjfvj22bNmiu0+r1WLLli2Ijo6WMZn1KioqQkpKCvz8/OSOYnVCQkLg6+tb6/ehoKAACQkJ/H2Q0YULF5CTk8PfCT0QQuDFF1/E2rVr8ddffyEkJKTW19u3bw+1Wl3rdyA5ORnnz5/n74ARWcVll6lTp2LYsGEIDw9HREQEYmNjUVxcjBEjRsgdzSq8/PLL6NOnD4KDg5GRkYE333wTSqUSgwYNkjuaRSoqKqr1L+i0tDQkJSXB3d0dQUFBmDx5Mt577z00bNgQISEheOONN+Dv749+/frJF9rC3O5n4O7ujrfffhtPP/00fH19kZKSgldffRUNGjRAr169ZExtGWJiYrB8+XL8/PPPcHJy0s3jcHFxgZ2dHVxcXDBq1ChMnToV7u7ucHZ2xsSJExEdHY2oqCiZ01sRuZfbGMuXX34pgoKChI2NjYiIiBDx8fFyR7IaAwYMEH5+fsLGxkbUq1dPDBgwQJw5c0buWBZr69atAsBNt2HDhgkhqpfbvvHGG8LHx0doNBrRo0cPkZycLG9oC3O7n8G1a9fEww8/LLy8vIRarRbBwcFi9OjRIjMzU+7YFuFW7zsAsXjxYt1jSkpKxIQJE4Sbm5uwt7cXTz75pLh06ZJ8oa2QJIQQxq88REREZK0sfs4HERERmRaWDyIiIjIqlg8iIiIyKpYPIiIiMiqWDyIiIjIqlg8iIiIyKpYPIiIiMiqWDyIiIjIqlg8iIiIyKpYPIiIiMiqWDyIiIjIqlg8iIiIyqv8H30R6RZrRU0wAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -608,7 +673,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -618,7 +683,7 @@
     },
     {
      "data": {
-      "image/png": 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OknyIHEp6dZ0QQojSTZIPkYOkHkIIIdxJkg+RQ9aKD+l8KoQQwtUk+RA5ZE04pAVGCCGEq0nyIYQQwqM0Gg2LFi3ydhjCiyT5EDkppw+FECJf8fHxPPnkk9SsWROTyUS1atXo3bs3K1as8HZoTsXGxjJ06FCio6MxmUxUqVKFLl26MGvWLDIyMrwdXpklk4yJHLImHDLyRQhRUHFxcXTo0IGQkBCmTJlCkyZNMJvN/PHHH4wcOZL9+/d7O0QHmzdvpmvXrjRq1IipU6dSv359ALZu3crUqVNp3LgxzZo1K9Kx09PTMRqNrgy3TJGaD5GDQ4dTyT2EEAU0YsQINBoNmzdvpn///tStW5dGjRoxZswYNm7cmOvrjh8/zr333ktISAhhYWH06dOHuLg4+/YtW7bQrVs3KlasSHBwMLfccgvbt293OIZGo+F///sfd911F35+ftSpU4dffvkl13MqpRgyZAh169Zl3bp19O7dmzp16lCnTh0GDBjA33//TdOmTQHo3Lkzo0aNcnh9QkICRqPRXqNTvXp1Jk6cyEMPPURQUBCPPvooAPPnz6dRo0aYTCaqV6/Oe++953Cczz77jDp16uDj40NERAR33323fZvVauWdd96hdu3amEwmoqOjefPNN+3bd+/eTefOnfH19aVChQo8+uijJCcn27cPGTKEvn378vrrrxMeHk5QUBCPP/446enpDueYNGkSNWrUwNfXl2bNmvHTTz/l+r65TL7r3npYYZbkFe5x6tIVFfPCYhXzwmJ17HyKt8MRotzJsWy51apUWrJ3blZrgWI+f/680mg06q233sp3X0AtXLhQKaVUenq6atCggRo6dKjatWuX2rt3rxo4cKCqV6+eSktLU0optWLFCvX999+rffv2qb1796phw4apiIgIlZSU5HDMqlWrqtmzZ6uDBw+q0aNHq4CAAHX+/HmnMWzfvl0Bas6cOfnGO2vWLBUaGqpSU1PtZe+//76qXr26sl57f2JiYlRQUJB69913VWxsrIqNjVVbt25VWq1WTZgwQR04cEBNnz5d+fr6qunTpyullNqyZYvS6XRq9uzZKi4uTm3fvl199NFH9nM8//zzKjQ0VM2YMUPFxsaqtWvXqq+++koppVRycrKqXLmy6tevn9q9e7dasWKFqlGjhho8eLD99YMHD1YBAQHqvvvuU3v27FGLFy9W4eHh6sUXX7Tv88Ybb6j69eurpUuXqkOHDqnp06crk8mkVq1a5fS9yPHZzKIw129JPkQOJy9eTz6OnpPkQwhPy/EFn5as1KtB3rmlJRco5k2bNilALViwIN99syYf33//vapXr579Iq6UUmlpacrX11f98ccfTl9vsVhUYGCg+vXXXx2O+fLLL9ufJycnK0D9/vvvTo/xww8/KEBt377dXnbmzBnl7+9vv02dOlUpZft9hIaGqrlz59r3bdq0qXrttdfsz2NiYlTfvn0dzjFw4EDVrVs3h7LnnntONWzYUCml1Pz581VQUJBDEpUpKSlJmUwme7KR3ZdffqlCQ0NVcvL138+SJUuUVqtV8fHxSilb8hEWFqZSUq5/j0+bNk0FBAQoi8WiUlNTlZ+fn1q/fr3DsYcNG6YGDBjg9LyuSj6k2UXk4NDnQ7qcCiEKQBWxjXbnzp3ExsYSGBhIQEAAAQEBhIWFkZqayqFDhwA4c+YMw4cPp06dOgQHBxMUFERycjLHjh1zOFZmMwmAv78/QUFBnD17tsCxVKhQgR07drBjxw5CQkLszRM+Pj48+OCDfPPNNwBs376dPXv2MGTIEIfXt27d2uH5vn376NChg0NZhw4dOHjwIBaLhW7duhETE0PNmjV58MEHmTVrFleuXLG/Ni0tjS5dujiNdd++fTRr1gx/f3+HY1utVg4cOGAva9asGX5+fvbn7du3Jzk5mePHjxMbG8uVK1fo1q2b/b0PCAjgu+++s7/37iIdTkUOWb9EpM+HECWAwQ9ePOW9cxdAnTp10Gg0he5UmpycTKtWrZg1a1aObeHh4QAMHjyY8+fP89FHHxETE4PJZKJ9+/YOfRcADAaDw3ONRoPVas01XoADBw7QokULAHQ6HbVr1wZAr3e8PD7yyCM0b96cEydOMH36dDp37kxMTIzDPlkTgYIIDAxk+/btrFq1ij///JPx48fz2muvsWXLFnx9fQt1rKLI7B+yZMkSqlSp4rDNZDK59dxS8yFyUDLUVoiSRaMBo793bhpNgUIMCwujR48eTJ06lZSUlBzbL1265PR1LVu25ODBg1SqVInatWs73IKDgwFYt24do0eP5rbbbrN33jx37lyR306AFi1aUL9+fd59991cE5SsmjRpQuvWrfnqq6+YPXs2Q4cOzfc1DRo0YN26dQ5l69ato27duuh0OsCW5HTt2pV33nmHXbt2ERcXx19//UWdOnXw9fXNdYhygwYN2Llzp8N7vW7dOrRaLfXq1bOX7dy5k6tXr9qfb9y4kYCAAKpVq0bDhg0xmUwcO3Ysx3tfrVq1fH++4pDkQ+SpqFWpQojyZ+rUqVgsFtq0acP8+fM5ePAg+/bt4+OPP6Z9+/ZOXzNo0CAqVqxInz59WLt2LUeOHGHVqlWMHj2aEydOALZaiu+//559+/axadMmBg0aVOyaAY1Gw/Tp0zlw4AAdOnTgl19+4eDBg+zdu5fPP/+chIQEe4KQ6ZFHHmHy5MkopbjrrrvyPcczzzzDihUrmDhxIv/99x/ffvstn376Kc8++ywAixcv5uOPP2bHjh0cPXqU7777DqvVSr169fDx8eGFF17g+eeftzeDbNy4ka+//tr+vvn4+DB48GD27NnDypUrefLJJ3nwwQeJiIiwx5Cens6wYcPYu3cvv/32G6+++iqjRo1Cq9USGBjIs88+y9NPP823337LoUOH2L59O5988gnffvttsd7ffOXbK8TDpMOp9x09l2LvcBp79rK3wxGi3MmrU19Jd+rUKTVy5EgVExOjjEajqlKlirrzzjvVypUr7fuQpcOpUkqdPn1aPfTQQ6pixYrKZDKpmjVrquHDh9uvA9u3b1etW7dWPj4+qk6dOmrevHkqJiZGffDBB7keUymlgoOD7SNLcnPgwAE1ePBgVbVqVaXX61VwcLDq2LGj+uKLL5TZbHbY9/Lly8rPz0+NGDEix3Gyx5Ppp59+Ug0bNlQGg0FFR0erKVOm2LetXbtW3XLLLSo0NFT5+vqqpk2bOnRqtVgs6o033lAxMTH212cdTbRr1y516623Kh8fHxUWFqaGDx+uLl++/p09ePBg1adPHzV+/HhVoUIFFRAQoIYPH+4wasdqtaoPP/xQ1atXTxkMBhUeHq569OihVq9e7fT9clWHU41SJetf26SkJIKDg0lMTCQoKMjb4ZRLR8+ncMuUVQAsH3MLtSsFeDcgIcqZ1NRUjhw5Qo0aNfDx8fF2OOKauLg4atWqxZYtW2jZsqW3w8nXkCFDuHTpkkunss/rs1mY67d0OBVCCCHyYDabOX/+PC+//DLt2rUrFYlHSSd9PkQOjnVhJapiTAghPG7dunVUrlyZLVu28Pnnn3s7nDJBaj5EDo5ru3gtDCGEKBE6depUKjvfz5gxw9sh5EpqPkQOWf/ISt+fmxBCiJJOaj7KoM9XH2Le1uPMfaw9FQNM3DhpBacSUwGIDvNj6sCWNKkazHPzdnL0whXmDG+HTnt9LL/UfAghhHAnqfkogyb/vp9DCSlMXRkLYE88AI5duMLjM7cBMG/bCTYfucD2YxcdXu84yZhkH0J4S2ms6hdlm6s+k5J8lGEWq/MPyVWzJZ/9ZHp1Ibwpc5rwzHU+hCgpMqe0zz4BW2FJs0sZpi3gtMjZEwyHmg9JPoTwOJ1OR0hIiH1RND8/PzQF/HsWwl2sVisJCQn4+fnlWPumsCT5KMPySj4cO5U6Zhiyqq0Q3hcZGQlQqFVZhXA3rVZLdHR0sZNhST7KMJ029/Y55Zhh5LpNaj6E8A6NRkPlypWpVKkSZrPZ2+EIAYDRaESrLX6PDUk+yrBjF66Q4aTfx4WUdC5eub4Udc4eH5JxCFFS6HS6YrevC1HSSIfTMmb53jP2x3/8e4bvNhx1ul+rN5bbH1ulekMIIYQHSfJRxsxYH+fwfMof+/N9jXQ4FUII4UmSfJQx2ZtMUs3WArwm23OZ50MIIYQbSfIhcnRKVTLPhxBCCDeS5KOM0VD44U9513wIIYQQriXJRxmT26ymecrjJTK9sxBCCFfTqBJ2dUlKSiI4OJjExESCgoK8HU6psv3YRfp9tr5Ir21aNRh/o55alfyZufGYw7Y7mlamVUwoD7aLQa+7nq+uP3SOpKtmejauXKy4hRBClH6FuX7LPB9lSFETD4BdJxIB2HD4fI5ti3edZvGu0wA83KGGvXzgV5sAWDe2M1VCfIt8biGEEOWLNLuIAtt29KLT8nOX0zwciRBCiNJMkg9RYCWrgU4IIURpJcmHKDDHIbiSiQghhCgaST5EgcnMp0IIIVxBkg9RYFnXgMn6WPIQIYQQhSGjXcqIWZucLyDnSn/8e4bqY5fgY9ASHebnsE0pxYsLd1MtzI8RnWq7PRYhhBCllyQfZcRLC/d47FypZiv/nUl2KNt5IpE5m48DSPIhhBAiT9LsUk58NqglXw9u7ZZja4Ar6RluObYQQoiyR5KPcsKg09KlQYS3wxBCCCEKl3xMmjSJG264gcDAQCpVqkTfvn05cOCAwz6pqamMHDmSChUqEBAQQP/+/Tlz5oxLgxaFV6Q1X4QQQgg3KFTysXr1akaOHMnGjRtZtmwZZrOZ7t27k5KSYt/n6aef5tdff2XevHmsXr2aU6dO0a9fP5cHLgrHncmHpDVCCCEKo1AdTpcuXerwfMaMGVSqVIlt27bRsWNHEhMT+frrr5k9ezadO3cGYPr06TRo0ICNGzfSrl0710Uu7FLNlnz3sbhxYg6LVXE59XqfD6tVodVqsFiVfUiuXqtBo9G4LQYhhBClR7FGuyQm2hYjCwsLA2Dbtm2YzWa6du1q36d+/fpER0ezYcMGp8lHWloaaWnX1wZJSkoqTkjlzuu//sv0dXH57ufOGUn7T3Nc0G7x7tPc1jiSm95eSXxSKgAd64bz3dA2botBCCFE6VHkDqdWq5WnnnqKDh060LhxYwDi4+MxGo2EhIQ47BsREUF8fLzT40yaNIng4GD7rVq1akUNqVxylnjc1aIKnetXokqIL7c3rUydSgH0aBQJwDt3NyXIR0/ragF00u5glG4hY/VzGKJbSkNNHK5oRBk95x8OJaTYEw+ANf8lFPu4QgghyoYi13yMHDmSPXv28PfffxcrgHHjxjFmzBj786SkJElAiumD+5rnuu3e1tW4NzQWfn0SjDknJtttrc4nGXcxadxYjl68Sr/P1js5Sv7MFmuRXieEEKLsK1LyMWrUKBYvXsyaNWuoWrWqvTwyMpL09HQuXbrkUPtx5swZIiMjnR7LZDJhMpmKEoYoin8Xwk/DQFnAryLU6QY+IXDhMNbDq2hCHF8aP8D8ywEMbd4q8mnSJfkQQgiRi0IlH0opnnzySRYuXMiqVauoUaOGw/ZWrVphMBhYsWIF/fv3B+DAgQMcO3aM9u3buy5qUTRn9sLCx22JR5N74I4PwRRg37z134NsmTOB4bolGA/+Rt343dTTjOSAii70qTIsMgZGCCGEc4Xq8zFy5EhmzpzJ7NmzCQwMJD4+nvj4eK5evQpAcHAww4YNY8yYMaxcuZJt27bx8MMP0759exnp4m1WK/w8AjJSoXZXuOtLh8QDIM0YwpSM++mT/gYqtDqmy8eZZ5xAK82BXA6aO2l2EUIIkZtCJR/Tpk0jMTGRTp06UblyZftt7ty59n0++OAD7rjjDvr370/Hjh2JjIxkwYIFLg+8PFNKsf7QOZbsOl3wF+1dBKf+AWMA9PkMtDl/9RnX5gLZp2LQDF9JcsQNBGmu8L1xMh20uwsV4wvzdzkt3xp3gYTLaew5mchvu09z6tJV+8+08fB5Ll1JL9R5hBBClD6FbnbJj4+PD1OnTmXq1KlFDkrkbevRiwz8alPBX6AUrJlie3zjkxDofJr1IJ8sHwe/MA71/J5L39zLLbpdfGOYwiPmZ1lrbVqgU564eDVH2frYcwz8X8644ybfzuJdp3lyzj9UCjSx+aWuOfYRQghRdsjaLqXQvtO5z4UyfcgNOQuPb4Kze0HvC20fz/W1LaNDefyWWrxz97UEQ+/LcPMz/GFpjUmTwVeG92in3VvkuP/afzbXbX/8axuKffZyWq77CCGEKBsk+SiFcuvMadJrubV+pZwbtn5ju29yN/iG5HpcjUbD2F71ubf19aHO6RgYZR7NCksLfDRmvjZMKVIfELjerOOMTiuznwohRHkhyUcplNs6LUadk19nWjLs/dn2uPXDRTqfGT0jzP/HGksT/DVpzDC+QzNNbKGPk9fwW51MvS6EEOWGJB+lUG41CFpntQexy2wjXEJrQFTLIp8zDSOPmsewwdKQQM1VvjNOppEmrlDHMGc4Tz4s19aCEUIIUT5I8lEKWazOL+J6Zxfwvb/Y7hveCcWsXUjFxDDzs2y11iVYc4XvjJOoozlR4NfnNvw2PcMqNR9CCFGOSPJRCi3f57zjZo7aA3MqHPzT9rjBnYU+j7P6lSv48HD68+y01qSC5jKzjG9RXVOwIb+LdpxyWt5g/FLmb887iVkfe473/jxAhswfIoQQpZ4kH6XQjuOXnJbf1aKKY8GRNZCeDIFRRWpyiQr2yVEWYNJzGT8eSh/LPms0lTSXmG18k6qa3EeyFERenVEBBv5vE5/8FZtvkiKEEKLkK/LCcqJkeaxjTcZ0r+tYeHil7b5ON6eTiuWnUpAPcx9tR4CPHqUgJS2DWpUCWLLrNG/+to8H0scx1ziR2tpTzDa8yfNBb1O9Rh1+2HLcBT+Rc87mDxFCCFG6SM1HGfF0t7qY9DrHwsOrbPc1OxX5uG1rVqBRVDCNqwTTtmYFKgaYGHxjdXo1juQ8wQxMf4k4awTR2gR+ML3F2JtCi3yugtBK3xAhhCj1JPkoI3IMs70cb5tYDA3UuMXl58tsJjlLKIPSX+Q0FeF8LIE/3UMouU+CVlxOO9UKIYQoVST5KGVym+I+R2fTw6tt95Wbgn8Fl8eRtePnScJ5Qv86BESiS9jH98bJBJHi8nMC6HSSfAghRGknyUcpk9dEXQ7sTS63uiWO7LOsntREwuBfUH4VaayNY4bxbfxxff8MGZIrhBClnyQfpcDmIxfo8cEaNh0+z/nkAq76GrfWdl/T9U0uAGZno1PC65HxwEIuKX9aamP5xjgFP1ILfezqY5dQfewS5mw+Ro8P1jDp9332bTqthh82H6PXR2s5nSidT4UQojSS5KMUuPeLDRw4c5n7vtzIwbPJObY3igpyLEg8AYnHQaODqm3cEtOTnWs7PH/9zkYA6Cs34cH0cSQpX9pq9xerBmTcgt0cOHOZL1YftpdpNRrGLtjNvtNJvPXb/qL/AEIIIbxGhtqWMulOpij/eWQHx4JjG233kY3BFOCWOG6oHsbOV7sT5KMnKTWDYF8DYFuc7qZbuvHgaivfGyfTRnuAGca3GZL+Ain45jhO94YR7Dh+qcCr2Wbt2pKcanbJzyKEEMKzpOajlEnLsOQo02cf6XJ8k+2+Wju3xhLsa0Cj0dgTj0wmvZadqjYPpI8jSflxg/Y/vjW+TQBXchwj0MdAxQBTgc+pydLnI5fFfYUQQpRwknyUMs5qPnLIrPmIbuveYHKhwZYg7FK1GJT+IonKj9a5JCBKKUyGgn8Ms/Y3zW3kjxBCiJJNko9SJt/kIy0ZzuyxPXZzzUdusjaN7FY1GZj+EpeUP620B/nOOJnALAmIwskcJXnImm9YJfkQQohSSZKPUmb7sYt573ByKygrBFeD4Cp57+sm2UfD/qtqMCj9RfsomKwJiFIKo77gH8PYLB1ur6ZbOJOUitWqOBB/mWPnczbrXLqSTqo5Z1OVEEII75EOp6XMj1vzWVjtWGZ/D+80uQD4m3J+rGwJyEvMNL5FC20s3xsn8VD6CwT6GEhOyyjwsb/feNT+ePuxS7R9a4XD9tmPtOXG2hUBuJiSTouJywjzN7L9lW5F/GmEEEK4mtR8lGItokOY/0R7x8Ljmf09vNPkAjCgTTQdalcgzN/ILXXDWf1cJwD+VdUZmP4SF1QAzbWHmGN8kzEdwhw6kRbXl2uvD8vddtRWS3QhpYBzowghhPAIqfkopaqG+rJwRLYhtlYLHN9ie+zFmg8fg45ZjzgmP3GTbwdg7PxdDNj6MjONk2ikPQo/3kWQzwSXnduSZfKzDGsBZ4MVQgjhUVLzUZac3Qvpl8EYCBGNvB2NU0rBARXNfemvcF5bERL28/zpp4ninEuOn7VDrlnG4gohRIkkyUdZkjnEtmpr0Oq8G0s+Dqso3qj0HoTEEJFxkh9NE4jRxBf7uGlZkg+LsynghRBCeJ0kH2XJia22ey82ueQna/eOc4bK8PDvxBuqUlVzjh+NE6ityadDbT7MFqvTx0IIIUoOST5KKadTXJy8lnxUbe3RWAojR9zBVXin8gfss1YjQnOJucaJNNTEFfn4/55KYtvRC3y84iDP/bTLXt7xnZUs2H6C1f8lsOifk8zfdsJeM2KxKhZsP+F0qK4QQgjXkw6npVTbGmGOBVcvwvlY2+MqrTwfUAE1qBxof9ysaggAmxP0/JX+Mt8a36aZ9jBzjG8wOH0sO1TtXI6St/7TNuQoO3bhCmN+3OlQdsVs4cF2MczdcpwXF+4GrneMFUII4T5S81FKvXpntg6lJ7fZ7kNrgF9YzheUEIPaxdC7WRTdGkYw6trKuGaLlUsE8kD6i+zQ1CdYc4VZprcYWz+BjnXD3RbL5iMXANhw+LzbziGEECInST5KqeyLuXFyu+2+BDe5ABh0Wj4Z0IKvHmqNj8HWKTaza8Zl/Gg+7i+ocQv+pPL48ef5rv1Zt8WSOQ28TNMuhBCeJclHCVfgERuZnU2rlOzkwxlL1vk4jP4w8EeofwdY0uDHB7lHt8ot59Vm9n6V3EMIITxKko8SztlCcjptthlBlbre2bQE9/fITUb2BMvgA/d8Cy0eAGVliuFLHtEtcfl5M5MPqfkQQgjPkuSjhCtQ8nHpKFw5D1oDRDbxUGSuY3VWu6PTw52fwo1PAvCyYRbP63/AldUUmYvpSvIhhBCeJclHCXfgzOUcZbrsa6FkNrlENrHVGpQyOWo+Mmk00P0NJpkHADBC/wtv6f+HFtfM3/Hj1hNUH7uEVPP141Ufu4T1h5zPtvrO0v1MXRnrknMLIUR5JslHCbf2YEKOssdvqeVYkDnSpRQ2ucD1n+fOZlFOt39h6c0L5uFYlIaB+pV8avgYI2aXnX/1f47v8cCvNuXY5+Slq3y26hBT/jggM6cKIUQxyTwfJVz2JoGfHm9Pi+hQx50yk48SPtIlN6O71OGWeuE0jgp2un3Xa935dWdjzlpaE7n8SW5jM60itBzoNI2HZu7zSIzp2aZtz9H0JYQQosAk+SjhsjZJ9GwUSevq2ebwsJjh9LXJs0rhSBew9WFpmT2hyiLIx8CgtjFADEREwA+DiDi3kYj1wwjjUS4Q5PYYs+YaUvMhhBDFI80uJVzWzphOO0ae2QMZqeATDBVq5dxe1tS6FQb/Cr5hcGo7Pxlfo5rmjNtPq83SzybDKmvGCCFEcUjyUcJlrflw+v921v4e2TuillVVW8HQPyA4mpraeBYYX6Wx5rBbT5n1rZXcQwghikeSjxLKalVYrt0yKWc1Hycyk4/S2eRSZOF14ZFl/GuNIVyTxFzjRG7R7sz/dQWU+d6nZ1hzDAU2W21lTocICyGEyJf0+SiB9p1OotdHa3OUO73WlYKVbN0mMJL70l9hmuFDbtbt4WvDFMZmDOcnyy3FPnStF3/Lddsj325lx/FL+Bp0fDPkBtrXqlDs8wkhRHkiNR8l0MuL9jgtf+n2Bo4FqYlw7j/b41I6zLa4+rdvwFDz8yyw3IReY+VdwxeM0i0ks5HKqHf9R3zH8UsAXDVbGP7dVpcfXwghyjpJPkogZ6MposP8qBUe4FiYuZhcSAz4V/RAZCXP630as/+tO7nr9V/hpqcBeNYwj7f0X6PDwspnO/Fy9qTNhcpJLxshhHApaXYpJfQ6J5e58tzkkoVtzg0NdH0NgqqgfnuOgfq/CNdcwmC5yWGkistJ9iGEEIUmNR+lhN7ZpFaZNR/ltMnFqTbDOX/7/0hVBrrpthP20934pF9w2+kk9xBCiMKT5KOU0Gmz/aqUur6mS3kb6ZKPKzVvY1D6i1xS/uhPb+OOLQ9RU3PKLefSlJfhzUII4UKSfJQSOWo+Eo9DylnQ6qFyU+8EVUJZlWKbqkf/9NewhsQQdPUEC4yv0k671+XnSrxqW2MmOS2Dnccv2YdDJ1xOY/uxiw5lV9Iz+OfYRedDpoUQohyR5KMEcnZpql7R37Egs9YjojEYfN0eU2liMtg+1odUFTIeXsaF0GaEaFL4zjCJu3WrXX6+VLOFOz/9mz5T1/HnXttsqze8uZx+n62nz9R1LN0TD8CALzdy12frmbf1hMtjEEKI0kSSjxLIWfeOV3s3dCw4Jf09clM52JcnO9fmuR71MAZHEPTY7/wT1BmjxsK7hi94v8Iv3NaoEm1qhNEm+1o5RZB01czhhBQAFv1zMsf2hdfKdp5IBODHrceLfU4hhCjNZLRLCaRz0o+gYoDJseDUDtt9lZbuD6gUeqZ7PftjvY8/LZ6aDyvfgLXv0S/lB/r5pMP9n4HBl4NnLtPtgzVFPpc2S7ZotuSst8q+Jo80ugghyjup+SiB8h0aarVeTz6iWrg9njJBq4Uu46HPVFs/mX8XwLd3Qso55zPHFkLW5MJsybnwS0a2EzhdIFAIIcoRST5KoOwDW3K4cAjSL4PeFyrWy2dn4aDFA/DgQtsqwCc2w1ed0Z47UKxDZp0UzlnykX3SOMk9hBDlnSQfJZDOWaePrE79Y7uv3BR00nJWaDU6wrDlEFodLh2lxi99uUm7u8iHy5pcZDhpdsmRfBT5TEIIUTbIlasEORB/mWmrYlkXez7vHTOTD2lyKbrwuvDICvhhIPrjm5hheJs3Mh5ghqUHhZ067Ka3V9ofb467wPR1Rxy2rz90nomLrw/z3Xn8Evd/uYGKASY0Gg3Pdq9LTIXro5l+2nYCDXDy0lU6169E4yrBRfoRhRCipNKoEjbpQFJSEsHBwSQmJhIUFOTtcDyq10dr2Xc6KUd5n+ZRfHR/lkTjm55wbAPc9QU0u9+DEZZB5lRS5o/Cf/88AH7I6MQrGUMxezAvD/M3sv2VboBtfpAb3lzusD1u8u0ei0UIIYqqMNdvaXYpQZwlHgDj78gyzNZqgdM7bY+l5qP4DD743/cVsc3HotByv34VPwe8zdQ+VT0WwoWUdPvjpFSzx84rhBDeIslHCedn1FEh6zDbc/+B+QoYA6BCbe8FVpZoNNTuOw7NoB/BFETDjH+5feMgGmriPB5KCauIFEIIt5Dko7SxdzZtBlqdd2Mpa+p0s/UDCasFicf5yfg6PbWbPRpCcYf9CiFEaSDJRwmXo+ujdDZ1r/C6MHwF1LwVP00anxs/5P9089GQcwitO8gcIEKI8qDQyceaNWvo3bs3UVFRaDQaFi1a5LB9yJAhaDQah1vPnj1dFW+5k2PVVEk+3M83FAb9xDcZts/t04b5fGr4GF9S3X5qyT2EEOVBobv0p6Sk0KxZM4YOHUq/fv2c7tOzZ0+mT59uf24ymZzuJ67bH++8s6kDixnir81HIcmHe+n0TMh4iP2qGm/ov+F23Waqa87waPoYThLu8tNtOHSepXtO83fsuRzbrFbFs/N24mPU8dZdTVx+biGE8LRCJx+9evWiV69eee5jMpmIjIwsclDlUc8P1zotd6j3SNgPGalgCobQGh6JqzyrGGDkx+RbOWytzOfGD2mkPcovppd5Iv0pNqsGLj3Xy4t2c+ja4nTZLdl9mgXXFqd75faG+Bqlr48QonRzy2QGq1atolKlSoSGhtK5c2feeOMNKlSo4HTftLQ00tLS7M+TkgpQA1Be2ZtcmhVgDnZRXH+/0JlUswWjvgcn4m4jaNkjVEjYw1zfSZzp8DqJjQbT48OiL0iXVW6JB0CG9Xp/E7PVii+SfAghSjeXX8F69uzJd999x4oVK3j77bdZvXo1vXr1wmKxON1/0qRJBAcH22/VqlVzdUilW9aqD+nv4VE+Bh0hfkb8jHrq1m2AcfgyaNwfjTWDyLUvUW/LKxjIcHsc+iyJZnqGZzq+CiGEO7k8+bj//vu58847adKkCX379mXx4sVs2bKFVatWOd1/3LhxJCYm2m/Hjx93dUilmkOzi32YbXMvRCIw+kH/r6HLq4AGtk1nlvFNKpDosRAk+RBClAVur7uvWbMmFStWJDY21ul2k8lEUFCQw004YTHDmWvrg1Ru5t1YyjONBm4eAwPngimINtoD/GJ6mUZunJAs6/DbNEk+hBBlgNuTjxMnTnD+/HkqV67s7lOVSfahtucOgiUNjIHS2bQkqNsDHlnBIWtlqmjO85PxNe7QbnDLqbLWdmQ+TjVbuJpuIcNi5fK1KdkzywASr5hltlQhRIlV6A6nycnJDrUYR44cYceOHYSFhREWFsbrr79O//79iYyM5NChQzz//PPUrl2bHj16uDTwsmTNfwm5bgvyvfYrit9lu49sLJ1NS4rwutyVPoGPDZ/SSbeTT42f0CDjKO9l3IvVhXn9cz/tsj9Oz7BitSpueGM5V8wWYsL8OHwuhS0vdaXzu6tITs9g/hM30u+z9fRoFMEXD7Z2WRxCCOEqhf6G3Lp1Ky1atKBFC1unxzFjxtCiRQvGjx+PTqdj165d3HnnndStW5dhw4bRqlUr1q5dK3N95GHmxqNOy+tHBvLFA9cuHpnze0TKPA8lycNdmjPU/ByfZ9wBwEj9L3xleI9ArrjlfBlWK+kWK5fTMrBYFYfP2UbJrNh3hstpGSgFExfbmuf++PeMW2IQQojiKnTNR6dOnfKszv3jjz+KFVB5lOFkQY+BbaMdJ5TKXMk2sqmHohIF8XS3ujzdrS7Vx2rZZ43mfd+v6cI/7I54h63tp3L3vNxrtYrCqpTTWVCzFklrixCipJP6+xLAWfKRYcnSsVApqfkoBX623sSe7j9AYBSc+4/mS/txi3anS89hVc7Xf8laJrmHEKKkk+SjBLBYc45gyLBkuYQknoDUS6DVQyXXzqwpXCu5QlN4dBVUbYPefJlvDO8wXLcYV6UEFqvC4iz5yJLASkdTIURJJ8lHCWBxUvNhzlqW2dk0vD7ope9MSaYUEBgBQxZzosbd6DSKlwyzed8wDRPpxT6+VSmUk9G2WT8uknsIIUo6ST68zGyxsvHwhRzlDs0u0uRSaqjMGg69id0tJjLePJgMpaWf7m9+NE4ggpy/68IY+NUm/twbn6N8w6HzOWMAxi3YzZX0ws3CmpKWwS87T9mH8AohhKtJ8uFlC7efdFpeu1LA9SenM4fZSmfTki7M32h/XDHIh+8sPXjQPI6LKoBm2sP8anqZlpr/inWOrENvMy3993pCkrUVb87mYzzy7dZCHX/sgt2MnvMPo2b/U+QYhRAiL5J8eNn2YxdzlEUF+zCiU+3rBVLzUeJNG9SSl29vQKOoYHtZ65hQXuhZnytRN7L/zp+5EFCHSppLzDG+wT26VW6LJXury/ostSIF8evOUwCszmP+GSGEKA63rGoriufZHvWuL5t+9SIkHrM9luSjxOrVJOcMvhqNhic61eKJTrVsBY1XwcLHMO1fzBTDlzTUHOXNjEFkuPjPUDqcCiFKOqn5KOkyaz1CosE3xKuhiGIyBcC937Or9hMAPKz/g28NbxPCZS8HJoQQniXJRwnk8I+rvclF+nuUCVotu+s8wWPpT5OiTHTQ/csvxpeppznmslM4mwdECCFKEkk+SjrpbFom/WG9gX7pr3PMGk60NoEFxlfpod3ikmM7G7othBAliSQfXpR41cwPW47nvZN0Ni2zDqho7kx/g3WWRvhr0vjC+AH/p5uPBicTeRTCoYSUHGXVxy7hyzWHGDV7O+tizzl93dI98by8aHexzi2EEAUhyYcXvf/ngbx3MKdCwn7b48pS81FWtIoJtT++RCAPmcfyTUZPAJ42zGea4SP8SHX5ed/6bT+Ld53mse+3Od3++MxtzNzouuYfIYTIjYx28aJjF66vfNqjUYR9FVJ7pXnCPlAW8A2FoCqeD1C4Rf3IIH4e2QGdVsOJi1eIDPYl9mxLdpy8mQbbXqWnbgvVNfEMN4/huIpw+fmT0wo36ZgQQria1Hx4kU57/e0fdlPNnDuc+dd2H9EYNBoPRSU8oVm1EBpXCaZn48o0rxbC3a2qUq3zcAakv8xZFUJ97XF+Mb7Cjdo93g5VCCFcTpIPL9JlefeN+utP7PM0ZE0+RJmn1WjYrurSO+0NdlhrEqpJ5jvDZIboliJr1QohyhJJPrxIp71em2HUOflVnLn2X29EIw9FJEqCM4RxX/p4FlhuQq+x8prhO97Wf4URWWtFCFE2SPLhRVmbXUyGLDUfYJvsw17z0dCzgQmvS8PIGPMTvGEehEVpuE+/ih+MEwkn53T8RaWUcrjlt58QQriKdDj1knWx5+xraICTmo/ks3DlPKCB8AaeDU6UEBr+Z7md/1RVPjF8QkttLL+YXuGx9KfZpWoV68jVxy4p8H56rYYQPyOv3dmQO5pGFeu8QggBUvPhNdnnWogI8qF7wwiCfQ30bBwJZ6/VelSoBUY/L0QoPC3Y10D9yEDqVArg04Et0GigYoCJNdZm9EmfyEFrFSprLjDPOIG+2r89FleGVXEuOU1WuRVCuIzUfHhJ9kkojXotXzzYCotVoddprze5VJIml/JCq9Xw2+ibUdj6A/VsFIlepyXVbEGv1UDa3Syf1Jeuun/40PgZDTKO8nbGAKzyP4QQopSRby0vcbb+hkajsSUeICNdyimtVmPviJz5WfAx6NDrtOj9QhhufoZPM/oA8Jh+CTMMbxNEstfiFUKIopDkw0us+a2/IZ1NhRMKLe9m3MeeGz/gqjLSUbebn42vUEtz0tuhCSFEgUny4SWWvEYPWDIg4drU6zLMVjiREH0H/dNf44SqSA3tGRYZx9NZu93bYQkhRIFI8uEFhxKS+e/M5dx3uHAILGlg8IeQ6h6LS5QiGtirqtMnbSKbrPUJ1Fzlf4b3GKFbhDsnJNt29CJL95xm85ELHE6wNfdYrIp/TyXmX5snhBDXSIdTD9tzMpE7PnEcqRAeaHLcKXNysUoNQCv5ocgpwGT70z1PMA+kv8ir+m95QL+C5w0/0lB7jOfMj3IVH5eft/+09Q7Plz51MzM3HmXmxmOM7lKHMd3quvycQoiyR65sHrZ835kcZd8Pa+NYcGav7V6aXEQ2L95Wn/tvqEbrmFDG32HrD2RGz8sZw3jJPBSrRs8duo38ZHydKiS4PZ5VBxLsK+F+vOKg288nhCgbJPnwML3WcYG4EZ1qUT8yyHEne2dTST6Eo0c71mJy/6ZoNBqG3lSDuMm327fNsnRFO+RXzqkgGmmP8rPpFQZEHCdu8u32W51KAV6MXgghbCT58DBdtmaUDGft5JJ8iKKKuZE+aRP51xpDRU0SExNfhC1f2zfrtK5dHVlmXRdCFIUkHx6WvebDbLE67pCaCIm2amyZYEwUxUnC6Z/+Gr9a2qHHAkvGwK9PQUa665MPWW1XCFEEknx4mDbbl78le83H2X22+8Ao8AvzUFSirEnFxJPmJ5kb9DCggW3T4bs+VCDRpeeRmg8hRFFI8uFh32+Ic3hutmT79pYmF+EyGn4PHQgDfgBjIBxbz3uXnqKR5ojLzjDljwMOz19cuJuZG48yavZ2/vw3ni9WH+Lo+RSXnU8IUTbIUFsPSs+wEnf+ikNZjmYXmdlUFFKbGmFsPnKBm+tUBMDHoCXVbPtcta9ZAeq1geErYM4Awi8cYr7xNcaah7PIepPLY5m96Zj98eJdpwH4aMVB9k7o6fJzCSFKL0k+PChHE4uzMlnTRRTS5w+0YvGuU9zZzLbc/bKnb+Hb9XFUCfXlgXYxtp3C68Hwv7DMfwSf2GV8aPyMJhlHmJQxgCB/Py6kpBMeaCLhcprL47uSbnH5MYUQpZskHx7kbEp1h5oPpeDstTk+pLOpKKAwfyMPta9uf14tzI+X73Dy+fENQTdwLtu/e56Wcf9jmP53GmqO0n7Mr+Bf0b5b9bFLPBC1EKI8kz4fHmTJ3r8DyMhalngc0pJAq4eKMlOkcAOtjm01R/JY+lMkKx/a6/bCF7fAqX+8HZkQohyR5MODnNV8ZFiz1HxkzmxasS7ojR6KSpQ3CsUf1jb0TZ/AYWskJJ2Ar3vAjjneDk0IUU5I8uFBDonGNQ6jXexNLg08FJEoz2JVVfqmT4Q6PWwLGS56HH5/AT0Z3g5NCFHGSZ8PD3LW4dQhIUnYb7sPl+RDuI+G63PNJOFvG4q7ahKseQc2fc5M42pGpo/mPMEuO2fWfiQhfgbev7cZnetHuOz4QojSRWo+PMhZ8jHkxhrXn2ROMFapvociEuVR14bXL/o1w/1tKyd3fgnumwnGANpp9/GL6WWaaA675fyXrpgZOmOrW44thCgdpObDg7ImH3MfbUfFQBO1wq8t9GW1wLn/bI+l5kO4UY2K/mwY15mr6RaqhPpe39CgN1Ssy6FP+lBLe5qfjK/zonkY860dAWgUFcS/p5K8FLUQoiyRmg8PylxELshHT9uaFa4nHgAX4yAjFXQmCKvh/ABCuEjlYF9qhgdg0uscN4TXo2/6RJZbWmDSmHnP+Dmv6r9FTwYdald0fjAhhCgkST48yHot+dDrnLztmf09KtYFrS7ndiE85DJ+DDc/w0cZ/QB4WP8Hs4xv4W++4OXIhBBlhSQfHpRZ86HVOFlZVPp7iBJEoeWDjLsZnj6Gy8qXttr9PPzvEJpqDnk7NCFEGSDJh4copYhPSgVA72xZ84RrC3SFS/IhSo5l1tb0TZ/AIWtlgtLPMs84gbt1q11y7JS0DBIup5FqtpBwOY3Eq2aupltQSnHVyZTsWcusVkWqWaZtF6K0kg6nHtL707/Zc9LWWU/nNPnIrPmQzqaiZDmkqtA3fSKLor6j1oU1vGv4gsaaI7yR8QAZxfgKafTqH3luX/zkTTSuYhvu+8qiPXy/8Sg/j+xAs2ohPPD1JtYfOs/Wl7tSMcBU5BiEEN4hNR8ekpl4AHSoXcFxo9UC5w7aHkvNh/Cyyf2aULOiPxX8r8+y+9aADhgHzeEbw/0ADNH/ySzjW1Qk0W1xfLTioP3x9xuPAvDxtbL1h84D8Pvu0247vxDCfST58IJXsi/6lTnSRe8DodW9EZIQdve3ieavZztRNczPXta7WRTVKgQw9KUvSLhjhr0fyK+ml+hXKZ64ybdTLyLQ4Tgf3d+8WHEoJ8sR5NinWGcQQniLJB9eYNRne9szO5vKSBdRkuRy8U+r1YO+6ROItUZRWXOByUkvwD8zMWdbPiDDyUKKLji9EKIMkOTDC4zZh9pKfw9RAuV27ddqNNf6gUxgmaUVRszw80ievPo5hizrwjhby6i455d8RIiyQZIPL9BkH2p7NnNNF+nvIUqO3GoeMj++yfjxqPlpZvs9AMBdGb8zy/gm4VwCsi2aWATWgjS7SDYiRKkkyYcHbDx8Pu8dMicYk5oPUYKoXOoZss5To9AyL2AgDJhLMn600R7gF9PLNNfEkmEpXs3HqgMJ/LzjJF+svj63yF/7z/LO0v3250t25d7h9NSlq6w9mFCsGIQQ7iHJh5udS07j/i835r6DJSPLmi5S8yFKjrrZOpBm8jE49kuqHxkI9XryRtSn9n4gc40TaHlhidPXF8b//bCDSb/vdyj7bNX1ZGRz3AVizyY7fe2Nk//iwa83SwIiRAkkyYebnbp01eF5z0aRjjtcPAKWdDD4QUiMByMTIm/j72jIkBur8+uomxzKg30NvH5nI/q3rMqQG6sztpetxm7MgNuZ2eQbtvreiEmTQdNtL/FV2GyHfiDusD8+78XuMoflCiFKDplkzM00OPbveKJTLccdHEa6SC4oSo4QPyOv3dnI6bbBN1bPUVYp0IfX7mkP1iWw9j1Y+SbdrixmtvE/RqQ/RQIhOV4TN/l2ftp2gmfn7SxynNZ8+n1Y8ttBCOFxcrVzs+x9S3PMbir9PURZo9XCLc/BwLlYjYHcoP2PX00v0UJz0OnuBZnPIy/5vV6SDyFKHkk+PEyvyz7S5VrNh/T3EGVN3R6cG7iU/6xViNRc5AfjRAboVuDpAbOSfAhR8kjy4WY5aj6yF8iCcqIMSw+uyV3pE/jdcgMmTQaTDF8zRf8FJtLt+xQ3NchvSG5x5xsRQrie9Plwo4TLafT7bL1DmUOzi9UC52Ntj8PrejAyITxDKUjBlxHm/+Mx62Ke08/lHv0aGmmP8rj5KZec4+m5O5m75TjdGkYS5KPnuZ920aZ6mH37rE3HuJpuRaEY2Caa1te2bYm7wJJdp3muRz38Tde/ChOvmvlg2X8E+ehJzbDyQs/6zheDFEIUWaFrPtasWUPv3r2JiopCo9GwaNEih+1KKcaPH0/lypXx9fWla9euHDzovK23rHt23k7SMhz/6wr1u75YF5eOgSUNdEYZ6SLKpBA/A2CbD2R3jYd5wPwi51QQDbVHWWx8CQ4sdcl5Nh6+wMTFe3nup12AbQhuJqVg/vYTLNh+krs/32Avv+fzDcxYH8cnf8U6HOvtpfuZsT6Oj/+K5cs1h1mw/YRLYhRCXFfo5CMlJYVmzZoxdepUp9vfeecdPv74Yz7//HM2bdqEv78/PXr0IDU1tdjBljb/nnJc8bN3syhCs6wUaq/1qFBb1nQRZVKgj4H5T9zI8z3r8cWDrXnhiUdZcMNsEis0J0hzBebcR+P9H6PlepLer2UVj8Z49HyKw/PYM47zhpy6VP6+u4Rwt0I3u/Tq1YtevXo53aaU4sMPP+Tll1+mT58+AHz33XdERESwaNEi7r///uJFW8pkb4puUz3UsSBzcrGKdTwTkBBe0ComlFYxts9+82ohNK92M2Qsgz9fhs1f0DD2S741rOf/zKO4QBC1wgM8Gp8+21pL2btlCSFcz6UdTo8cOUJ8fDxdu3a1lwUHB9O2bVs2bNjg9DVpaWkkJSU53MqK7N3gdNnn8bAnH9LfQ5QzeiPc9g70+x8ZOl9u1u3hV9NLNNPEYvXw6BRDtv4c2ft3SDIihOu5NPmIj48HICIiwqE8IiLCvi27SZMmERwcbL9Vq1bNlSF5VfZe+NkXs+Xctb4wFaTmQ5RTTe9h2Y2zOGStTBXNeeYZX6fRqZ/w5HDc7MPftZJtCOF2Xh9qO27cOBITE+2348ePezskl8ne7JLjS02aXYTgUmAd+qRPZKnlBowaC50PTeY9wzR8SPPI+bPXSEruIYT7uXSobWSkbd2SM2fOULlyZXv5mTNnaN68udPXmEwmTCaTK8MoEf74N57Eq2aHMof/sK5ehJRrC15J8iHKuWT8eNz8FI9aFzPWMJf+ur9pqDnK4+anOaoi8z9AIVQf67jg3ZzNx5iz+Viu+7+/7D8CTHpmrI9jyt1NaVuzgkvjEaI8cmnNR40aNYiMjGTFihX2sqSkJDZt2kT79u1deaoS77Hvt+Uo61wvS3PUuWsjXQKjwOR89VAhyhcNR+o9wvHeP5CggmigPc6vxpfopt3q7cCYsHgvxy5c4b68VqgWQhRYoWs+kpOTiY29Pi7+yJEj7Nixg7CwMKKjo3nqqad44403qFOnDjVq1OCVV14hKiqKvn37ujLuUin42pwHgDS5CHFN1ubJLx9shUajITl6HeaFQwk6tYWvjO+jOjxNUvsXMBqNrDmY4DS5F0KUHoVOPrZu3cqtt95qfz5mzBgABg8ezIwZM3j++edJSUnh0Ucf5dKlS9x0000sXboUHx8f10VdFshIFyEAUFk6l2qudbgICI+GYb/Dn6/Apmlo1n1A8Klt0P8bx4n6hBClUqGTj06dOuW5iqRGo2HChAlMmDChWIGVeZkjXST5EOVcrl8nOgP0mgxVW8Mvo+HIGviiI8G3fOrR+IQQruf10S7llr3mo7Z34xCipGtyNwz/yzYk/fIp6vx2Hw/p/sDTq+MKIVxHkg9vsJjh4hHbY6n5EOVcgVKISvVtCUjDPmitZiYYvuVDw1R88fzU51fTLfbHiVfMbI27QNy5FCxOJkdTShF3LiXP2mIhyiNJPrzhYhxYM8DgbxvtIkQ5FmAq4LpGPkFwz7dcvOlVMpSWvrr1LDS+Sg3NafcGmE3HKSvtj5tN+JO7P99Ap3dX8ey8nTn2nbb6EJ3eXcWExXs9GaIQJZ4kH27gbHrooR1qXH+Stckl+5TrQpQzdzSNokejCF65o2H+O2s0hHYdw/TaH3NRG0Z97XF+Mb5MD+1m9wd6TcJl55OfLfznZI6yd5YeAGD6ujh3hiREqSNXPjewOKliHdAmy7TxMtJFCDuDTssXD7Zm2E018t/5muEPPkjo0xsguj2Bmqt8YfyQl/Qz0ZMBwP6JPfl6cGt3hQw4/ydDCFEwkny4gbO2X5M+S9WyjHQRovgCI2Hwr9B+FADD9b8x1ziRypxHq9G4fY0WZ/9kCCEKRpIPN3CWfBj1Wd7qzJqPCjLSRYhi0Rmgx5vE9/ofScqPVtqDLDGNQ3doOVqtm5MPqfkQosgk+XCDjLySD6Wk5kMIF0uvfTu3p7/Jbmt1wjTJ6ObcQ42d76HDkv+Li0iSDyGKzqULywmbhMs5h/+ZMpOPlHOQegnQQIVaHo1LiLLsuIrg7vTXeFk/kwf1y4n+dxozDasZbR5JAqEuPVf2xekyPfLtVqxKkZyaQZ2IAIdt32+Io3X1MDYfuUDPxpFEBF2f9dliVczdcpzW1UOpGyFrPYmyT6NK2AD0pKQkgoODSUxMJCgoyNvhFMlNb//FiYtXHcpi3+yFXqeFuHUw4zYIiYGndnkpQiHKlosp6bSYuMz+PG7QVSw/j0aXkUKCCma0eRQbrI28GKGjamG+rH2+s/35j1uP8/xPtu+DuMm3eyssIYqlMNdvaXZxg+yJR78WVWyJB8hIFyHcINTfyGeDWnJnsyimP3wDNLkb7WOruBhQm3BNIrOMk/giegUarN4OFYDjFxy/I3aduOSdQITwEkk+PKB7o8jrT6S/hxBucVuTynw8oAW31qsEgCa8LqGj10LzB9BipcfZr/nOMJlwLno5UiGEJB8eoMva617WdBHCc4x+0Hcq9JkKBj9u1u1hqWkst2r/8XZkDjS4d2SOECWNJB8e4PC1cl5qPoTwuBYPwKOr2WuNoYLmMtONUxiv/w4jZm9HJkS5JMmHJ5lT4eJR22NJPoTwrPC63JX+Ot9k9ARgqH4pC43jqaXJOS26EMK9JPlwoa7vr851CB4AFw4BCnyCwT/cY3EJIWzSMDIh4yGGpj/LeRVII+1RfjW+zL26lRRwfV2XqT52CU/98A/HL1zh+41H7eXnknOuHfPPsYsMnbGF2LPJngxRCLeR5MNFTidezfWLoWa4v+1B1pEubp76WQiRU1SwbW6N1t0H0CttMn9bGuGnSeMdw1d8aviEIFI8Gs+iHad4eu4Oh7IfNh/Lsd9dn63nr/1nGf7dVg9FJoR7ySRjLpLbbIfLx9xCzfBrkw3JSBchvGrZmFs4k5RKzfAAujeMANWbq3u/wmftJO5gI92DT5By+1SWXq6JUvDiwt1uj+nkJcdhtxdScu+HcvzCFXeHI4RHSM2Hi+i1zt/K2pWyzHKYmXzImi5CeIW/SW//Z6B2pUBqRwTje+uzaIb+ASExGJNPEDq3LwMSv2ZgqwjublXV7TFlXwDPYs19LhKpMBVlhSQfniQTjAlRMlVtDY//bRsVg4J1H8JXXYhMPez2U1uzTTItq+WK8kCSDxfJ/gWSgywoJ0TJ5hNkmw/kvpngVwHO7Oapw8MZplvi1plRszfZ5rVgncwHIsoKST5cJN8VLpNOgTkFtHoIq+GZoIQQhdegNzyxAer0QK/MvGKYxSzDW0Rxzi2nS0p17OORkmbBbLHab6nm6yvzZv0nJ+s+WcsKymyxUsKW9hLliHQ4dZHsPdZzyGxyCa0BOoPb4xFCFENgBAycy/yv3qDXyU+4UbeXpdqxvGIews/WDuDCGohUs2PC8MvOU/yy85TTfTOsigyLlfeW/ce0VYfs5S/d1oAqob6Mmr2dD+9vwZ3NovI8Z3JaBje//RctokP5ZsgNxf8hhCgkqflwka1Hc64X8fgtta4/kSYXIUoXjYbNYX3olT6J7dbaBGmu8JHxMz41fEIwtmH1Yf5GXu3dkBbRIR4L6/jFqw6JB8Cbv+1jxKztWBWMnpP/1PF/7T/LxStm/tp/1l1hCpEnqflwo7G96l9/Yp9WXUa6CFGaHFWR3JP+Kod67YdVk7lDt5E22v3MCh/D06P+D4CHOzg2peY52WAx5dvEWwA6GTYjvExqPjxFRroIUepkXqMt6OCW5+GR5cRao6ikucTT58bDgsfgqmdXyXVFPw2t5B7CyyT58BRpdhGi9KvSktvT3+LzjDuwooVdP8DUdnBgqcdCcMVQXI3UfAgvk+TDE9IuQ9K1xatkgjEhSg1n1+g0jEzOGMiLoVOgQh1Ijoc598HCxz1SC5KeUfxhv7osVR8y4kV4g/T5cIF8F3s6H2u79w8HvzD3BySEcLt/tfXh8bWw8k1Y/ynsnAOHV0Hvj9x63rd+25fvPv8cu0iASY9ep+XTv2LpVC8cnVaDv0mPQZt9RlWFXne97HBCMmaLIshXz9mkNJpVC3H1jyCEJB/FpZSi6/ur895JmlyEKJWqhPjmuq16RX8w+EL3N6DBnbDoCds/GrPv5V1DRyaYHyQJf5fHtPHwhXz3ueuz9Q7P528/4fD85joV7Y8zrAq9zvbYalV0fs/x++zPpztSNyKwiNEK4Zw0uxST2VKAKktZ00WIUumRm2sysG000x++PhfGghE3cl/rarzWu+H1Hau1sU3P3n4UoOFu3Rr+ND1PF+02AHo2imTmsLYejj53aw9enzAt68RkGU5G0uw4fskTIYlyRmo+iiktw5L/TjLSRYhSyceg4627mjiUtYwOpWV0aM6dDb7Q401bLcjPI4g8H8vXxvdYbGnHHXd9DwEVGd2lDh+vOOih6AsmI8s/UPkuEyGEi0jNRzEVqPOXNLsIUX5Et4XH/2ZaRm8ylJY7dBvh0xvgn5moPFas9RazNe+aDyHcQZKPYkrPby0Fq+V6h9OKddwfkBDC+wy+vJ0xgD7pb7DbWh1SL8HPI7l77yiiNWe8HZ2DrDUfFmfNyJKPCDeQ5KOY0sz5JB+XjoElDXQmCIn2TFBCiBLhX1WdvukTodtE0PsSk7iFP4wv8KjuV3QUoMnWA7ImHxklsGZGlE3S56MYTl66Sqd3V+W9U9bOplqd22MSQpQsFnTQYTQ0uIO4GcOpnrSVFw1z6K3bwFjzo/yrqns1vo5TVgLwdv8mfLAsZ3+UH7Yc471lB6gc7MuO45eYNqglxy9eITrMj56NK3M2KZXPVh3itiaVaVPD9VMJLPrnJEmpZh5qX93lxxbeIzUfxdBh8l+5bqtewc/2QNZ0EUIAhNXkUM9ZPGd+lEvKnybaOH42vsxY/Wx8SfV2dLwwfzfxSTnj2H7sEmeS0uyjXp6YtZ23ftvP4zO3A/DRioPMWB/HI99ucUtcT83dwfif/+X4hStuOb7wDkk+XKxVTCgd64azePTNtgIZ6SJEubTq2U4MaBPN2udvtZd1bhBBqz5PsujGhaw13oxeY+Vx/WKWm56ju3YLPz7ajtGda3P/DdUI9TN4MfqC23MqCYCk1Ay3nueym48vPEuaXVzs8wdaER5oul6QkJl81PNOQEIIr6he0Z9J/RyH6Wo0Gu5vEw1E86XvR0xfOpvX9d9STZvAl8YPMK/7lzZ3vAuh9Zjcv6lbV8d1FXeuEiNTv5ddUvPhYjlWi7TXfMhIFyHEdRo0/GVtSbf0d5iacSfpSofh0J8wtS2sfQ8y0r0dYoG4c4VcGflbdkny4WIOq0VeuQBXrs0kKLObCiGyyPyqSMXElIz76ZU+GUv0TZBxFVZMgM9vop12r3eDLAB3rpArk56VXZJ8uJhDNWHmSJegqmAK8E5AQogSSZetyuCQqkL6oJ/hri9ti1CeO8APxjd43/AZFUn0UpR5s1qVW5tdJPkouyT5KIJ/TyXm2hbr8KciTS5CiFw4u2hrtBpodh+M2gKth2FVGvrp/maF6RkG6/4oMXODZLrp7b/YevSi/Xn1sUuoPnYJHd9ZyR//xgMwfd0Re3mHyX9xKCGZo+dT6PnhGn7ecZKF/5yg54drOHo+JcfxneUexy9coddHa/lp24mcG0WpIclHETz2/bZct4X4ZumhLiNdhBC50Gap+dBpNQSY9Bh1176SfUPhjvdZ3mEWu63VCdZc4XXDtywxvkh77b+5HvPuVlXdHbaDU4nOhwgfu3CFF+bvAuD1X683HZ28dJVn5+3k5UV72B9/mf/7YQdPz93J/vjLvLRwT47jOKv5eGPJXvadTuLZeTtd9FMIb5DRLkWQdNWcoyzApGfry13R67Lkc/Y1XaTmQwjhKGtfiT2v9UCrdUxIALp3v53EDl24uvM7TGveon7qceYY3ySj/p3csqMLJwmnX4sqjO/dkOS0DKqG+jG+d0MuJKfnPwEitqTH4qZenZeu5PyeBEhJy3DakTQlPedQWmf7XUkvWbU/omik5sNFwvyN+BiyzWCaWfMRLsNshRCOsqYZvkYdJr3zGZCD/X3wvfFRtKO3ww3DQaNFv/8XVpie5f908wk1WgjxM1I11DaxYZCPgeoV/QsUQ51Knu+LpkHjtD3FWTOUs5oPd3ZwFZ4jyYeLqOyrL2WkwcU422NpdhFCZKMt7EXULwxufxceWwsxN+GjMfO0YT6j9g6EvT877yDh6hhcoDCndPYjuXNor/AcST5cJMcfyYXDoCxgCoKACK/EJIQouXRF/faNbAxDFjMyfTQnVQVCzfHw40Pw3Z1wpnBDc/U6byQfGqcZiLMaDWeTjOmk5qNMkOTDRXL8jWQd6SJ/LEKIbDTFGaSq0bDE2o6uaVNYUWmwbdXsI2vg8w7w61OQfLZAh8k+3NfV9l6bej2rCylpJDhZQ0YDXEhJJy3jep+OU5cc9zuTlJprs4vFqki4nFa8gIXHSPLhIicvXXUskJEuQog8+BqLv8r1VXxYH/04jNoMDXqDssK26fBxS0bofsZE3rOkursW4baP1+YoO5OU5nSUTHxSKi0nLqPzu6sB+Hz1IYfXz958lLZvrWD5vjNOzzXwq43c8OZydl5bAE+UbJJ8uIuMdBFC5KFn40g61QvnmW5F+wfl7f5NaFMjjFG31obQ6nDfTHj4d4hqAemXed4wl7/9nmd5twRaR4c4PYZOq6F/S88Oz83NiYu2f+Ay/5Gb/Pt+h+0zNx7L8/WbjlwA4Ictx90QnXA1ST7cRWo+hBB5MOi0zHi4DU92Kdo/KPfdEM2Pj7Un1N94vTDmRnjkL9ssqUFVCLeepfba/+MnwyvEPh6a4xh6nYb37m1G3OTbebV3w6L+KCWKtHKXDpJ8FEG+fcqVylLzIcNshRAepNVemyV1K3R+GQz+cHIb+hm9mGr4kGqa680WWUe76IvcA1aIwpNPmztcPg3pyaDVQ1gNb0cjhCiPjH7Q8TkY/Q+0HAwaLbfrNrPc+Bwv6mcRRDL6LB1ODWVkDGvZ+CnKPkk+iiDfD3dmk0toDdAZ8t5XCCHcKTAC7vwYHv+bNZYmmDQZPKpfwlrTU9yWNA/Mtj4WUvMhPEk+bYUQdy6F/609TFJqzmmAHSRIfw8hRAkT0YiHzGMZkv48B6xVCdZc4Z6LX8InrWD79xhK0KJ1++NzDtF1Zt9p237HL1yxl83bdoKzl22jaeLOpbBg+wmsTuZpX7zrFAfiL9ufbzt6gRd+2lXgc4vikeSjEDq9u4o3luzLf0dZzVYIUSJpWGVtTq/0yTxrfozLpghIOgm/jKL72v50026lAL3a3K7nhzmH6DrT6yPbfje/s9Jelp5h5e5pGwDbd/aYH3fmWAF3few5Rs3+hx4frrGX9Z+2gblbjxf43KJ4XJ58vPbaa2g0Godb/fr1XX2aEiPQR8+YbnX58+mO1wtlpIsQogSaPbwtL9/egF+e7Ej1LsMxPv0PdH8DfEPxvXSQr4zvszlyCuObJvJAu2iH197dqiqju9Tx+Mq5RXEsS00IwMbD5x2e7z6Z6PDcWc2IcC+3rGrbqFEjli9ffv0k+rK7eO4TnWoxolNtx0L7SBdJPoQQJceNtSpyY62KADSuEnyt8Elo8SCs+wg2TqPSpR0MvfQE1O3FJs2tHFS2ZOPde5rZjzO6cx06TlmZ4/gllTlbcpE91bAUYV0cUTxuyQr0ej2RkZHuOHSJk2NhprTLcPmU7bE0uwghSgPfEOj6KrR5FFZPhu3fw3+/s9S4lPmWjnyY0d9hd6O+dLXYZ1isDs+zr5ZrkZoPj3PLJ+jgwYNERUVRs2ZNBg0axLFjec9MV5rlGJ2WWesREGH7gxZCiNIiqDL0/ghGboIGd6LTKO7Vr2alaQwseRaSTgNgKmXJh9mSd3IhyYfnufwT1LZtW2bMmMHSpUuZNm0aR44c4eabb+by5ctO909LSyMpKcnhVprkqPnI7O9RQWo9hBClVMU6cN/39E2bwDpLI0yaDNjyFXzcHP54CWP6BW9HWCgZVseaj+ytLBmSfHicy5tdevXqZX/ctGlT2rZtS0xMDD/++CPDhg3Lsf+kSZN4/fXXXR2Gy1264nyBphxNhWevjYapVHY72QohyocdqjaDzC/R3vIvc2oth+ObYMOn+G2dzjP6bnyVcRtJBHg1xupjl+RbvupAgv15mxphbD5yPXl65NutdGtYKcfr98cnccfHf5NhVbSvWYFne9SlVUxYrnHsPH6JL9ccZmyv+lQL87OX/7zjJGv+O8ekfk1KXXOVO7n9nQgJCaFu3brExsY63T5u3DgSExPtt+PHS+aiQO/+ecBpeY4VFhOuLYYULsmHEKJ0e6h9DAB12t4GQ/+AQfOhcnM05hSe1C/ib9NTPKlbQABX8jlSyZE18QDbd/gL83fn2O/uaRvsNSIbDp/nuXm78jxun6nrWLL7NKNmb3co/78fdjB/+wl+3Foyr23e4vbkIzk5mUOHDlG5cmWn200mE0FBQQ63kig+Mc1peY4Jx+w1Hw3cHJEQQrjX+DsasmDEjbxyR0Pbim11usKjq+C+WZgr1CdIc4VnDD+xM+R5RhqX4IPz78nc3NHU+XWhJEhOc/xuP3wupUCvizvvPBG7kOK89ry8cnny8eyzz7J69Wri4uJYv349d911FzqdjgEDBrj6VB5l0DmfVN2hND0FLl3rXCs1H0KIUk6v09IyOhRD1qnXNRpocAeGkRug/9dQoTa61As8p53FWtNTDNX9TpDeXKDjt6tZwU2Re09uq+rKmjOOXJ58nDhxggEDBlCvXj3uvfdeKlSowMaNGwkPD3f1qTwqt3UPtFmLz/0HKPCrCP4VPRKXEEJ4hVYLTe6GEZug7zTO6iII1yQy3vA9f+lGM1y3GF9S8zyErowsZpdV2fuJ3MPlHU5/+OEHVx+yRNDn8kfiMNrl7LX+HtLkIoQoL3R6aD6QMZuqUe3YQkbofqGaNoGXDLN5XP8r/8u4ne8s3UjBN+dLc6smKMU0ZfBncgfpepuL7NPt5vZ5ckg+Eq7195AmFyFEOWPRGJhj6cKt6e8xzvI4cdYIKmgu84LhB/42/R8jdYsIzNYxVVtCaz5ym/fDalUopbBar98yyzNpsuybVealIvP1WffJWubsnFnPXVaU3XnPi2HErG3sj7/M7/93Mya9jlUHzrJg+0mn+zpUGyZcGxETXs8DUQohRMmTgZ6fNbfyY3oH+mjXMUq/iJraeJ4z/Mij+sV8k9GL6ZYeJBGQc5LGEqLWi785La/54m9UC/Pl+IWr9rJejSP5O/ac/fn5lHRSzRZ6fbSWI046qQ6ZvoUzSam8fHtDnpi1jYl9GvPzjpOcTkxl8ZM3OTTxv7lkLwv/OcWvT3Zg8DebqRbqx9dDbnDhT+o9UvPhxG+74zmckMKGQ7bFiD5acTDXfd+8q/H1JzLSRQhRTk3o04hQPwMv3daArwffgL+PiQXWjnRNf5fR6SOJtUYRrLnC04b5/G36P94M/pkW4db8D5xNdJY5NLwha+IB8PueeC5nG/X498FzORKPzOaY1f8lsD/+Mg98vYnLqRk8NXcHKw/Yyv495TjJ5ldrj3AuOY2Rs7bz35lkVuw/64afyDsk+chDZq1GcvbhtMCRSbdx+K3bqB95bWhwegpcOmp7HC7JhxCifKkTEcj2V7oxvGNN2teqwM5XuwNgRcsv1g7UHL8b7p6OqtSQIM1VBqXNJea7trykn0kk59k5vjuxb/YixM+Q6zkCffSsef5Wjky6zVM/VpFoc7my5tdsklsH3LLT2HKdJB95yOwM5ewXr9FoHNsrM5tc/MPBv+wNHxNCiPxk7WyZveOlVq+Hxv3QPL4O7v0eIpqgNV9huP431piewu+Pp9BfPJxzyYosMjv+l/ROnZpcxrwUdRb3MtTVw06Sj2yydjQqVGcomdlUCCHyp9VCwzvh8bWcvuN7NlnrY9RYMOycCZ+25m3LuzTWHHb60lIzNDeXMLOvpptdbolXGcw9pMNpduYsSy9nftAL9HGX5EMIIQpOoyElujP3petoqfmPeY03oju4lG5spJtpI2ssTZhmuZMN1oZkfguX9BqPTLlFmd/qubk112SllCo170NeymXNx/ELVziWyxS4Z5KuT4qTnJrBkl2nOXg2Of+D2uf4kORDCCEKY7uqi/X+OfDEBpZoOpKhtHTU7WaO8U0WGcfTQ7sFDdZSMy/I+eScU6n/vuc0245ezPN1O45dItVsIfZsMvGJ169FO49fsj/OrfIkr+taSVTuaj7MFis3v7MSgP0Te+Jj0Dlsv/vzDfbHT8zaRqq5gL2x7XN8SGdTIYQACPY1kHjVTOVgH6fbfQzX///VaTQQ0ZBXtKOZlNqf4brF3KdbRXPtIb4wfkCsNYq/fO8FcwcwOD9eSfHMvJ05yvacTGLQ/zbl+bqxC3Yzc9NR9pxMynUfZ7lH1uvavgk98TXqnOxVspS7mo8raRb740tXcq4/kHD5+sJIuSUes4e3dSxIS5Y1XYQQIpsfH2vPHU0r8/2wtk63Vw31Y+SttXihZ32HPnYnVDivZjzMlrvW8GeFB8kwBFJbe4pHEz+EDxvDqrf5eajz79oOtUt3h/+8Eg9w3m/E4bp2tXQsYFfuko/ierBdDDfWyrZuy9m9tvuASBnpIoQQ19SLDOTTgS2pXSkg132e61GfJzrVcrrt5uYN6f7kp+if2Qvd34TgapCSAKveotmPNxLXYRn/jq7p8JpZj7Rz6c9Q0jhLPlSW+pC8RguVJJJ8FJLTztZn9tjuIxs72SiEEKJYfILgxlEweodtJd2oFpCRCtum4/dle74yvEcbzT7K5rgQR876fGTtx1pKco/y1+dDuePDGX8t+Yho5PpjCyGEsNHpbSvpNu4PR9fD+k/Q/Pc73XTb6Kbbxk5rTdidig4jFkp+v4eicFbzkbVMaj5KqKJO8pLJ6cvP/Gu7j2hSvIMLIYTIn0YD1TvAwB9If2IzszK6kKoMNNMehvnDWG16mmG6JQSRc22V0s7ZNSzronSlZUKyclfzkXWcdbtJK/j8gVZ0qF2Br9YeYfeJS/m+Pscv1mrNknxIzYcQQniSLrwuL2UM472Me3hAt5wxwauoeuUcrxhmMUb/E/MtHfnW0p1Dqoq3Q3WJ7u+v5sXbG7Dx8HkOJ6RQOdiXzXHn7dtnbjzK093qArAl7gIfrzhI4yrBjOhUi/WHznMhJZ0BbaK9Fb5duUs+ss+t//jMbQxqG82sTccK9PrEq9lGyCQeg/TLoDNCxTquClMIIcqlno0jmb3pGHXy6KSaVWY/vAsE8bGlH2Oe/pQXXnuFh3VLqa89zkP6ZTykX8YaSxOmW3qyytoMla3S36jTkm5xHN3ob9SRkm6hpDmVmMqo2f/kuv2jFQcZeWttjHot91ybOmLtwXME+uh5Z6ltGZB2NStQo6K/R+LNTblLPixO6qR2ZJnAxRmN5nqNR9OqwY4bM/t7hNcDXe4LIgkhhMjfK7c3pEW1EG6tX6lA+2ed7XNcr/pg8GXwyPGsOzSCs1f/oeXpufgfWUZH3W466nZzNSCanVH3sSWkF7vPKV7oVZ/k1Az+O3OZepGBvDB/N32bRwEw6ff9bvkZ3S3dYsWod0ywDidcb4JKuJwmyYenOWsvy6+DzuG3bqPGuN8ACPUzOm7MHOki/T2EEKLYfI067mldrUivbRgVZL+3Pa4J9IeLcbDlf7D9O3yTj9Huvym0M06D5gNB8yhUq0OzaiEA/P5/NwPw/Ya4PM/Vr0UVFvxzskhxult6hhVMjmVZZ4fNsBZw8kw3Kn8dTp1kH/mNgMmaWedY2EiG2QohRImQa2fL0OrQ/Q0Ysw/u+MA2GWR6Mmz+Ej5tDTP7w39/2vrwXZPfwqIleX2VtIyczUVZw82weL9Xajms+Sjem54j+ZBhtkIIUSLk++1u9IfWQ6HVw3BkNWz6Ag78DrHLbbeQGGj9MLR4EH0+yUdJXmA3PSPvmo2SUPNRDpOPnGWagq1bC+D4gUxLhotHbI8jpOZDCCG8KfuAglxpNFCzk+124YitSeaf7+HSUVj+Gqx8i3aR3WmlacU2VRdn69Tm+Ee0BMkv+TCXgJqPctfs4mxJ490nEwv8eoeqOIdp1Ss6f4EQQgiPKNIlNawG9HgTxuyHPlMhqiVY0ok5uZj5ptf53TiWB3TL8Oeqw8vya5bxpm4frKH62CUOZT9sOW5//Nj321ix74ynw3JQ7pKPAmfG17SIDgEgPNDWe+eG6mHXN56+tnKh9PcQQgivCfGzjTRsca3TaJEY/aDFA/DoShi+kquNB3BVGWmgPc4bhulsMo1kduUfqaexTcug02iY0Kf0NrcP+3arV89f7ppdnA21zU14oIkFT9wIwNrnbyXVbCEk62iX0zts91EtXBihEEKIwtg4rgtpZivBfi6a7qBKS3zv/pxLt07AcGAeum3TCTh/kBsvLuIP0yK2WOsSd+F+7rljFF0aRNBh8l854rmcaiYqxJdGr/7hmpjKmHJX81GYfjZNqwTbezT7GHSOiQfAqR22+8rNXRKbEEKIwvMx6FyXeGQRUqES+htHohm1BR76hfiqPTArHTdo/+OeYxPgvfpEbZxILY3jkNvIYB/qRATib7r+/32Aqdz9r5+ncvduFGa0S55DqdKvwNl9tsdS8yGEEGWXRgM1b2HHlXqMj13O/bqVDPNbTfDVBDQbp7LCBJut9fgh41aWWNs5PYRBV3L7iHhD+av5KETykWd/ojN7QFnAvxIERRU/MCGEECWaUoqzhPKxpR/v1J8HA36Aur2wKA1ttAd43/g5W0wjYMmzEL/b4bU6bbm73Oap3L0bhVnVNs85ZDKbXKJa5LOjEEKIsiDr5cOq0UG9XjDwB25M+4R3zfdw3BpOkOYKbPkKPr8JvryV+3Qr8SM133lDyptyl3zMzTLcKD/+ebXRnbq2sE9U8+IFJIQQolQw6K5fMn0MOvvjM4TxqeUuOqZ/wIPpY6FhH9Dq4dR23jZ8xWbTCMbzBU01hyjigOAyp9z1+chv8pVMjasEMbZn/dx3sCcf0t9DCCHKg071wu2Pn+x8fRXzh9rHsOpAAn5GHQO7DIEmlSE5AXbOJmXDNwQkx3Fb+h/cZvqDvdYY5lhu5WdLB5LwZ/wdDdFpNXy7IY7hN9dk3ILdTs7sekE+3r38a1RhJ75ws6SkJIKDg0lMTCQoKMjlx3/qh39YtOMUL93WgOEdawLYJ2Pp3SyKTwYUIJlIS4bJ1UBZbRPTBFV2eZxCCCHKAKXg6DrY9i3s/RksabZyvS806guthkC1tvbm+8zr0Y21KjCuVwN6f/q3/VCVg33YMK6L/fkri/bw/cajRQqrVUwo869NJeEqhbl+l7uaj4xrnT70TnoeF7hNLn63LfEIiJTEQwghRO40Gqh+k+3W623Y9SNs/9Y2Q/bOObZbeH1oORia3W9/mVI5r1PZn2cUphNjNsV5rSuUuz4fmav5OUs0CjxX//FNtvuqrV0VlhBCiLLOLwzaPQ5PrIdhy6D5A2Dwg4T98Mc4eK8+Hxo+pa1mH0pZcwzPNWQbMZNhKfoCcRYvLy5Xjms+cuZduoKOWjm+2XZfra2rwhJCCFFeaDRQrY3t1vMt2D0Pts2A+N301a2nr249p85WwXfnUMKowgVsTRiGbNet4tReFCNvcYlyVfOx91QSy68tpuOslkNXkElglLpe8yHJhxBCiOLwCYYbHoHH1sLwlczO6Eyy8iHKcpLQdRPZaBrJp4aP6aDdjVHnmGyYS3HNR7lKPu76bJ39sbNmlzqVAvI/yIXDcOUc6EwyzFYIIYRraDRQpSUvZjxCm7TP+LnaC2RUboFRY+EO3UZmGScxI/lxWPseXLb9E127INesXHi7z0e5anZJyzLMNmuzy4+PtWfNfwk80C4m/4Mc22i7j2oBepOrQxRCCFGOLX7yJpbsPk2XW/ugN73In8uXEbJ/Nk0v/kGF9FOwYgKsfAvq9mRE84cw31Kdbo2rkJKWweYjF/hoxUEAKvgbmflIW3p9tDbHOepFBDoMG/aGcpV8ZJW15qNNjTDa1Agr2AvtTS5t3BCVEEKI8qxxlWAaVwm2P+/etRt07QbpKfDvIttImeObYP9ijPsX81xwNfB7CFo+RIfade3Jx7jbGtCgchC3NYnkt93xAMRNvt0bP5JT5abZJft0JkWe6jYz+Yh2vniQEEII4XJGf2gxCIb9CSM2QtsnwCcEEo/Dyjfhg8Yw/xGaa2IByLzC6UvomjIlMyo3sGRr33I2z0e+Us7bhkSBdDYVQgjhHZUaQK/J8Mx+6PeV7XpkNcPueSwyjWeR8RWiT/wKGWlFu9Z5QLlJPrJ3rinSCoNHVtvuKzUC/4ouiEoIIYQoIoMvNL3XVhvy6CpoNpA0pae59hA3/DMWPmhMr4QZhHPR25HmUG6SD2u2ZhdDUZpdMpOPmre4ICIhhBDCRaJawF3TuDHtE6aY7+WqTyVIOUu3hOmsM43mbf2XkHDA21HalZvkI2fNRxGSj8PXko8aknwIIYQoec4TzFRLX04P2Qx3TyexYkuMGgv36VfB1DYwZyAc2+TtMMvPaBeLJXufj0LmXRePwsUjoNFB9Q4ujEwIIYRwjfVjO3M+OZ2akcEQ2Y/gxv3Yt3k5tf77GmPs73Bgie1WrR08MB9MRZ8rpDjKT/JR3NEumU0uVVuDKdBFUQkhhBCuExXiS1SIr0NZgzZdoU1XSPgP1n8Mu+aCzuC1xAPKU/JR3GaXg8ts9zU7uSYgIYQQwpPC60KfT+HWlyA10auhlJvkI3ufj+wL9OTJnAqxK2yP6/Z0YVRCCCGEhwVVtt28qNx0OLUWp+Yj7m8wp0BgZajc3LWBCSGEEOVMuUk+ctZ8FCL5OPCb7b5uTyihs8UJIYQQpUW5uZJmXz64wDUfVsv15KPebS6OSgghhCh/yk3yUaNiAF0bVLI/L/B893Fr4fJp8AmWycWEEEIIFyg3yYdOqyHUz2h/XuD57nf9aLtvdBfoTW6ITAghhChfyk3yAZC110eB5vlIvwJ7f7E9bnq/W2ISQgghyptylXxkXd+lQDOc/rsQ0i9DSLSsYiuEEEK4SLlKPrJOcppvzYdSsOlz2+PWQ2WUixBCCOEi5eqKarZcH/GS72iXo+shfhfofaHlYDdHJoQQQpQf5Sr5MOqv/7h51nwoBasm2R43uw/8wtwcmRBCCFF+lKvko3FUsP2xRpNH8nF4pW2Irc4INz/rgciEEEKI8sNtycfUqVOpXr06Pj4+tG3bls2bN7vrVAVWoHnFzFdhybWEo/VQCKnm1piEEEKI8sYtycfcuXMZM2YMr776Ktu3b6dZs2b06NGDs2fPuuN0BVagWU2Xvw4XDkFAJHQa5/6ghBBCiHLGLcnH+++/z/Dhw3n44Ydp2LAhn3/+OX5+fnzzzTfuOF2BafNLPrZ8DZum2R73/hB8Q9wdkhBCCFHu6F19wPT0dLZt28a4cddrDbRaLV27dmXDhg059k9LSyMtLc3+PCkpydUh2SQncMO+t3lVfw4NCpasBJStc6myQmoi/LvAtm+ncVCvl3viEEIIIco5lycf586dw2KxEBER4VAeERHB/v37c+w/adIkXn/9dVeHkVPqJerGzaJu5k+8JZf9bhwNt7zg/niEEEKIcsrlyUdhjRs3jjFjxtifJyUlUa2aGzp5+obBzc9w4EwywX5GIoN8QaMBNNfvo1pA3e6uP7cQQggh7FyefFSsWBGdTseZM2ccys+cOUNkZGSO/U0mEyaTBxZs868AXcZTz/1nEkIIIUQeXN7h1Gg00qpVK1asWGEvs1qtrFixgvbt27v6dEIIIYQoZdzS7DJmzBgGDx5M69atadOmDR9++CEpKSk8/PDD7jidEEIIIUoRtyQf9913HwkJCYwfP574+HiaN2/O0qVLc3RCFUIIIUT5o1Eq61qv3peUlERwcDCJiYkEBQV5OxwhhBBCFEBhrt/lam0XIYQQQnifJB9CCCGE8ChJPoQQQgjhUZJ8CCGEEMKjJPkQQgghhEdJ8iGEEEIIj5LkQwghhBAeJcmHEEIIITxKkg8hhBBCeJRbplcvjswJV5OSkrwciRBCCCEKKvO6XZCJ00tc8nH58mUAqlWr5uVIhBBCCFFYly9fJjg4OM99StzaLlarlVOnThEYGIhGo3HpsZOSkqhWrRrHjx+XdWO8QN5/75PfgXfJ++9d8v67l1KKy5cvExUVhVabd6+OElfzodVqqVq1qlvPERQUJB88L5L33/vkd+Bd8v57l7z/7pNfjUcm6XAqhBBCCI+S5EMIIYQQHlWukg+TycSrr76KyWTydijlkrz/3ie/A++S99+75P0vOUpch1MhhBBClG3lquZDCCGEEN4nyYcQQgghPEqSDyGEEEJ4lCQfQgghhPCocpN8TJ06lerVq+Pj40Pbtm3ZvHmzt0MqN1577TU0Go3DrX79+t4Oq8xas2YNvXv3JioqCo1Gw6JFixy2K6UYP348lStXxtfXl65du3Lw4EHvBFtG5fc7GDJkSI6/iZ49e3on2DJm0qRJ3HDDDQQGBlKpUiX69u3LgQMHHPZJTU1l5MiRVKhQgYCAAPr378+ZM2e8FHH5VC6Sj7lz5zJmzBheffVVtm/fTrNmzejRowdnz571dmjlRqNGjTh9+rT99vfff3s7pDIrJSWFZs2aMXXqVKfb33nnHT7++GM+//xzNm3ahL+/Pz169CA1NdXDkZZd+f0OAHr27OnwNzFnzhwPRlh2rV69mpEjR7Jx40aWLVuG2Wyme/fupKSk2Pd5+umn+fXXX5k3bx6rV6/m1KlT9OvXz4tRl0OqHGjTpo0aOXKk/bnFYlFRUVFq0qRJXoyq/Hj11VdVs2bNvB1GuQSohQsX2p9brVYVGRmppkyZYi+7dOmSMplMas6cOV6IsOzL/jtQSqnBgwerPn36eCWe8ubs2bMKUKtXr1ZK2T7vBoNBzZs3z77Pvn37FKA2bNjgrTDLnTJf85Gens62bdvo2rWrvUyr1dK1a1c2bNjgxcjKl4MHDxIVFUXNmjUZNGgQx44d83ZI5dKRI0eIj493+HsIDg6mbdu28vfgYatWraJSpUrUq1ePJ554gvPnz3s7pDIpMTERgLCwMAC2bduG2Wx2+BuoX78+0dHR8jfgQWU++Th37hwWi4WIiAiH8oiICOLj470UVfnStm1bZsyYwdKlS5k2bRpHjhzh5ptv5vLly94OrdzJ/MzL34N39ezZk++++44VK1bw9ttvs3r1anr16oXFYvF2aGWK1WrlqaeeokOHDjRu3Biw/Q0YjUZCQkIc9pW/Ac8qcavairKnV69e9sdNmzalbdu2xMTE8OOPPzJs2DAvRiaEd9x///32x02aNKFp06bUqlWLVatW0aVLFy9GVraMHDmSPXv2SB+zEqjM13xUrFgRnU6XoyfzmTNniIyM9FJU5VtISAh169YlNjbW26GUO5mfefl7KFlq1qxJxYoV5W/ChUaNGsXixYtZuXIlVatWtZdHRkaSnp7OpUuXHPaXvwHPKvPJh9FopFWrVqxYscJeZrVaWbFiBe3bt/diZOVXcnIyhw4donLlyt4OpdypUaMGkZGRDn8PSUlJbNq0Sf4evOjEiROcP39e/iZcQCnFqFGjWLhwIX/99Rc1atRw2N6qVSsMBoPD38CBAwc4duyY/A14ULlodhkzZgyDBw+mdevWtGnThg8//JCUlBQefvhhb4dWLjz77LP07t2bmJgYTp06xauvvopOp2PAgAHeDq1MSk5OdvgP+siRI+zYsYOwsDCio6N56qmneOONN6hTpw41atTglVdeISoqir59+3ov6DImr99BWFgYr7/+Ov379ycyMpJDhw7x/PPPU7t2bXr06OHFqMuGkSNHMnv2bH7++WcCAwPt/TiCg4Px9fUlODiYYcOGMWbMGMLCwggKCuLJJ5+kffv2tGvXzsvRlyPeHm7jKZ988omKjo5WRqNRtWnTRm3cuNHbIZUb9913n6pcubIyGo2qSpUq6r777lOxsbHeDqvMWrlypQJy3AYPHqyUsg23feWVV1RERIQymUyqS5cu6sCBA94NuozJ63dw5coV1b17dxUeHq4MBoOKiYlRw4cPV/Hx8d4Ou0xw9r4Davr06fZ9rl69qkaMGKFCQ0OVn5+fuuuuu9Tp06e9F3Q5pFFKKc+nPEIIIYQor8p8nw8hhBBClCySfAghhBDCoyT5EEIIIYRHSfIhhBBCCI+S5EMIIYQQHiXJhxBCCCE8SpIPIYQQQniUJB9CCCGE8ChJPoQQQgjhUZJ8CCGEEMKjJPkQQgghhEdJ8iGEEEIIj/p/w7H+nIc/3N0AAAAASUVORK5CYII=",
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aPiwRERENQpoW4h46dAhXXHEFmpubUVJSgnnz5mHNmjUoKSnR8mGJiIhoENI0aFm2bJmWd09EREQnEe49RERERLrAoIWIiIh0gUELERER6QKDFiIiItIFBi1ERESkCwxaiIiISBcYtBAREZEuMGghIiIiXWDQQkRERLrAoIWIiIh0gUELERER6QKDFiIiItIFBi1ERESkCwxaiIiISBcYtBAREZEuMGghIiIiXWDQQkRERLrAoIWIiIh0gUELERER6QKDFiIiItIFBi1ERESkCwxaiIiISBcYtBAREZEuMGghIiIiXWDQQkRERLrAoIWIiIh0gUELERER6QKDFiIiItIFBi1ERESkCwxaiIiISBcYtBAREZEuMGghIiIiXWDQQkRERLrAoIWIiIh0IWVBywMPPABFUfDDH/4wVQ9JREREg0hKgpZ169bhiSeewJQpU1LxcERERDQIaR60dHR04KqrrsJTTz2FgoICrR+OiIiIBinNg5ZFixbhoosuwoIFC6Le1m63o62tLeCDiIiICABMWt75smXLsGHDBqxbty6m299///24++67tTwkIiIi0inNMi11dXX4wQ9+gOeffx4ZGRkxfc/ixYvR2tqqftTV1Wl1eERERKQzihBCaHHHr732Gi699FIYjUb1cy6XC4qiwGAwwG63B3wtlLa2NuTl5aG1tRU2m02LwyQiIqIk0+r8rdny0LnnnovNmzcHfO66667DuHHj8LOf/SxqwEJERETkT7OgJTc3F5MmTQr4XHZ2NoqKivp8noiIiCgaTsQlIiIiXdC0eyjYihUrUvlwRERENIgw00JERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdEHToOXxxx/HlClTYLPZYLPZMHv2bLz55ptaPiQRERENUpoGLUOHDsUDDzyAzz77DOvXr8c555yDSy65BFu3btXyYYmIiGgQUoQQIpUPWFhYiAcffBA33HBD1Nu2tbUhLy8Pra2tsNlsKTg6IiIi6i+tzt+mpN1TFC6XCy+//DI6Ozsxe/bskLex2+2w2+3q/9va2lJ1eERERJTmNC/E3bx5M3JycmC1WvHd734Xy5cvx4QJE0Le9v7770deXp76UVVVpfXhERERkU5ovjzkcDhQW1uL1tZWvPLKK3j66afx4YcfhgxcQmVaqqqquDxERESkI1otD6W8pmXBggUYOXIknnjiiai3ZU0LERGR/mh1/k75nBa32x2QTSEiIiKKhaaFuIsXL8aFF16I6upqtLe344UXXsCKFSvw9ttva/mwRERENAhpGrQcO3YM3/72t3H06FHk5eVhypQpePvtt3Heeedp+bBEREQ0CGkatDzzzDNa3j0RERGdRLj3EBEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBQYtREREpAsMWoiIiEgXGLQQERGRLjBoISIiIl1g0EJERES6wKCFiIiIdIFBCxEREekCgxYiIiLSBU2Dlvvvvx+nnXYacnNzUVpaioULF2Lnzp1aPiQRERENsNauXk3uV9Og5cMPP8SiRYuwZs0avPPOO+jt7cX555+Pzs5OLR+WiIjC6LA78fbWevT0ugb6UGgQ+/mrn2tyvyZN7tXrrbfeCvj/0qVLUVpais8++wxnnHGGlg9NREQh/HnFXvzvB3vwq69MwA3zRgz04dAgtamuRZP71TRoCdba2goAKCwsDPl1u90Ou92u/r+trS0lx0VEdLLY3+TJdO9t7BjgI6HBqrW7F+092mTyUlaI63a78cMf/hBz587FpEmTQt7m/vvvR15envpRVVWVqsMjIjopNHZ4Lgwb2+1RbkmUmEMnujS775QFLYsWLcKWLVuwbNmysLdZvHgxWltb1Y+6urpUHR4R0UmhyRu0HDuJg5Z/fX4EK3YeG+jDGLTqjndrdt8pWR669dZb8e9//xsfffQRhg4dGvZ2VqsVVqs1FYdERHRSkhmWxraeAT6SgXGsvQe3LduIDJMRm+86HyYjJ38km24zLUII3HrrrVi+fDnef/99jBjBoi8iooHS0+tCe48TgGeZSAgxwEeUevsaOyEE0N3rQv1JGrhpre64ToOWRYsW4a9//SteeOEF5Obmor6+HvX19eju1i51REREoTV3OtR/97oEWjSapZHOav1OqFouY5zM6k5o93vVNGh5/PHH0drairPOOgvl5eXqx0svvaTlwxIRUQhNQXUsJ2Ndi38WoE7DZYyBcKSlGx/taoTD6R7Q49ByeUjTmpaTMfVIRJSuZBGu1Nhux9iy3AE6moHhn2k5pOEyRir0utzYcPAEPtjZiBU7j2FHfTsA4PbzxuC2c0cPyDEJIfRfiEtERAMvOGg51n7y1XQELA9puIyhtc8OHscNz60PucT3n231Axa0NHc60N3rgqJoc/8smyYiOkk0dTgC/p+M5aGnP96Hc36/Akdb9REA1Db717ToN9Pyn60NaOnqRV6mGZdOq8SfvjUV//mRZ9L81iNtON7piHIP2pC/05IcbTqBGbQQEZ0kggfKHWvrX9ByrK0Hv3t7J/Y1duLDnY39uq9U6LA7A4qR9VzTIgPQ75xZgz9cPhWXTK3EmCG5GFeWCyGAVXuaBuS4ZPZqaEGmJvfPoIWI6CQhp+FW5mcG/D9RT3y0Ty361MOEXZkFsJg8p76GNrtuN45s7vT8vouzAzMa80YVAwBW7h6goMX7O5Z/Y8nGoIWI6CQhu4fGl9sAeDIlCd9Xhx3Prz2o/l8PnUiynmV8WS6yLEYAwOEWfSxrBWv2ZlqKciwBn5832hu07GkakGaYQ95MS2VBlib3z6CFiOgkIQtxJ1R4gpb+ZEee+ngfenp9rbWJFPX+Y9Nh/Oq1LXC6UtOiK7MA1UXZqPKeVPVa19LsfS6LgmpHZo0ogsVowOGWbnVzzFSS7c6V+Rma3D+DljTRaXfi+y9uxJubjw70oRDRICXrICaU9y9oOdHpwF9We7Isl00fmvB9/f4/u/CXNQfxcYrqLw56i3CrCzNRVehZvojUQbTnWIcaHKQTIQSavLU5RdmBmZZMixHThxUA8GRbUs23PMRMy6C2ak8T/vX5ETz+4d6BPhQiSnNHW7vx4799ji2HW2P+HofTjdZuT3vsRG+mpd3uRLcj/pqOZ1ftR5fDhYkVNlx+WhWAxJaHTnhPvBtrW+L+3kTI5aHqwiwM9WZaws1qOdLSjQv/9BGufubTlBybv2h1Nh12p1pLFLw8BPiWiD5OcV2Lyy3U5bbKAmZaBrU2734gJ7oGpk2NiPTjtY1H8PcNh/DMyv0xf48s3DQZFFTmZyLD7Hn7j3dZp7W7F0tXHQAAfP+cUSjN9ZycGtvj28vI5RZot3ve9zbWnojrGBIlswBVhVlqd0u4DqLPDp5Ar0tge31bSot11+xrxqQ738afI1zAynqWLIsRWZa+49bme4OWNXubU7b0BgANbT3odQmYDArK8liIO6h19HiugFpPwr1AiCg+8uKmIY5C2qZ2X+GmwaAEBBvxeO6TA2i3OzF2SC7On1CGUpunpsLudKsXX7Fo6/a9122qbYHbrW3RqMst1CLR6sIsVBV6My1hloe2HmkDAAjhW1ZKhfe2N8DpFhFblmUAGirLAgATK/KQn2VGu92Jzw+1aHGYIcmgsCI/E0aDNtPlGLSkiQ7vFUdbjxMujV+8RKRv8uImniWZxg5PgFPsLdwsybXGfR8ddieeXeXJ7iw6ZxQMBgUZZiNyMzxX+41xZG1a/YKWdrsTexs7Yv7eRDS09cDhcsNsVFCelxm1EHfb0Tb13/s0PjZ/2496RvFHmqEja5OKskMPcDMaFMwdmfolIhkAynohLTBoSRPtflco7T3MthBRePKEH0+WRGZaZNBSKoOWOLI1f11zEC1dvagpycZFk8vVzycSAPkHLYD2dS2ynmVoQRaMBkU9sZ7o6lUvGv1tO+IXtKSoC0cIoQZLDRECQLk8VBxh6qza+pzCoEUutVVp1O4MMGhJG+1+L5rgFzMRkT/5HtHa3RtzvYUcJBcctMQzYG7FzmMAgOvmjghI/6v31Z+gpU7buhY5vl8uC+VmmJGfZQbQN9tyrL0nYJ+mVLUOH2u3q+P3W7p6YXeGfm6b1ecy9PIQ4Bsyt7GuJWUXwnKjRPk71gKDljTR0cOghYhi4/8eEbwJYjjydjIromZH4hjlL9P/44N2hk6kPqbNeyKVG+ulKtNS7bd0EW6JaKtflgVIXdCyLehxwz03ciuCcDUtgCdwGF6UBZdbYM2+48k7yAhkpkWrEf4Ag5a00cFMCxHFyP89ItYlmSZ1ScFzopOBRqzf73S5cbTVs2QxNCj935/loVOG5gMAdja0h1ymSRb/dmcp3KwWGTyMLs0BkMKg5WhQ0BLm9ykD0HA1LZJviSg1+0Id8luC0wqDljThn2kJtdU4EZHk33kTa3ZDjvBXMy22+JZ0jrb2wOUWsBgN6nKQlEh9jAxaRpXmoDI/E0IAX9S1xPz98fIFLdnq58JlWmTw8GVv3c7xTgdaUjCOYntw0BLm9xluhH+weaNKACAlw/scTjeOeo+XhbgngTa/NUdmWogoHP/5JkA8mZbQNS2xfr9vT5lMGILaWUsSqI+R73N5mWZMq84H4Km/0EpdiEzLULXtOTBo2e7NtMwYXoDyPE9GKhXFuDJYkt1Y4Z4bdbPECIW4ADB7ZBEMCrCvsRNHNN5j6WhrN4QAMswGlEQ5rv5g0JImuDxERLFoC3p/iDnTEhS0yECjudMe0wCySPUK6lJTHPUxbX5By6nVnrHzGw5qU4zbYXeqdSBVATUt3uWh474Teqfdif3NngBlfLkNI4o9mZn9jdoGLV0Op7oMJYfDhZvDE2umJS/TjFOq8gFo30Ukf4dDC7KgKNrMaAEYtKQN/6Al+E2JiEgKvqiJZTZKr8uNE95lZ1nTUpRthUHxDE+TJ/RIZKYlVL2CHDCXjEyLFjsTy86hwmwLcjPM6udll0vdiS71cXfUt0EIYIjNiuIcqy9o0TjTsrO+HUJ4np+JFXkAQmdaXG6B412R57T4k/Na1u7XthjX1+6s3dIQwKAlLQgh2D1ERDEJfn+IJbshr8yNBgUFWRb13zLrEku2xldk2fekJJcDIrXpBvMPWiZU2GAxGnC806HWniRT7fHAdmepMt/zs3Q5XGqrsSzClYFDqoIWOVRufLlNXboLlWk50eWAEJ6uq4Isc5+vB5sx3JPFWn9Q46AlzO842Ri0pAG70w2n3xRcFuISUTh9Mi0xZDfk0lBhtiWgHsXX9RM9W+Obdtr3pJSfZYbZ6LnfWJer/IMWq8mIiZWeTRy1aH0OVc8CABlmoxogyA4iWVcid8KuKfEELVrXtGw72qo+7hBb+BZyGYAWZFlgMkY/hZ86rACK4tmKINFdvWMhf39aDpYDGLSkhbagwT/MtBBROPL9IdtiBBBbpkUGNsEFkqVxzGo5FKGmRVEU9b7jDVpsmZ6i02lVnoyAFpsnykzLsBABl7pE5L2NnNEywbsT9ohi2fbcoen+SDLTMqHCpi63hcq0NKvtzpHrWSRbhhljh3jm6nymYbYl0t9HMjFoSQMdQZuMMWghonD8W4UBTxYl2slUtjsX92lVjm0oXEA7a5gr6RJbfHNf2ro973t5mZ4lDi07iA6GybQAfsW4J7rgdLmxo94bPHgzLVUFmTAZFPT0ulEfR0t3PNxuobY7jy+3YYj3eTkRYrmtKYbBcsHkEtG6A9pNHU7FNFyAQUtaCB6oxKCFiMKR7w81JZ6gxekW6q7P4QQPlpNiHQrn384abnR8PKP83W6hZphtQUHLtiNtMW9NEKtI9Rb+uz3va+qEw+lGjtWkBjgmowHVRZ5/a1XXUnu8C10OFywmA2qKs5GfZYbFu/QT/PtUMy1xtBXPGFYIAFivUXdWt8OlLkFyeegkIDMtFpPn6WD3EA02v//PTsy+/z0cbdV2VkSq9fS6cPUza/GHd3al7DHl+0NRtgWF3iWCaHUtTeGWh2yx1bTE0s4az1TcdrsTsklIZloq8zNRkmuF0y2w5XBr1PuIlcst1KULGXz48x8wt/WI53HHl+cG1P7UFGtb1yLraMYOyYXJaPAst4X5faqbJca4PAQA04d5Mi1bD7ei25HcgBDwLQ3lZpiQF0NxcH8waEkDbd6gRVayt9udMc1NINIDIQT+uuYgjrb2YMXO1IwTT5X1B07g491N+NN7u7H5UPJOtJH4F7DGWpMSPKNFijU7Eku9gu++oi+hyMArw2yA1eSpzVEUBdO8M0WSWYxb39aDXpeA2aigzLuE5W+od27LoRPdaueQXBqStJ7Vsv1o38dVA8qgJSk5WC6eTMvQgkyU2TLgdAts0mD5LRW7O0sMWtKAXB6qyPe9oNp6tNuDI1k+r2vB4le/6DNNksjf3sZOdUbIvsaOAT6a5PIvlPztWztS8phq0JJl9k2ijRJ0NKo1LYktD/lmtIQPWmI9FiAw8PI3zTtkLpk7Pqu7OxdkBexMLckT7eET3dhyOLAIV5LFuPuatPn7lcHS+HLfRpRDwuwN1RTjYDl/iqJgureuRYtiXF89i7ZFuACDlrTQ4V3bzc+yqB0BeqhreeT9PXjx0zp8+5lP1RkHRMH83yT3aTxVNNX8CzNX7mnSfOooEHjCjzXoCJ9p8Z0YIw11i+VKOp4NGMMHLfkAgA0HW6LeR6xqj3v+5sIViJbnZcBoUOBwudVZJnJGi6T1rBY10+L3uOE6iGLdLDHYjGFyXkvy61oOMdNycpGZllyrCfnewU96CFrkVce+pk7c+Nw6TdZKSf/8OxZSsX9LKsnUfabZc7Hx27d2aNoWC/i3CseeaZFX5yVB3UPy/w6nO2J2N9I0XCmeQtxwQcuUoXkwKJ5gMHgTw0SF2t3Zn8loULPcvS4Bk0FRO7MkOaul7ngXHM7kLt23dDlwxLt79jj/TIst9NYIzWGKqqORxbifHTyR9L9RX80TMy0nBbn5WY7VpFbSp3vQ4nS51TeVTLMRG2pbcNuyjXBp/IZN+vOZ35VdrQZv+gNJZlpuPqMGOVYTNh9uxeubj2r6mIE1LTK7Eb6OxOlyq91FwZmWDLMRNu/mfJFqUdQr6Qjpf/8AKtpJUQ28MgKDliyLCTOGe06uL6+vi3gfsar1nlDDBS1AYIZgVGkOMrxBqFSaa0W2xQi3QNIn9soi3KrCzIDfh/x9NiShewjwLD1lWYxo73Fi17H2mL7n7a31uPqZtVF375YZqGFF2RFvlwwMWtJAu/cKJzfDjDzvoKVUbIPeH0daPMVtFpMBS687DRaTAe9sa8Cd/9yiyd4hpE9NHXb1Dc1iMsDlFpqMaR8oDd6r4AkVNtw0vwaAp1OqV8NC+lDLQ5GyG8c7PWPfDQrUEf7+SqIU8/b0utSfM1KmRQZEsbRgh8u0AMC3Zw8DALzwaW3MWwJEEm6Evz//oCW4CBfw1ISMKNFmiUitZykLfFxfpsUXMHQ7XOj0ZrTjqWkBPBklufy2PoZ5LW63wD3/2oaPdzfh7xsOh71dt8OF3cd8g/G0xqAlDciW55wMk/oiTve2Z7kL6rDCLMyqKcL/fGsqFAX465pa/PHd3dhR34ZNdS1YvbcZH+w4hvUHtN33gtKTzLKMLs3BaG/KfTAV48oTyhBbBm6cPwLFORYcaO7CsnXJyRIEc7mFepHj3z0UKWhpVEf4W0MWoqoD5sK0TR9p8WQqsizGiHvdWEyGmFuw27oDZ7T4u2BiGcpsGWjqcOCNJGStZEZ4WIh2Z8l/WSPcidd/Mm4y+U/C9RfquZWdQxajAblWU9yPNV3Oa4nh/XjdgeM47H3uNx9uCXu77fVtcAtP0FqaG1/2JxEMWtKAf01Lnk6Whw54rzaGewvUvjSpHHddPBEA8Kf3duNLf/wYCx9dhSueWoPrlq7DN/68Gh/uGlztrhSdDFpmDC9Qh6ENlroWt1uoRadltgxkW0247dzRAIA/vbsbnfbkdwC2+235EWumJdxgOcnXWhv6Pvz3lAk3o0WSc2CitWBHyrSYjQZcNasaALD0k4MR7yeaDrtTbRKImGnx+1r4oMU7qyXJxeTb/Cbh+pMBQHOnQ11SbfbrHIr2XIRy2vDYi3GXb/RlV76I0M6/1TtTZ3KlLaFjiheDljQQKtOS7kGLTJHKFzIAXDNnOH76pbEozLagOMeCoQWZGF2ao7743t3WMCDHejJwuwU+2duU9Emi/SWv6KYPK/QN6BokmZbmTgecbgFF8QUE3zqtGtWFWWjqsOPZlfuT/pjyfSHLYoTZaFBfW+12Z9hCeDnCP7gIV1IDjTA1LfHsKSMDoGjFuJGCFgC4YlY1LEYDPq9r6ddckXpvgWtuhgk5ETIT/rU6oZaHAG0GzDmcbuw5FrhtgFSQZVE3oZQdQ74ZLfEtDUnTqgtgUDyF1fJ3E0pPryugNuvQiW61libYZm/QMqkyL+TXk03ToOWjjz7CxRdfjIqKCiiKgtdee03Lh9Mt/0JcvXQPHfAuDw0PKry65axR2PCr87D+l+dh5c/OwTu3n4n7Fk4CAKzao307aLL09Lp01Q31yoZDuPKptXjgzdTMColFT69LnXsxY1iBb7dcDdqehRC4dsmnuOh/PkaXIzUzjmQranGOVd1t12Iy4IcLPNmW1zaFrwNIVPDJPsdqQobZ89jhgo7GMO3Okm8qbuiTUqTdnYP5AqD+BS3FOVZ85ZRyAMBznxyI+rjh+C/fRTKuzIYyWwZOrylU34ODadH2vOdYB3pdArkZpj5BocHg24RS/q2pM1ribHeWcqwmjPPWzqyPMK/l/R3H0N7jREVeBoZ7l9U2h5lSLF/jgyJo6ezsxCmnnIJHH31Uy4cJ6d5/b8P1S9clpZBLazLlm5vh6x5q6UrzoEVdHor+Rnb6yCIYFM8VilwjTWc9vS6c+eAHuOTRlbrpdFmzrxkA8J+t9WlTCL35cCscLjeKcywYVpSFkRouD+2ob8eKnY3YeqQNr208kvT7D0WeSIKnrJ7m7X6pO9Gd9NbS4JO9oihRNz1UN0sMu2dQ5O+XNSGxZFpKYtwWoC1K0AIA184ZDgD49xdHot5fOA3tMmiJfJLPtprw0U/Pxgs3nh72NrIQt7HdHrBM1x/rvJnI8WWhl1ZKgzahbE5gsFwwdYkoQjHuq97C20umVeIU75TiUBOfe3pd2NXgyRQNiqDlwgsvxH333YdLL71Uy4fpo6fXhWdX7cf7O44FtFumK7WmRSfLQ70ut7rO7b88FI4tw6z+4esh27K3sQMNbXbsaujAv79IzQmwv3Z4i/mOtPZoNgArXvJNcfqwAk/3hfdv5XinI+ndcf5Lj899ciAlgVt9W+gTYlleBgyKJ/XfFKUgNV6tIQpYow2YU/cdCrc8FOX7Y5nRIsW6a7T/VN9wpgzNx7TqfPS6BF5cm1hhs+x6ipZpATxZMkOIQmXJlmFWs1UHmvrfAed2Cyz1ZpG+NKks5G182zR4/taao2TNYjF9uG9eSyjHOx1YsfMYAOBr0yox2RuMfBEi07KroR1Ot0BhtgUVedF/x8mQVjUtdrsdbW1tAR+J2HOsQ92MK5l7WGhBCOGrabGadRG01B3vgsstkGE2qKOmo5k3qhhAcoKW+tYedYKkFo60+K7qnlm5v98nQJdb4Hdv7dCsELnX5caeY746kZVpEhjKSbhyqFW21aRmJfYmeYno3e2+oGVnQzvW7te+Wy3cCdFsNKA8z5OVkMF9soRaVonWQeQrxA2zPBR0YgwWT01LrBN6oy0PSTLb8vzagwllPWXdRixBSyx8dS39r8t6d3sD9jd1wpZhwuWnVYW8zZDgTEunXB5KPNMiJ+NuO9oWslj8318cgdMtMKnShtFDcjFlaD6A0JkWuWQ0sSI1RbhAmgUt999/P/Ly8tSPqqrQT2Q0/m/gG2vTO9Nid7rh9KaQ9dLy7F/PEunKxN9cv6Clv0HAjf+3Dhc/slJNSybbEb8lrK1H2rBmX/9OgJ/sbcJjK/biJy9/rkkGYF9jJxx+c0FSMUo+GiGEeiUn9zwB4FfXkrxi3Ia2HnzufUM9b8IQAMD/rT6QtPsPJ1K9RGWB3IQvuTNpQp3sfYFC6KAj3Ah/SWZH2nqcfQq5ux0uNeiJZUS7DICaIgQtQgh1+m7wcLlgF04qR0muFcfa7Xhra33Uxw8mfydDktSKm8wOoqc+3gcAuOr0YcgOUyQsf5++mpbEBsv5q8jPREVeBlxuEfKiXi4NXTptKABPQCKnFAcHtqmuZwHSLGhZvHgxWltb1Y+6usRSgv4ns421LWmzxh+KnLmgKECW2Yh8HWRa9ntTo7EsDUnTqvORaTaiqcOBnf0INoQQ2NXQAadbqC+ucNp7etGWwNqzrLuRMy2eWbkv/gP1I9Prx9rtAQF1suyo97xxyBPZ6r3NA75LuNwk0WoyYJLffipq0JLEJaz3tntS2VOr8vHj88cAAN7e2oCjrdrWT4VbHgJ8J/hDaZFpiRy02DJNsJgMIe/jcIvntZ6bYYq4lCPFkmnpsDvVydnRMi0Wk1/786r4s57xLA/FIlkD5jbUnsC6AydgNipqNimUPpmWJNS0AMCsmiIAwH8v3xzws+xv6sSmuhYYFOBibyF0ttWkbmsQXIy7RW13PkmDFqvVCpvNFvCRiF0NvhNDc6dD3RchHcmCrhyrCQaDor6IOx2ukFM19xzrwNwH3k/JlWQ4wTNaYmE1GTFzhGeZoD+ZgO5el5om/tfnR8IWOtqdLlzyv6twzkMfxt1NIoOWb3lTtu9uP9avzMBRv9ZCLZZu5JyHi6aUIy/TjHa7M+T6sxaaO+x4Z1tDnyBJLg2dUpWvnhABoKY4+QPm5NLQeROGYFyZDafXFMLlFnhhbW3SHiOUSCfEoRplWkIVsEYKFFxuoc4pCd7hWVIUJWzXj29Pmdg2wpMBVIfdGfZ1J7MsFqNB7XyK5MpZ1TAbFWyobcFN/7c+bOttKDJDUZqsoCVJy0NPe7Msl0ytjBhQlaibJga2PBcn2D0k3X7eGFQVZqL2eBe+/vgn2OBdkZCzWeaPLlEzcAAwuTIfQOC8FofTjZ313iLcipM0aEkWOVJYvlkmc5vzZPMfLAcEFtiFyras2HkMh1u68ZJGEzdjIZeHRsS5z0Qy6lpO+HVVHW7pxmdhlv/e2lKPfU2daOqwx53KlctD80YVY8H4UgDAs6sSn7lR73fFr0UhsizCnVhhw5yRniuoVSlaIvrF8i246f/W4/svbgwIsuUmiXL9XEp223OXw6kGggvGe5aGrpk9HADwYpLGwIfTEGF5yBe0pCLTEr74tbnTDrfwZHILw7TyAuHnq/h2741tI7wcq0ndPDJc5qe1y1dMHEsdRGluBu5bOAkWowHvbj+GC/74sVooGokQQh1yV5akIlHZAbf3WGfCnWG1zV14a4tnqUtu/RDOEPW57YEQImmZlqrCLLz6vbmYXJmH450OXPnUGry9tR6veYOWr51aGXD7KUO9xbiHWtTP7Wpoh8Plhi3DFHFPqmTTNGjp6OjApk2bsGnTJgDA/v37sWnTJtTWancF1NPrUveauGCipyI7nYtx/QfLAZ4lCRnAhApa5Jvgrob2AWvH3Z9ApgXw1bWs3X884WM/0RnYdfLPTaG7e55f4/sbi7fN+rD3d1xZkIkb5nneVF757FCfx46Vf6Zlzb7jSd+XRi4PjSuzqb/jj1NQjGt3utTi4je31OOW5zeoQYL/JFx/8k3/YHNXUjbX/GhXExxON6oLszBmiOe+z5swBOV5yRsDH4rd6VIzGMEtz4AvM5GKoCVSpqWp3XOMhVkWdZZMKDJDciTotVIXR+cQ4M3aRFki8v0MsY+hv/y0avzj1rkYMyQHTR12XLtkHe7+19aIwxRPdPWqtV4l/agB8Te8KAsWkwHdfueZeD27aj/cAjhjTAnGluVGvK0MJps6HOowQwDqdgn9UZJrxbKbT8fZY0vQ0+vGd/7yGWqPdyHbYsT5EwK7mSZ7g5bNh1vVJbqtR3xD5VJVhAtoHLSsX78e06ZNw7Rp0wAAt99+O6ZNm4Y77rhDs8eUnUP5WWb1KjlSMe6muhY1lT0Q/AfLSZF2epZvgr0uoVkhaiR2p0t9Y4tlRou/cWW5KMq2oMvhSnjKpZxfI+t/X998tE8QsKO+DZ/67a0R/EYcid3pUt9sK/IzcXpNISZW2NDT68YLnyYWbPtPnuywOwOuVvrreKdDTR2PK8tVs1kba0/0a4z8qj1NuOLJNdgbYRln/YET6O51ITfDpG6Y+b2/bsCRlm41sD21OjBoqcjPhMVkgMPlTsrSiVwaWjB+iPrGafIbA/9cP8fAhyOv4C0mA/JD1HrIK8/DSZ7VEqmmpbnD3icQjFbPIsmahKWfHAgIBGLZ3TlYtBqbWDuHgo0vt+Gft85Ta0CWrDqAq55eGzb4lZmwomxLwBJlf5iMBnUPrR318b//tnQ51Cz5zVGyLIA32PS+2cmlmNwMU59dqBOVbTXhqW/PUJfCAeCCSWXItATe/4RyG4wGBU0dDvUibPMA1LMAGgctZ511FoQQfT6WLl2q2WPKpaExpbnqG+bWI20hI/ITnQ5868nVuPyJNahtHpidZ9vVTIvvBSzfBEMFLYcDOltSU7fgr+54F9wCyLYY4756MRgUzPGeVBOt7ZC7x06rLkBxjgXHOx197uuvawJPVIfjuNptaPW80VpNBhRle/b3uGHeCACe+R8JtV163zzHDvFcVa3c3Rz3fYSzw1vPMqwoC9lWE4YVZWFoQSZ6XQKfJtj263C68dNXvsDqfc144sO9YW/3kTfLcv6EMjx7zWnIMBvw/o5juOzPqwF4NkkMni5qNCjqsmJ/l4hcboH3d3iWCRZMKA342rdmesbAb6prwef9GAMfzjG/oWWhrjLLbBkwGhQ4XO6o7b/xCDWnpSjHCoMCuIWv5kGKNqNFum7uCAyxWVF7vAtPfeQrPI9nRotUEqWFOpbBcuFkmI2466sTseTa02A1GfDZwRNh66OSXc8iyezIzgSClufX1qK714Xx5TbMHVUU9fYGgy9zJXeD7s+MllBMRgPu/9pk/PRLYzG6NAc3n9E3mMowGzHG+/4l61pk59DEwRS0DARZhDt6SA6GFmSiJNcKp1uoVc7+3thyFD29npbjJZ/0f58Qu9OFa5d8ij+8syvm7+nwm4YrRWp79r86lX80qSQ7h4YXZyeUEpznfaEmWtshh5IVZVtw0WRPdbv/ElGH3Ynl3q4i2f56JI4ukkPebonK/Ez15/vKlAqUetsu4x0212F3qoHpN6Z7WgiTWdeibrbmHc2tKIqabUk0MPzb+jo1OP7Ptoawy1lyaejMsSWYN7oYS66diUyzUf3e4KUhSda1RMrixGJj7Qkc73TAlmFSp9BKxTlWXDTFOwZeg6J1tQg3zJwik9GAcm8dRTKLcWU9iP8J32hQUJgdOrvhy7REXk7Itprwi4smAAAeXbFHPeZ4puFKpTEvD8UftEhnjytVO1rCLdMcUwulk3uSHyeDlob43n/tTpc6TO7mM0bE/P4pgy45m6o/M1rCURQFt5w1Cu/cfqY65j/YlEq5RNQCp8utHs+gyrQMhN3eoGXMkFwoioJp3kmsoepa/uF3svvburqE2mP9baxtwYqdjXjq430xt+YFF+ICvhdz8Cj/1u5e9QQIDEymRW7LHm89iyRrLjbVtSQ0ClsW4hZkWfDVqZ5isf9srVf3CVq+8TA6HS7UlGTj66d6goR4Mi1ysFxFvu9N2mIy4Bq/lHQ8/DdskzVWG/q5dONPpqjHlfvWxueN9gYtCRTj9vS68L/v71H/39LVi7Uh5tQ0tPVgR307FAWY731OZ48swnPXz0S2N7U8a0ToK8lktT2/410aOntcKcwh6jXkc/bvz48mfR+pWIaWJbsY1+0W6nJy8Ak/XKCw95jndxxLtuHiKeWYNaIQPb1u3Pfv7eiwO9XXW1xBiy3yVNxQ2aJEVHv3QgoXtKiF0jEOwIzVWO9JPd7loTc2H0Vjux1ltgx8ZUpFzN8nn1t5gdLfItxETamSxbit2NPYAbvTjRyrCcNi2JMqmQZf0OJdHhrtLcqb5l0iCu4gOtLSjU/3H4eieK6qOx0uvPRp/zpy5JVjl8MV895BoWpawk3FlSdfWc+x7WhbUooZ4yEzLTUJBi1DC7IwvCgLLrcIeTKMRi4P5WebcWp1PoYWeJ6793Y0QAiBv672LA1dffow9Y32cEvoNHUosv6lIj/wjU5mSbYcaY2rI0We3MpsGaguykJVYSac7sSXboLJqx3/q6M5I4uhKJ7JsPHu2bLs01rUt/WgPC8DX5vmCQrf3NK3mFVmWaYMzUeB35XfzBGF+Pstc/Crr0zAV7yZjmDJanuWo/tl11CwqVX5yMs0w+Fy4+Dx5E7g9e1pE/6EKGe11CVYsBmsvcepTvoODlrkEkJjmy9Q6Ol1qc/dmWNKot6/oii455JJMBoUvLW1Hsu8NVz5WWbkRhkCF3AsUTZNTEamBfAFLQfDLO2rc3SSPF5eZloONHXGtav639YdAgBcMbM6ZJAdjswUyRlP/Rks1x9TvG3Pmw+3qtNxJ1TYYh4wmiyDKmjpdvgqukeXev6wplXnA+ibafnX554sy8zhhfj+OaMAeIrQ+jOUS17VALF3rAR3DwHhgxaZsp1QYUOWxYieXndS513EQp3REme7s7+5/Vi+aPHLtCiKgq+e4rli+cemI1h/8AR2NrQj02zE104dikpvtqSpwx7zm4sMWirzA68eSnOtyLGaIATimvsjB5zJlsv+Lt34c7rcambRf1v7wmwLJlZ4/h/PUlS3w4VHV3hqWG49ZxQu8QYtb2+t7xMcy3qWM71ZHX/jymy4Yd6IsN0qyWh73tfYgb2NnTAbFZw5NvwJeVhR5BOb1NLliCv71dDqq2kJJ9kdRPL9INNs7FNYqha/+s0w+WDHMbT1OFGel4HTa6LXTwCeeg3ZMv7btzw7hscyCddfSZj2aSlpQUtR5KCwQaPlodJcK/KzzHALxDwssu54F1bva4aiAN+YMTTOx/O8d8jOoWINlodiMaYsBxajAS1dvWrLdqqXhoBBFrTsbfR0DhVkmdU13ClD82BQPG2n/hMyX/MuDV0ytRILp1WiMNuCwy3dCY2K9n98KdZ1bLUQ1z/TEqYQV775VRdmqSeprUdSW9eijvBPMNMC9G9ei8y0FHh/R5d4l4g+3NmIRz/Y4/1cBfIyzcjPMqszI/zbjiM5HCbToiiK35Vd7CdbmWmR9Q1zk7gH0/4mz/j+bIuxT/peDQzjKPp9fu1BNLbbMbQgE5dNr8KckUXIyzSjqcOB9X7dWC63UIOuM2K4gg9W4217PtaP3XJl19DpNUURR8GrSwgRgpZOuxNnPbQCF//vypiXdRtimP+hLg+1JCfTEulkH6r49e/e2q6F0yrV6c6x+OF5o1GcY0Gvy/O7iGdpCIieaZHL8FovD/lG+Cc306IoilpUH+sS0cufebIsc0cWqxdTsQoOugYq02I1GdVl6A+8c3ImVSY2ALY/BlXQ4lsaylWLnLIsJjV1LrMtuxrasf1oG8xGBRdOKkOG2Yj/On0YAM8GeYkKDFpizLT47fAshV0eavFV8su9HkIVGGul2+FST/7xjPAPNntkERQF2H2sQ113jpVcY5ddKWPLcjGuLBcOlxsrdnqu/uVzqSiKugdMrHUth9VMS983FtnifSCOTrOj3p+vzLuB3mzvFe+O+shLNx12J7YcbsW/Pj+Cpz/eF/JqUq5xjy3L7ZOinT/KE0ys3NMY04m40+7E494sy23njIbFZIDZaFCXXt7c4gvmvzjUgpauXuRmmDDVWzMWj7xM30VFIuPQe11uvP6FZ9kj3NKQpAaaEZaHdjW0o6WrF/saO9Xl2mjk8lBphBNismtaIgUtwZmW5g57wE698bBlmPHzC8er/6+Ks2ZBzhZp7rSHzFwne3mo9nhXyLbySMP/+kstxq2PftHodgv83Ru0XBZnlgXo+zc2UDUtgC+zIn/dzLT00y61CDcn4PO+JSJPXYvsNjlzTIm6Hn/16cNgMRqwsbYl7JbdkXQ7XAFLQjEHLT0yaPG9gNWgpSv08lBlfiYmVKQ+0yLf+G0ZJjXTkYj8LItaiS6X6WLVomZafC/ci0/xFbVNrcoP2LxLFtQejuFqVwjhWx4KcXVZXegJ1Gr7kWkpyrGqWbLVewOzILXNXbhuyaeYcd+7mHTn2/jKIyvx/Rc34r7Xt+PWFzb0CT7kVd748r5XOzOGF8BiMqChzR5Tl85zqw+gudOBYUVZuNRvGuaXJ3uKh9/aUq+eGD7a5cmyzBtVHHFgWSS+upb4gpaWLgeuefZTfH6oFWajonaIhSOXh2ojLOn5B071MWbkYloe8p5Uj7R0J6X2LHKmxbtHjTcD9K/PPTv1Tq7Mw+ghkQeYhfK1aZWY7p1mPCbO7y/K9rRgCwF1AJ+/ZAUtFfmZMBoU2J3ugGUxwJMNlMtTyV4eAuIrxl29rxmHW7oDivHjURqcaennCP/+kJNxASDLYsSI4pwIt9bGoApadnuHrQW/yOS8Frl54j8+96RNZfcJ4EmvXjLVc/J7NoFsy/6mTvifU2INWuIpxPXNTMhU93rYcqQ1ZRtCynqWEQm2O/u7YqZn+NeSVfHVEcmptP5B01f9gparvVkWqTI/9mLc450O9PR6jiVU2n94UQKZFlmI63d/obp79hzrwGVPfIIPdjb6dnLNtmD6sAJYTQZ8fqgVq/YEBjlqEW6IoCXDbMRMbxvwx1G6iNp7evGkdzbHD84dHVAkOG90MXKsJtS39WCjd97Jh7s8V/CxFHeGE2635/d3NOBP7+4OWau1t7EDCx9dhU/2NiPbYsSf/2t6QJdXKLEEmv5BSyzLiB12Jzq93UiRruLLbBkwGRT0ukTcGcVQInXdqGP4vX87r4YZxx4rg0HBs9echj99a6r6vhgro0FRlzBCLRH1Z06LP7PRoC7jBi8RNXV4ti/wP5ZkksskscxqeXm9p8Hjq6dUJDQULjjTEq19XUtyDyLAN3Au1QZV0CIzLbJ/X5KZls2HW/Hp/uOoO96NLItRnZgr3TDfM0TszS1H456tIK9m5XMYcyGu3bthYpzLQ6OHeIqi2nucKdsQ0n9GS38tnFaJojjriFxu35b2/kPLqgqz8J0za/CliWXqbA5paBzLQ7LduTTXCqup75vLMG/xcXw1LZ7HLfcLWvzrWoQQ2H60DZc/sRoNbXaMLs3Bq7fMwed3no/PfnUe/v69OWqA99iKPQH3LfccmlAe+krY9ziR61qeX1uLlq5e1JRkqzVCktVkxLne18lbW46itatXnWacSD2LpM5q8QYMbrfAw//ZieuXrscf3t2Fc37/IS5/YjWWbzyEnl4XPt7diIWPrsKB5i5U5mfi77fMwblRloYAX6bl0InusMGxf9DSEEPQoraxW03I9rvYCGY0KGpQlYwlooiZFhkktNmx51g7vjjUCpNBCchCxisvy4xLplbG1ekiyeWq4MyVECJpmRYgfAeRDBJLcqyanFjlhfGxdnvE7T3aenrVpdXLZlSFvV0kRdmWgJ9hoGpaAM8qhtVbBD5pAJaGgEEUtHQ7XKjzBhrBmZYRxdnIyzTD7nSrFfHnTRiCLEvgG864MhvmjSqGW3imn8ZDBi2neNf44y3E9Z/Tkp/pOSH7By3tPb1q50xlQSbMRoM6mTFV81qS0Tkk+dcRPfVxbFvO+/8+gkenL75wPP589fQ+VzLySiyWUf6+ItzQV++xnAD99fS61BqccpvvPk8bXgCL0YAjrT345+dH8K0n16C504GJFTa89J3ZOLW6IOAN/aYzamAyKPhkb7MaMJzodKgtneHS93Li5tp9zRGP9z/eoPGGeSNCvsFfOMmT0n5jcz1W7mmCW3guDKJlOSLxXx7qcjhxy/Mb8D/e+TCneIvn1+4/jh+99Dlm/vpdXLtkHdp7nJg+rAD/uHVu2AFYwYbYMmAxGuB0i7BZlHgzLcfiaKVN5m7PsRTidve68Bdv2/9ZY0uSPj01VrLYendQd013r0st8E1O0OLNpB0PDlq0WxoCPJlxubVBpCWif31+BHanG6NLc3DK0MRO8gaDbxdugwLkJ+H3liiT0YBThuYDAE6pYtDSL7JzqDDb0ueFqiiKmm3Z4C3GDZfylCPbl31aF9dAqr3etfn5oz1Xn+09zpBj+P0JISK2PHf3utSZIPKEmp9lVpeSZFvrlhQFLfLNXV4l99fVs4fBYjLg87oWdWv0SGTnUK7VFPPVn2xdjiXzFakIF/Ck+y0mzwnwSAzLTfIqM9NshM1vc7gsiwmnDssHAPxg2Sa0dvdiWnU+Xrjp9JAboVXmZ6oZkMe8HVLbvQWAVYWZYWdoTKzIQ26GCe12Z9jap7aeXnzunbkQbrnnzDGl6qTbP3vH+vdnaQjw/Q3tb+rA1x9fjbe21sNiNOChy07BP26dh5U/Owc/WjAGlfmZaOtxwuUW+NqplXjhpllxnYiNBgVDvSeXUF0mQojAmpa26H8n6vyPGE6IMmhJRjY0UtCSbTWpQ/1e8i5HfO3U+Is+kyVcoar8GYwGBVmW/u+fIzMtwYXqWo3w9zd2iOf9N1Ix7svrPQW435xR1a8ldfm3VphtTflclGD3LpyE//7yOFwcx4C8ZBo0QYvcPHB0aejCoGlVvpHiBVlmNbgIduaYElQVZqLd7lTbKmOx13tFMbkyTx2zHG1Jwu50q733/iee3AwT5N+3fJEf9qtnkSaqHUSpKcbd35y8TAvgGbUuOxue+ih6HVGL32C5WMlMy9HW6BvXRSrCBTxXPMNi6EaR5MmtPC+jzxuWbPsGPAPZ/nLDrIhXnt87qwaK4hmrv7uhXV0aGh8h42A0KOp8jk/2hl4iWrO3GS63wIji7LD7y2RajDh7nOf1IjdJ68/SEOBZ0jMZFPT0esaBF+dY8OLNs9QhfhX5mfjBgtH46Kdn4/+un4k//9ep+P1lp4RctotmWIQhZMfa7ejyuziJpRDXdxUf/YRYpc5q6X+mxVcLEnpJSp6ge3rdsGWYcM640pC3SwUZtARnIfwDr2TsDBxuDMGxOALLRPnG+YfOtOw51o5NdS0wGhQsjLODK5gstB7IehZpbFkubj5jZMJF+P01iIIW355DochMCwB8eXJ52Ct1g0HBQu9V7WveYrZo3G7f1drIkmz1pBftjUouDSkKkOW3rGEwKOpykXyjUotw/YaeTVQ7iJJbjLvtSBt+sGxjQHdLh92pVuMno6ZFkpmtt7fVR60VOdHpGywXqzJbBgyKZ1fs4A6DYOo03Ahp/2FxFOPWhyjClS6aUoEcqwkLxpfiuetmBhRihzKqNBfneztlHv9wb8QiXH9zRsqgJXQxrpy34h9EhfKlSb5aIavJgFkjCiPcOjqz0aBmWyaU2/CPW+dh+rC+92k0KDhjTAm+NKk84ZOcWosUItAM7l6KZXkonlZameVJak1LmM49/w1ML5qSWNFnssil6z3HOgI2GQ21d1J/hOsOkxcMZVpmWsIEZpLMspw9tjTqhpXRyOBrINud08WgCVr2HAvdOSRNrc5XsxfBxYbB1IFluxrRHOVEB3hmcXT3umA2KqgqzPIbHx/5jUrOaMmxmPqk/IIHzKntzn5ZgPFlNhgUoKnDkdSdZB/9YA/+sekIrnhqDf57+Wa09/Sq9SyF2ZakveEAnpk6Z40tgRDR9/VRR/jHEbSYjAb1jSva8xGtpgXwOwHGMF8kVOeQNKI4G5vuOA9PX3Nan23gw7nlLM/k5n9sOqJmTsIV4UqyGHfdgeMhtx+QHUxzowQt54wrVaewzqopSsoJ8deXTsZPLhiLV743O+6BW/GoijBgTl5syEC1PoYuH9+eNrEsD3kzLUkYMBetgLXEL6vw9QS7hpKlMj8TuVYTnG6BfU2+uhZZSN/fwXKSfG6bOuzocvhm7MhsmJbLQzLTsqu+vU8Wt9flVof7JTKbJZh8DxuoGqV0MmiCFjXTUhr6TdyWYcZdF0/EbeeOxmlhdp+VRpXmYHJlHpxugdc39913JZhcGhpWlA2z0aC+AUe7upLTQP3rWaTgYlxf55DvzT3TYlQ7pZJVjOt2C6ze58uwvLC2Fuf/4SMsW+fZh0S2/SbTjfM8W6H/bX1dn9k0/nwj/ON7w4t1wFy05SHA9/MfjGE/Gdk5FO5qL9706ilV+Zg7qggut1D/HqIVpI4uzUFxjgU9vW5sCtrK4nBLN/Y1dcKgeAb+RSKzQgBw3vjkLDucNrwQi84e1acgPtmGRZicKjcAnT3SE7S1dPVG3fKhoS18MBpMvl6PtPT0a4sQIIagxXtCqy7MUmesDBRFUdS2YLmUCSRvRouUl2lW78v/+dVysJw0vDgbFqMBnUEzugDP1hdNHXYU51iSskx3ydRKLBg/pM9Ih5PRoAhaAjuHwg+7uWbOcNx+3piY0sxyDXJ5DEtEsnNopDfdLa+uop0kO0KM8JeC2559M1oCg4aJFcmta9nZ0I7jnQ5kWYz4yw0zMawoC0dbe/DXNd6gJYlLQ9LcUUUYV5aLLocLL3qDo1BOhBgsFwuZOYnUQdTT60JTh+f+I131V8fR9nw0aLBcMshsC+AZ7lQdZVqpoijqCTm4rmXlbs8E4VO8GwtGc9/CyfjTt6biyln6euNUlxCau/oso8pMy9SqPLUwNFpdSzxX8UNyM2A2KnC5RUxZnEiinfDnj/ZslPndM0cmpV6kv0ItnyQ7aAFCb9VwTMPBcpLZaMBI70Wj/8/ocgv84Z1dAIArZw1LqGU8WHVRFp6+ZgZmDO/fsuxgMCiClj3HPJ1DRdmWpPWwX3xKOQyKZyDdgShLAb6gxfMHrGZaoqSE20OM8Jfki1pmF2TQEnxCVTuIkjTOX+6JM3NEIeaPLsFbPzgDN84boc6fCZ6BkwyKouDG+Z5sy9JVB9Ab5orUN8I/zkxLfvTlOhnQZFmMEd9Qh/ttwBetsLc+aIR/MswZWaS2ToYa3x/ue4C+dS1y6Nz8KEtDUmG2BZdMjW8fm3QglxDa7U71b0jap3bE5agZsUh1LW63ULdfiKVewmBQYs68RuJ2i6h79pw7fgh23nshrpxVnfDjJNM4dWqs74KqNUoxcSKqiwIzaXanS53Em+x9h4KF6pJavvEw9jZ2Ij/LjBu9s78oeQZF0CL3HErmCbU0NwPzvB1G/9gUedS83N1ZBi2xFt/52p37vgnZ/DItXQ6n+iIMXrqQmZbgltZjbT14+uN9AZtExkIW38oTXabFiF9+ZQJevWUuvn/OKFxxmjZviBefUo7iHAvq23qwbv/xkLcJNcI/FrEsD8kW5sr8zIhXqf6jw6PVEWmRaVEUBT/70jhkmo34Sowth3O9mZaNtS3qur/bLdTMy7wwnXSDRYbZqAYY/hkyp8utXp2PKM5Wl3siTa893uVQ54zEWlyZjN2e2+1OdeJ2pKA6ePfngaR2EPktDyVrGq6/4I0T5VYGFpMh7guceAVnkxxON/74rifL8t0zR0bczJMSkz5/4f3g23Mo/j02IlnoneXy2qbDEbtz1ExLaWCmpaWrVy22DUXWtORGWR6SJ1tbhqnPi13uQXS4pRsnOh1wuwVeWFuLcx/+EPe9vh3/897u6D+ol9PlxlpvwDBnZODV99SqfPz4/LHqXk3JZjUZ1QAs3Ju7rxA3vjeCijgyLdEGppmNBrVO4UCEJSKH062O44+l9iEec0YVY+vdF6idV9FUFWaiMj8TTrfAugOeeTjbjrbheKcD2RZjQGfdYBVqR+BDJ7rhdAtkmD3F2vJ5ipRpkQFNcY4l5rS/b1ZL4sW48mSfYTYk1PY9EMZ4T+j1bT3qBYe6FUEST+Z9gha5u7PNqvky2Vg10+IJWl5aX4dDJ7pRkmvFNbOHa/rYJ6tBEbT49hxK7tLFBRPLkGk2Yn9TpzqAK1hbT696xS1bOHMzfMVhka7uO0LsOyTl+3UPqUtDIeZo5GWa1RetnK7q6fjx3Hc8u+huPtyKDrsTeZlmdVO/VIoWXPgKceMLnIbGELQcijFoAXwdRKG6UaRj7T0QArAYDSiM83hjEc+AKUVR+iwRyVbn02uKkrLmnu6qi/rWPez3m/BsMChqNqY+QnbyWBwzWiS5PNWfTIsWtSBas2WY1Qs4mYnQ4ucILrRW5+hovDQE+LJJ+5o60drdi0e8F4m3nj0q5q5Aio9u360cTjfe2nIUNz63Dit2eQoKE9nNNJJsqwnnT/TMxgg3s0XOeSjNtQZcPfjansOf2NTNEiPUtLR196on1KFhulomVXoCjDv/uRWfHjiOLIsRl3mHdMUyd0KSywWza4oGZOpihXqlGznTkmghbnuPU60LCHYkyu/Yn3yTjJRpkcWcQ/IGfoIlAMzxjvSXy3+y1Vlu3jjY+YYC+l6P+4ImPJfH0PZcn0BXSjJG+esxaAGA8UEbC2rxc6hB4XHPbtqp6BySymwZsGWY4HIL3P3PrTjWbkdlfia+NTOxfYYoOm17DZPkzyv2Ii/PBovJAIvJgN0NHfjHpsMBRXVzRhZpkuZeOK0S/9h0BP/6/Ah+cdH4Plelst1Z1rNIlfmZ2HqkLeLVlaxpiVaIK9/swp1QJ1bk4Y3Nnv1jzh5bgnsXTgIAvPzZIRxt6YHbLWI6ccqrcHmCS7Vytcun70lDCJFwIW621YT8LDNaunpxpKUbtrK+3+9bHor+RjfMrxg3HLWexZa8Itz+kMt9mw+34lhbDz494FkGjDZUbrAInWnxvHZHeDviZMF0pO6hRE6IvqDl5Mq0AJ5i3He3H1OLcbWoaSnP8+ym7XC50dDW49fdpf1ME0VRMK7Mhk8PHFd31v7BgtG6WcLTI10ELf/7wR4YrH2XRobYrPjaqUPx9VOHatLVAng6K4qyLWjudGDl7iacHdRz76tnCWwFjqXtOdLykH9NS7h2Z+mbM6pwsLkTZ4wpwUWTPZNDe11uKArgcLnR1Gnvs715sJ5eF9Z76x3mRJnZoRV1c8MQmZbuXpc6WTORupqKvEw1aAk120QdLBdDp8/wCBNWpUjTcAfCEFsGRpZkY29jJx55fw8cTjeG2KyavW7STXWI7Rfk8tAI7+aNsXQPNSQwHl6+bo+2dqPX5U5oOU6vQYus+dh+NDDTkqzhcoBn3tHQgkwcaO5C7fGulGZaAM/PKC8Cakqy1a1JSBu6CFq+MX0oFEsW7E7PicuWacbFp1Rg3qhizdsvTUYDLj6lAks/OYDlGw+HD1qCMy0xXF21x5Bp8S/EDTc/pCTXit9945SAz5mNBgzJzUB9Ww+OtPREDVo21rbA7nSjNNfa52dJFRkwHGnphhAioIhOZlnMRkXdGC4elQWZ2Ha0LWQQ6XYLHJXdQ7EsD8lMS1NXn+OU/PcdShdzRhZjb2MnXvzUMwtn3qiStJjnkQqyDqmhzY6eXhcyzEbsb5RBi8y0eJ6rxg572OBCXsXHMx6+JMcKi8kAh9ON+taegAm9v3t7B2aOKMR/zRoWMRuqxck+FeTy0K4Gz9RYrYKvqsIsT9DS7AtatBzh708GZgDwowVjBmxPnpOFLoKWu746ETZb6gtDpYXTKrH0kwN4a2s96o53qW86gK+mJfhEH8s6tm+4XN8XsH/QIseBxFJv4a8iXwYt3ZhalR/xtqvl0tDIogE7kcmTRk+vGy1dvQEZlROdvhH+iRyfb1ZL36vopk47HC43DEqMm+AVZkFRPDVJxzsdIWcDpVumBfA8t39Zc1DdpHP+SVLPAnimKOdaPTte1x3vwtCCLBzxPkc13qClKNsCs1Hx7FPVbg9ZlK3WKsVxQjQYFAzNz8S+pk7UnfC8f2w53Iprl6xDU4cd//7iKN7YfBQPfuOUgPcWf3rNtAwvyobFZECXw4U9jR2we7Ol4fZPSpR/B5Fvh+fUjLw/vaYQRoOCSZV5uGhyefRvoH5hSBiDU4bm4fSaQjicbtz3+jb1806XWy3GHFkaOmiJ1LESsRDX+6K2+7XOVoVZHgonlkmw0ip1PsvAncgyzEZ1F9Pg31uiI/ylSAPmZPZliC0jptR9wNyPMG2sR6OM8B8Ip9cUwT/ei7bf0GCiKIpa13KwuUt93eZnmdXg2GBQ1IxkuCUi2U4b7wnRP/P6yZ4mfOvJNWjqsKOmOBuZZiPW7DuOC//0MV5aVxtyvIJegxaT0YDR3vdGOU7BoHj2W0umYX4D5hLp8OqPUaW5eO/2M/H8jbPSouh+sGPQEgNFUXD3VyfBaFDw9tYGfOjtVqo70Y1el0Cm2YjyoBeI3I25qcOBbkfovUw67N45LSGClhyLCf5//zlWE2xxTpGsjFDYGngcTnxe1wIg+h40WpOBVvBJI5HNEv1VFoQP4PwHy8XKV4wbuq4lHTMtBdkWtZV9XFluv3ee1ZthfvtG+epZAmvRyiMMmOt1udWtHuINRmVdy9/W1eHaJevQYXfi9JpCvHbrXLz1w/mYMawAHXYnfvb3zbjhufXqhYqk16AF8E3G/dQbtNgyzUk/uctMy476NvViMFVBC+DZ3iTaTu2UHAxaYjS2LFcdFnT3P7fC4XSrnUM1Jdl9XoS2TJM6NC5ctkXtHgrxx24wKAHr10MLIk9qDUW+AUfLtKw7cBxOt0B1YVbY9HSqlIdpe/ZNw03sTVudAROipiXWwXL+1GLcEB1ELrdAg3d2T3kSR/gng9y8bcH4IQN8JKkn/7brIgQtkQbMyXlMZqMS/6wgb9C8/uAJOFxufHlyGZ67fiZsGWYMK8rGS9+ZjcUXjoPFaMD7O47hRy9tCvh+LbpuUkXOMlnr3YhViymx8rmVg0azLUYGEYMUg5Y4/PC80SjOsWJfUyeeWbk/bBEu4MnOVEaoaxFCqIW4oZaHgMA3qHjrWQC/5aEoo/yDR/cPpHAD5k4kOFhOklmUhvYetQtJOpxA0FIdoe25qcMOl1vAaFDSLpux6OxRePyqU/H9c0dFv/EgM6zQt9mlrEWrCQ5aIgyYkxcpQwuy4s4U+F8MfHv2MDxyxakBbbFGg4LvnDkSyxfNgcmg4OPdTdhYe0L9uq4zLd5iXBn0afEzBG8cmsosC6UWg5Y42DLMWHzhOADAI+/vVutAwnXbRKprsTvdakFkuCsC/xd3PEsXUqw1LXKTxIFeGgJ8HURHW0IvDyVawFeUbYHFZIAQfVP/8vmJpXNIkpmWUAPm5FV6aa417TYXzDAbceHk8pNyjkTg8pCc0RL42i1TB8z13VdqgzeIiFbUHsrZY0tw3oQhuOMrE3D3VyeG/buYWJGHS70ts49+sEf9vJ6DFv/uGkCbnyE3w4xCv8J9Bi2DF4OWOF06rRLThxWgy+HCR97aluAZLVKk3V1llkVRgOwwRWmBmZb4l23k4zd1ONDTG7qu5kSnA9uOegY/pUXQEibQSnSEvxRpt135WJUxDJaThoUYVibJq/R0qmch39X4oePd2NsYrqZFDpjr+5rdWNsCAAkNsczNMOOpb8/A9fNGRF3m/d5ZI6EowLvbj2G797Wp56ClJMeKIr+AQqufwT+bFc8cHdIXBi1xMhgU3P3ViQFdGOEzLeH3HFEHy1lMYVPN/V0eys8yI9PsuaION+Vz7f5mCOHZtynaLJdUKM8PXVNwop81LYDf8LqggEjNtOTHHhjKuR/NnY4+WwNosbsz9Z//5FQZBAwvDnzOy/I8J7vgvz+3W2CTt1h9WlWBpsdZU5KDL3tbZx/9YA/cbqHrmhZFUdQlIkC7WTPDAoIWvvYGKwYtCZhUmYerZlUD8GRKgq/WJLnccDhETUtHlHoWoP+ZFkVR1CAg3BKR3PX39JqBz7IAvuxQfVsPXG5f66dvhH/imw+Gant+/YujahYnlhH+Uo7VpLZnB2db1M6hNBnhTx4mvx26AU8QkxWU5ZSj/I+12eH2+/uTG+JlmA0BJ2CtLDrLU3P0+uaj2HKkVZ3VpLfhctLYIb45W1oFXv51LaUMWgatlAQtjz76KIYPH46MjAzMmjULn376aSoeVlP/7/yxmFhhw6VTK5FhDl0fEGnPkXbv1XmkCveAmpYEMi1A5PkkANQ9QSZV5iV0/8lWnGOFyaDA5RbqTAzAv3uoP0GL501NBnB/W1eH77+4AQBw+Ywq5MbZ1aCOhg8KWphpSV/VRb4LjFAXG6W5VnX7i+PevzkAalHslMr8lOyKPaHChnPHlUII4IE3dwAArCZD2PeadOcf6KUiaOHy0OCl+avvpZdewu23344777wTGzZswCmnnIILLrgAx44d0/qhNZWfZcHrt83Hw5dPDXsbmR051m6H3RlYUxJpsJwkX9xZFmPirb7qaPzQy0M76z0FiWOTvEN2oowGRa0F8c8OyYm4yVgeOtzSjWdX7sdP//4F3AK4YmYVfvO1yXHfX7hi3HSc0UIe/ksIoYIWs9GAYu+EY/8l1Y1yaUiDTVnDWXSOJ9sid1/X49KQNK4sBUFLke+5TaehjpRcmgctDz/8MG666SZcd911mDBhAv785z8jKysLzz77rNYPPeAK/GpKgoMG3wj/8EGL3M04kRktkm9YW99MS3OHHU0ddigKMHpI+mycFxxoOV1utHl/X/1aHvJmq9bsa8Y9//ZMNr75jBr85tLJCXX5DCvytdD6O9rm+V0z05J+hhVFDloA3/MWELT0owg3UadWFwSMIdBz0DK6NFcdlhnvkMxYVbOm5aSgadDicDjw2WefYcGCBb4HNBiwYMECrF69us/t7XY72traAj70TFGUsHsQyULcSIOWJpTnQVGA6cMKEz4G/+xCMDmIqbowq8/a/kAKrsORRZOAL5BLhFwq63V5CgR+fN4YLL5wXMIBoTwB7mroUKceCyHQ0OrdVI9BS9rx7zCpKQkdtMgT3lFva3yH3Ymd3mXUadXaFuEGW3S2b56OnoOWTItR3VFcq4L/Mu9O5kMLMvnaG8Q0PVM1NTXB5XJhyJDA6ZtDhgzBjh07+tz+/vvvx913363lIaVcZUEmdh/r6DOJNZaalslD8/Dpfy8ImD8Q9+NHmNUi34jHpMnSkBQ8yl8W4eZaTf2qJyjPy0SO1YQOuxN3XjwB180d0a/jHO69Ut9U14LJd72NiZV5mFxpg8PlGV6XDt1YFCgw0xI6u+jLtHheM18caoFbeF5Lqb6CnzOyCFOr8rGprkXXQQsAPPD1Kdhw8ARmDNMm8DMYFLz5gzPgFiIldUc0MNLqmV28eDFaW1vVj7q6uoE+pH4LV4wbS00LAJT0c0BZud/+Q8Ebse1sSK96FqkiqKZFFuHmZ/fvTdtiMuCFm2bh5e/O7nfAAgBTKvPwX6dXY4jNCqdb4PO6Fvx1TS0AT0GxxZRWLy+Cpw4pL9OM4hxL2DEC6oA5b8ZMLg1NTeHSkKQoCv77y+ORn2XG2d4tGPTq1OoC3Di/RtNNBS06Llam2GiaaSkuLobRaERDQ0PA5xsaGlBWVtbn9larFVbr4Kr6lh0rwcszsdS0JIO8auzudaGlq1fd0RYAdjW0AwDGlKVZ0BK0/UB/B8v5mzI0v9/3IRkMCu5bOBn3XjIJh05047ODJ7D+4HFsOdyGi0+pSNrjUPJkmI14/bZ5MBqUsFfj6ih/b22S7Bw6NcVLQ9LMEYXY+KvzEl7GJBpMND1jWiwWTJ8+He+99x4WLlwIAHC73Xjvvfdw6623avnQaSNaTUuoHZ6TKcNsRHGOBU0dDhxu6VaDFiEEdtV7gpZxaRa0lAeN8u/vDs9aUxQFVd7NJhd6R7BT+oo288h/00QhxIAU4QZjwELkoXn++vbbb8dTTz2F5557Dtu3b8f3vvc9dHZ24rrrrtP6odOC7FDYcrgNxzt9cx/UHZ41DlqAvjUiAHCktQftdifMRkVt3U0Xsg6nudOz/YAv06LvNX3SB98o/x7UHu9Cc6cDFqMBEytsUb6TiLSmedBy+eWX46GHHsIdd9yBqVOnYtOmTXjrrbf6FOcOVhMrbJhYYUN3rwtLVu1XP6/u8GzV/kTsayH2LVHJLEtNcU7a1V7YMk3IsnjWpY+29viN8E/PTAsNLnJ5yH9/sYmVtpNyk0midJOSs9Wtt96KgwcPwm63Y+3atZg1a1YqHjYtKIqC73uHRC1ddUBt3421EDcZQo3y3+ENWoJ3YE0HiqIEbJzoG+HPTAtpL9NiVDt13thcD0D7/YaIKDbpdYk9SJ0/oQyjS3PQbnfiL6sPAAA67NFbnpMl1Ch/WYSbjkEL4CsgPtLSnZQR/kTxkH9/a/d7ptEOZD0LEfkwaEkBg0HBrd5syzMr96PT7hyQmhb/TMtOb6Yl3Wa0SJV+rdq+QlxmWig15DwWuVHhqRrNFiGi+DBoSZGLJpdjeFEWTnT14oW1tSnrHgL6FuI6XW7saUzPGS2S2kHU2p3UlmeiWPhvwVCaa1VnBxHRwGLQkiImowG3eLeb//OHe9VR8qlYHpKj/BvaetDrcuNAcxccTjeyLMawA7YGmv/2AyzEpVTzHwM/rTqfLcdEaYJBSwotnFaJyvxMNPu1PmenYM+f4mwrzEYFbuEJXGQ9y+ghuZpOp+wPFuLSQPLfJXighsoRUV8MWlLIYjLgu2fWqP/PsZpSEjQYDIq63HKkpcfXOZRGOzsHk0FL3fFuOJyevXwK+rEHE1E8AjMtDFqI0gWDlhS7bEYVSnI9WxWkYmlIqvBre96ltjun77AsWVMgNx80GxVkWzgng1JDBs1Gg4LJlXkDfDREJDFoSbEMsxE3z/dkW1KZOfDfz0dtd07TIlzA83vy3906P8vCugJKmdGlObhyVjUWXzgOmQyWidJG6i71SXX17GFo6XZg1oiilD2mbCHe19iJA82dAIAxZem7PAR4skNy6wOO8KdUUhQFv7l08kAfBhEFYdAyADLMRvzkgnEpfUxZ0/LRrka4hScIKMlJ7x21y/MyseVwG4D03SyRiIhSh8tDJwlZ03Ks3Q7AMwk33ZdbZHYIYKaFiIgYtJw0/AMAIL3rWST/AV+c0UJERAxaThLlQUHLmDTdc8hfhd8xc3mIiIgYtJwkcqwmdedaABini6DFP9PC5SEiopMdg5aTiP9yy2gdLA9VBNS0MNNCRHSyY9ByEpF1LRV5GbBlpH/mojQ3A0bvxGCO8CciIgYtJxGZuRirg6UhwDONVAZacoowERGdvBi0nEROG1EIAJg/umSAjyR2d18yET84dzROGZo/0IdCREQDTBFCiIE+iHDa2tqQl5eH1tZW2Gzpu0+OnjR32FGU5kPliIhI37Q6fzPTcpJhwEJERHrFoIWIiIh0gUELERER6QKDFiIiItIFBi1ERESkCwxaiIiISBcYtBAREZEuMGghIiIiXWDQQkRERLrAoIWIiIh0gUELERER6QKDFiIiItIFBi1ERESkCwxaiIiISBcYtBAREZEuaBa0/PrXv8acOXOQlZWF/Px8rR6GiIiIThKaBS0OhwOXXXYZvve972n1EERERHQSMWl1x3fffTcAYOnSpVo9BBEREZ1ENAtaEmG322G329X/t7W1DeDREBERUTpJq0Lc+++/H3l5eepHVVXVQB8SERERpYm4gpaf//znUBQl4seOHTsSPpjFixejtbVV/airq0v4voiIiGhwiWt56Mc//jGuvfbaiLepqalJ+GCsViusVmvC309ERESDV1xBS0lJCUpKSrQ6FiIiIqKwNCvEra2txfHjx1FbWwuXy4VNmzYBAEaNGoWcnBytHpaIiIgGKc2CljvuuAPPPfec+v9p06YBAD744AOcddZZWj0sERERDVKKEEIM9EGE09bWhry8PLS2tsJmsw304RAREVEMtDp/p1XLMxEREVE4DFqIiIhIFxi0EBERkS4waCEiIiJdYNBCREREusCghYiIiHSBQQsRERHpAoMWIiIi0gUGLURERKQLDFqIiIhIFxi0EBERkS4waCEiIiJdYNBCREREusCghYiIiHSBQQsRERHpAoMWIiIi0gUGLURERKQLDFqIiIhIFxi0EBERkS4waCEiIiJdYNBCREREusCghYiIiHSBQQsRERHpAoMWIiIi0gUGLURERKQLDFqIiIhIFxi0EBERkS4waCEiIiJdYNBCREREusCghYiIiHSBQQsRERHpAoMWIiIi0gUGLURERKQLDFqIiIhIFzQLWg4cOIAbbrgBI0aMQGZmJkaOHIk777wTDodDq4ckIiKiQcyk1R3v2LEDbrcbTzzxBEaNGoUtW7bgpptuQmdnJx566CGtHpaIiIgGKUUIIVL1YA8++CAef/xx7Nu3L6bbt7W1IS8vD62trbDZbBofHRERESWDVudvzTItobS2tqKwsDDs1+12O+x2u/r/tra2VBwWERER6UDKCnH37NmDRx55BN/5znfC3ub+++9HXl6e+lFVVZWqwyMiIqI0F3fQ8vOf/xyKokT82LFjR8D3HD58GF/60pdw2WWX4aabbgp734sXL0Zra6v6UVdXF/9PRERERINS3DUtjY2NaG5ujnibmpoaWCwWAMCRI0dw1lln4fTTT8fSpUthMMQeJ7GmhYiISH/SpqalpKQEJSUlMd328OHDOPvsszF9+nQsWbIkroCFiIiIyJ9mhbiHDx/GWWedhWHDhuGhhx5CY2Oj+rWysjKtHpaIiIgGKc2ClnfeeQd79uzBnj17MHTo0ICvpbDLmoiIiAYJzdZrrr32WgghQn4QERERxYtFJkRERKQLDFqIiIhIFxi0EBERkS4waCEiIiJdYNBCREREusCghYiIiHQhpbs8x0u2R3O3ZyIiIv2Q5+1kjzlJ66BF7nHE3Z6JiIj0p7m5GXl5eUm7v7QOWgoLCwEAtbW1Sf2hKX5tbW2oqqpCXV0dN69MA3w+0gefi/TB5yJ9tLa2orq6Wj2PJ0taBy1yg8W8vDz+AaYJm83G5yKN8PlIH3wu0gefi/SR7I2SWYhLREREusCghYiIiHQhrYMWq9WKO++8E1ardaAP5aTH5yK98PlIH3wu0gefi/Sh1XOhCG67TERERDqQ1pkWIiIiIolBCxEREekCgxYiIiLSBQYtREREpAsDHrQ8+uijGD58ODIyMjBr1ix8+umnEW//8ssvY9y4ccjIyMDkyZPxxhtvpOhIB794nounnnoK8+fPR0FBAQoKCrBgwYKozx3FJ97XhrRs2TIoioKFCxdqe4AnkXifi5aWFixatAjl5eWwWq0YM2YM36uSJN7n4o9//CPGjh2LzMxMVFVV4Uc/+hF6enpSdLSD10cffYSLL74YFRUVUBQFr732WtTvWbFiBU499VRYrVaMGjUKS5cujf+BxQBatmyZsFgs4tlnnxVbt24VN910k8jPzxcNDQ0hb79q1SphNBrF7373O7Ft2zbxy1/+UpjNZrF58+YUH/ngE+9zceWVV4pHH31UbNy4UWzfvl1ce+21Ii8vTxw6dCjFRz44xft8SPv37xeVlZVi/vz54pJLLknNwQ5y8T4XdrtdzJgxQ3z5y18WK1euFPv37xcrVqwQmzZtSvGRDz7xPhfPP/+8sFqt4vnnnxf79+8Xb7/9tigvLxc/+tGPUnzkg88bb7whfvGLX4hXX31VABDLly+PePt9+/aJrKwscfvtt4tt27aJRx55RBiNRvHWW2/F9bgDGrTMnDlTLFq0SP2/y+USFRUV4v777w95+29+85vioosuCvjcrFmzxHe+8x1Nj/NkEO9zEczpdIrc3Fzx3HPPaXWIJ5VEng+n0ynmzJkjnn76aXHNNdcwaEmSeJ+Lxx9/XNTU1AiHw5GqQzxpxPtcLFq0SJxzzjkBn7v99tvF3LlzNT3Ok00sQctPf/pTMXHixIDPXX755eKCCy6I67EGbHnI4XDgs88+w4IFC9TPGQwGLFiwAKtXrw75PatXrw64PQBccMEFYW9PsUnkuQjW1dWF3t7epG+OdTJK9Pm45557UFpaihtuuCEVh3lSSOS5+Oc//4nZs2dj0aJFGDJkCCZNmoTf/OY3cLlcqTrsQSmR52LOnDn47LPP1CWkffv24Y033sCXv/zllBwz+STr/D1gGyY2NTXB5XJhyJAhAZ8fMmQIduzYEfJ76uvrQ96+vr5es+M8GSTyXAT72c9+hoqKij5/lBS/RJ6PlStX4plnnsGmTZtScIQnj0Sei3379uH999/HVVddhTfeeAN79uzBLbfcgt7eXtx5552pOOxBKZHn4sorr0RTUxPmzZsHIQScTie++93v4r//+79TccjkJ9z5u62tDd3d3cjMzIzpfga8EJf074EHHsCyZcuwfPlyZGRkDPThnHTa29tx9dVX46mnnkJxcfFAH85Jz+12o7S0FE8++SSmT5+Oyy+/HL/4xS/w5z//eaAP7aSzYsUK/OY3v8Fjjz2GDRs24NVXX8Xrr7+Oe++9d6APjRI0YJmW4uJiGI1GNDQ0BHy+oaEBZWVlIb+nrKwsrttTbBJ5LqSHHnoIDzzwAN59911MmTJFy8M8acT7fOzduxcHDhzAxRdfrH7O7XYDAEwmE3bu3ImRI0dqe9CDVCKvjfLycpjNZhiNRvVz48ePR319PRwOBywWi6bHPFgl8lz86le/wtVXX40bb7wRADB58mR0dnbi5ptvxi9+8QsYDLxuT5Vw52+bzRZzlgUYwEyLxWLB9OnT8d5776mfc7vdeO+99zB79uyQ3zN79uyA2wPAO++8E/b2FJtEngsA+N3vfod7770Xb731FmbMmJGKQz0pxPt8jBs3Dps3b8amTZvUj69+9as4++yzsWnTJlRVVaXy8AeVRF4bc+fOxZ49e9TAEQB27dqF8vJyBiz9kMhz0dXV1ScwkcGk4LZ7KZW083d8NcLJtWzZMmG1WsXSpUvFtm3bxM033yzy8/NFfX29EEKIq6++Wvz85z9Xb79q1SphMpnEQw89JLZv3y7uvPNOtjwnSbzPxQMPPCAsFot45ZVXxNGjR9WP9vb2gfoRBpV4n49g7B5Knnifi9raWpGbmytuvfVWsXPnTvHvf/9blJaWivvuu2+gfoRBI97n4s477xS5ubnixRdfFPv27RP/+c9/xMiRI8U3v/nNgfoRBo329naxceNGsXHjRgFAPPzww2Ljxo3i4MGDQgghfv7zn4urr75avb1sef7JT34itm/fLh599FH9tTwLIcQjjzwiqqurhcViETNnzhRr1qxRv3bmmWeKa665JuD2f/vb38SYMWOExWIREydOFK+//nqKj3jwiue5GDZsmADQ5+POO+9M/YEPUvG+NvwxaEmueJ+LTz75RMyaNUtYrVZRU1Mjfv3rXwun05niox6c4nkuent7xV133SVGjhwpMjIyRFVVlbjlllvEiRMnUn/gg8wHH3wQ8hwgf//XXHONOPPMM/t8z9SpU4XFYhE1NTViyZIlcT+uIgRzZERERJT+WIVEREREusCghYiIiHSBQQsRERHpAoMWIiIi0gUGLURERKQLDFqIiIhIFxi0EBERkS4waCEiIiJdYNBCREREusCghYiIiHSBQQsRERHpAoMWIiIi0oX/D9ofWKlRfItiAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -632,21 +697,64 @@
     "time2, zx, zy, zz = zip(*gyro_clean.measured_data)\n",
     "\n",
     "plt.plot(time1, wx, label='Noisy Gyroscope')\n",
-    "plt.plot(time2, zx, label='Clean Gyroscope')\n",
+    "# plt.plot(time2, zx, label='Clean Gyroscope')\n",
     "plt.legend()\n",
     "plt.show()\n",
     "\n",
     "plt.plot(time1, wy, label='Noisy Gyroscope')\n",
-    "plt.plot(time2, zy, label='Clean Gyroscope')\n",
+    "# plt.plot(time2, zy, label='Clean Gyroscope')\n",
     "plt.legend()\n",
     "plt.show()\n",
     "\n",
     "plt.plot(time1, wz, label='Noisy Gyroscope')\n",
-    "plt.plot(time2, zz, label='Clean Gyroscope')\n",
+    "plt.xlim(0,4)\n",
+    "# plt.plot(time2, zz, label='Clean Gyroscope')\n",
     "plt.legend()\n",
     "plt.show()\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Oe2JiYpSamqrc3FxJUm5urmJjY9W1a1enJj09XeHh4dqwYYNT06NHD0VGRjo1GRkZys/P17Fjx5ya8z+nvKb8cypSWloqj8fj8wAAALBF+FM8ZswYeTweJScnq06dOiorK9Pzzz+vAQMGSJIKCwslSfHx8T7vi4+Pd5YVFhYqLi7OtxEREWrUqJFPTYsWLS5YR/myhg0bqrCw8Cc/pyKTJk3Sc88950+XAQBALeTXEaTFixdrwYIFeuutt/TFF19o/vz5mj59uubPnx+o9lWpsWPHqqSkxHl888031d0kAABwFfLrCNKoUaM0ZswY9evXT5KUkpKir7/+WpMmTdKgQYPkdrslSUVFRUpISHDeV1RUpE6dOkmS3G63Dh8+7LPec+fO6ejRo8773W63ioqKfGrKn1+qpnx5RVwul1wulz9dBgAAtZBfR5BOnjyp8HDft9SpU0der1eS1KJFC7ndbuXk5DjLPR6PNmzYoLS0NElSWlqaiouLlZeX59R8/PHH8nq9Sk1NdWrWrFmjs2fPOjXZ2dlq166dGjZs6NSc/znlNeWfAwAAcNn8mdE9aNAg07RpU7Ns2TJTUFBg3nnnHdO4cWPz1FNPOTWTJ082sbGx5t133zXbtm0zffr0MS1atDCnTp1yajIzM03nzp3Nhg0bzNq1a02bNm1M//79neXFxcUmPj7eDBw40OzYscMsWrTI1K9f37z22mtOzbp160xERISZPn262b17txk/frypW7eu2b59e6X7w1VsAADUPMHYf/sVkDwej3nsscdMs2bNTFRUlGnZsqV5+umnfS7H93q95tlnnzXx8fHG5XKZnj17mvz8fJ/1HDlyxPTv399ce+21Jjo62jz44IPm+PHjPjVbt241t912m3G5XKZp06Zm8uTJF7Rn8eLFpm3btiYyMtJ06NDBLF++3J/uEJAAAKiBgrH/DjPmvNtg1zIej0cxMTEqKSlRdHR0dTcHAABUQjD23/xbbAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWvwJS8+bNFRYWdsFjxIgRkqTbb7/9gmWPPvqozzoOHjyorKws1a9fX3FxcRo1apTOnTvnU7N69WrddNNNcrlcat26tebNm3dBW1555RU1b95cUVFRSk1N1caNG/3sOgAAQMX8CkibNm3SoUOHnEd2drYk6d5773Vqhg4d6lMzdepUZ1lZWZmysrJ05swZrV+/XvPnz9e8efM0btw4p6agoEBZWVm64447tGXLFj3++ON6+OGHtWrVKqfm7bff1siRIzV+/Hh98cUXuvHGG5WRkaHDhw9f9hcBAABQLswYYy73zY8//riWLVumvXv3KiwsTLfffrs6deqkl156qcL6Dz74QP/yL/+i77//XvHx8ZKkWbNmafTo0frHP/6hyMhIjR49WsuXL9eOHTuc9/Xr10/FxcVauXKlJCk1NVX//M//rJdfflmS5PV6lZiYqN///vcaM2ZMpdvv8XgUExOjkpISRUdHX+a3AAAAgikY++/LnoN05swZvfnmm3rooYcUFhbmvL5gwQI1btxYN9xwg8aOHauTJ086y3Jzc5WSkuKEI0nKyMiQx+PRzp07nZr09HSfz8rIyFBubq7zuXl5eT414eHhSk9Pd2ouprS0VB6Px+cBAABgi7jcNy5dulTFxcUaPHiw89oDDzygpKQkNWnSRNu2bdPo0aOVn5+vd955R5JUWFjoE44kOc8LCwt/ssbj8ejUqVM6duyYysrKKqzZs2fPT7Z50qRJeu655y6rvwAAoPa47ID0+uuvq3fv3mrSpInz2rBhw5z/T0lJUUJCgnr27Kn9+/erVatWV9bSKjB27FiNHDnSee7xeJSYmFiNLQIAAFejywpIX3/9tT766CPnyNDFpKamSpL27dunVq1aye12X3C1WVFRkSTJ7XY7/y1/7fya6Oho1atXT3Xq1FGdOnUqrClfx8W4XC65XK5LdxAAANRqlzUHae7cuYqLi1NWVtZP1m3ZskWSlJCQIElKS0vT9u3bfa42y87OVnR0tNq3b+/U5OTk+KwnOztbaWlpkqTIyEh16dLFp8br9SonJ8epAQAAuBJ+BySv16u5c+dq0KBBioj4vwNQ+/fv18SJE5WXl6cDBw7ovffe07/+67+qR48e6tixoySpV69eat++vQYOHKitW7dq1apVeuaZZzRixAjnyM6jjz6qr776Sk899ZT27NmjV199VYsXL9Yf//hH57NGjhypOXPmaP78+dq9e7eGDx+uH374QQ8++OCVfh8AAACS8dOqVauMJJOfn+/z+sGDB02PHj1Mo0aNjMvlMq1btzajRo0yJSUlPnUHDhwwvXv3NvXq1TONGzc2TzzxhDl79qxPzSeffGI6depkIiMjTcuWLc3cuXMvaMeMGTNMs2bNTGRkpOnWrZv57LPP/O2KKSkpMZIuaCMAALh6BWP/fUX3QarpuA8SAAA1z1V9HyQAAIBQRUACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwOJXQGrevLnCwsIueIwYMUKSdPr0aY0YMULXXXedrr32Wv3qV79SUVGRzzoOHjyorKws1a9fX3FxcRo1apTOnTvnU7N69WrddNNNcrlcat26tebNm3dBW1555RU1b95cUVFRSk1N1caNG/3sOgAAQMX8CkibNm3SoUOHnEd2drYk6d5775Uk/fGPf9T777+vJUuW6NNPP9X333+ve+65x3l/WVmZsrKydObMGa1fv17z58/XvHnzNG7cOKemoKBAWVlZuuOOO7RlyxY9/vjjevjhh7Vq1Sqn5u2339bIkSM1fvx4ffHFF7rxxhuVkZGhw4cPX9GXAQAAIEkyV+Cxxx4zrVq1Ml6v1xQXF5u6deuaJUuWOMt3795tJJnc3FxjjDErVqww4eHhprCw0KmZOXOmiY6ONqWlpcYYY5566inToUMHn8+5//77TUZGhvO8W7duZsSIEc7zsrIy06RJEzNp0iS/2l9SUmIkmZKSEr/eBwAAqk8w9t+XPQfpzJkzevPNN/XQQw8pLCxMeXl5Onv2rNLT052a5ORkNWvWTLm5uZKk3NxcpaSkKD4+3qnJyMiQx+PRzp07nZrz11FeU76OM2fOKC8vz6cmPDxc6enpTg0AAMCViLjcNy5dulTFxcUaPHiwJKmwsFCRkZGKjY31qYuPj1dhYaFTc344Kl9evuynajwej06dOqVjx46prKyswpo9e/b8ZJtLS0tVWlrqPPd4PJXrLAAAqFUu+wjS66+/rt69e6tJkyZV2Z6AmjRpkmJiYpxHYmJidTcJAABchS4rIH399df66KOP9PDDDzuvud1unTlzRsXFxT61RUVFcrvdTo19VVv580vVREdHq169emrcuLHq1KlTYU35Oi5m7NixKikpcR7ffPNN5TsNAABqjcsKSHPnzlVcXJyysrKc17p06aK6desqJyfHeS0/P18HDx5UWlqaJCktLU3bt2/3udosOztb0dHRat++vVNz/jrKa8rXERkZqS5duvjUeL1e5eTkODUX43K5FB0d7fMAAACw+T0Hyev1au7cuRo0aJAiIv7v7TExMRoyZIhGjhypRo0aKTo6Wr///e+Vlpamm2++WZLUq1cvtW/fXgMHDtTUqVNVWFioZ555RiNGjJDL5ZIkPfroo3r55Zf11FNP6aGHHtLHH3+sxYsXa/ny5c5njRw5UoMGDVLXrl3VrVs3vfTSS/rhhx/04IMPXun3AQAA4P9l/qtWrTKSTH5+/gXLTp06ZX7729+ahg0bmvr165tf/vKX5tChQz41Bw4cML179zb16tUzjRs3Nk888YQ5e/asT80nn3xiOnXqZCIjI03Lli3N3LlzL/isGTNmmGbNmpnIyEjTrVs389lnn/nbFS7zBwCgBgrG/jvMGGOqOaNVG4/Ho5iYGJWUlHC6DQCAGiIY+2/+LTYAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADA4ndA+u677/Sb3/xG1113nerVq6eUlBR9/vnnzvLBgwcrLCzM55GZmemzjqNHj2rAgAGKjo5WbGyshgwZohMnTvjUbNu2Td27d1dUVJQSExM1derUC9qyZMkSJScnKyoqSikpKVqxYoW/3QEAALiAXwHp2LFjuvXWW1W3bl198MEH2rVrl1588UU1bNjQpy4zM1OHDh1yHgsXLvRZPmDAAO3cuVPZ2dlatmyZ1qxZo2HDhjnLPR6PevXqpaSkJOXl5WnatGmaMGGCZs+e7dSsX79e/fv315AhQ7R582b17dtXffv21Y4dOy7newAAAHCEGWNMZYvHjBmjdevW6e9///tFawYPHqzi4mItXbq0wuW7d+9W+/bttWnTJnXt2lWStHLlSt1555369ttv1aRJE82cOVNPP/20CgsLFRkZ6Xz20qVLtWfPHknS/fffrx9++EHLli1z1n3zzTerU6dOmjVrVqX64/F4FBMTo5KSEkVHR1fqPQAAoHoFY//t1xGk9957T127dtW9996ruLg4de7cWXPmzLmgbvXq1YqLi1O7du00fPhwHTlyxFmWm5ur2NhYJxxJUnp6usLDw7VhwwanpkePHk44kqSMjAzl5+fr2LFjTk16errP52ZkZCg3N/ei7S8tLZXH4/F5AAAA2PwKSF999ZVmzpypNm3aaNWqVRo+fLj+8Ic/aP78+U5NZmam3njjDeXk5GjKlCn69NNP1bt3b5WVlUmSCgsLFRcX57PeiIgINWrUSIWFhU5NfHy8T03580vVlC+vyKRJkxQTE+M8EhMT/ek+AACoJSL8KfZ6veratateeOEFSVLnzp21Y8cOzZo1S4MGDZIk9evXz6lPSUlRx44d1apVK61evVo9e/aswqb7b+zYsRo5cqTz3OPxEJIAAMAF/DqClJCQoPbt2/u8dv311+vgwYMXfU/Lli3VuHFj7du3T5Lkdrt1+PBhn5pz587p6NGjcrvdTk1RUZFPTfnzS9WUL6+Iy+VSdHS0zwMAAMDmV0C69dZblZ+f7/Pal19+qaSkpIu+59tvv9WRI0eUkJAgSUpLS1NxcbHy8vKcmo8//lher1epqalOzZo1a3T27FmnJjs7W+3atXOumEtLS1NOTo7PZ2VnZystLc2fLgEAAFzI+GHjxo0mIiLCPP/882bv3r1mwYIFpn79+ubNN980xhhz/Phx8+STT5rc3FxTUFBgPvroI3PTTTeZNm3amNOnTzvryczMNJ07dzYbNmwwa9euNW3atDH9+/d3lhcXF5v4+HgzcOBAs2PHDrNo0SJTv35989prrzk169atMxEREWb69Olm9+7dZvz48aZu3bpm+/btle5PSUmJkWRKSkr8+RoAAEA1Csb+26+AZIwx77//vrnhhhuMy+UyycnJZvbs2c6ykydPml69epmf/exnpm7duiYpKckMHTrUFBYW+qzjyJEjpn///ubaa6810dHR5sEHHzTHjx/3qdm6dau57bbbjMvlMk2bNjWTJ0++oC2LFy82bdu2NZGRkaZDhw5m+fLlfvWFgAQAQM0TjP23X/dBCjXcBwkAgJrnqrsPEgAAQG1AQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADA4ndA+u677/Sb3/xG1113nerVq6eUlBR9/vnnznJjjMaNG6eEhATVq1dP6enp2rt3r886jh49qgEDBig6OlqxsbEaMmSITpw44VOzbds2de/eXVFRUUpMTNTUqVMvaMuSJUuUnJysqKgopaSkaMWKFf52BwAA4AJ+BaRjx47p1ltvVd26dfXBBx9o165devHFF9WwYUOnZurUqfrLX/6iWbNmacOGDbrmmmuUkZGh06dPOzUDBgzQzp07lZ2drWXLlmnNmjUaNmyYs9zj8ahXr15KSkpSXl6epk2bpgkTJmj27NlOzfr169W/f38NGTJEmzdvVt++fdW3b1/t2LHjSr4PAAAAyfhh9OjR5rbbbrvocq/Xa9xut5k2bZrzWnFxsXG5XGbhwoXGGGN27dplJJlNmzY5NR988IEJCwsz3333nTHGmFdffdU0bNjQlJaW+nx2u3btnOf33XefycrK8vn81NRU88gjj1S6PyUlJUaSKSkpqfR7AABA9QrG/tuvI0jvvfeeunbtqnvvvVdxcXHq3Lmz5syZ4ywvKChQYWGh0tPTnddiYmKUmpqq3NxcSVJubq5iY2PVtWtXpyY9PV3h4eHasGGDU9OjRw9FRkY6NRkZGcrPz9exY8ecmvM/p7ym/HMqUlpaKo/H4/MAAACw+RWQvvrqK82cOVNt2rTRqlWrNHz4cP3hD3/Q/PnzJUmFhYWSpPj4eJ/3xcfHO8sKCwsVFxfnszwiIkKNGjXyqaloHed/xsVqypdXZNKkSYqJiXEeiYmJ/nQfAADUEn4FJK/Xq5tuukkvvPCCOnfurGHDhmno0KGaNWtWoNpXpcaOHauSkhLn8c0331R3kwAAwFXIr4CUkJCg9u3b+7x2/fXX6+DBg5Ikt9stSSoqKvKpKSoqcpa53W4dPnzYZ/m5c+d09OhRn5qK1nH+Z1yspnx5RVwul6Kjo30eAAAANr8C0q233qr8/Hyf17788kslJSVJklq0aCG3262cnBxnucfj0YYNG5SWliZJSktLU3FxsfLy8pyajz/+WF6vV6mpqU7NmjVrdPbsWacmOztb7dq1c66YS0tL8/mc8pryzwEAALhs/szo3rhxo4mIiDDPP/+82bt3r1mwYIGpX7++efPNN52ayZMnm9jYWPPuu++abdu2mT59+pgWLVqYU6dOOTWZmZmmc+fOZsOGDWbt2rWmTZs2pn///s7y4uJiEx8fbwYOHGh27NhhFi1aZOrXr29ee+01p2bdunUmIiLCTJ8+3ezevduMHz/e1K1b12zfvr3S/eEqNgAAap5g7L/9CkjGGPP++++bG264wbhcLpOcnGxmz57ts9zr9Zpnn33WxMfHG5fLZXr27Gny8/N9ao4cOWL69+9vrr32WhMdHW0efPBBc/z4cZ+arVu3mttuu824XC7TtGlTM3ny5AvasnjxYtO2bVsTGRlpOnToYJYvX+5XXwhIAADUPMHYf4cZY0z1HsOqPh6PRzExMSopKWE+EgAANUQw9t/8W2wAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWCKquwHVyRgjSfJ4PNXcEgAAUFnl++3y/Xgg1OqAdOTIEUlSYmJiNbcEAAD468iRI4qJiQnIumt1QGrUqJEk6eDBgwH7gq9GHo9HiYmJ+uabbxQdHV3dzQka+k2/awP6Tb9rg5KSEjVr1szZjwdCrQ5I4eE/TsGKiYmpVT9Y5aKjo+l3LUK/axf6XbvU1n6X78cDsu6ArRkAAKCGIiABAABYanVAcrlcGj9+vFwuV3U3JajoN/2uDeg3/a4N6Hfg+h1mAnmNHAAAQA1Uq48gAQAAVISABAAAYCEgAQAAWAhIAAAAlpAKSK+88oqaN2+uqKgopaamauPGjT9Zv2TJEiUnJysqKkopKSlasWKFz3JjjMaNG6eEhATVq1dP6enp2rt3byC7cFmqut+DBw9WWFiYzyMzMzOQXbgs/vR7586d+tWvfqXmzZsrLCxML7300hWvs7pUdb8nTJhwwXgnJycHsAeXx59+z5kzR927d1fDhg3VsGFDpaenX1Afitt3Zfoditv3O++8o65duyo2NlbXXHONOnXqpP/6r//yqQnF8a5Mv0NxvM+3aNEihYWFqW/fvj6vV8l4mxCxaNEiExkZaf7617+anTt3mqFDh5rY2FhTVFRUYf26detMnTp1zNSpU82uXbvMM888Y+rWrWu2b9/u1EyePNnExMSYpUuXmq1bt5q7777btGjRwpw6dSpY3bqkQPR70KBBJjMz0xw6dMh5HD16NFhdqhR/+71x40bz5JNPmoULFxq3223+4z/+44rXWR0C0e/x48ebDh06+Iz3P/7xjwD3xD/+9vuBBx4wr7zyitm8ebPZvXu3GTx4sImJiTHffvutUxOK23dl+h2K2/cnn3xi3nnnHbNr1y6zb98+89JLL5k6deqYlStXOjWhON6V6Xcojne5goIC07RpU9O9e3fTp08fn2VVMd4hE5C6detmRowY4TwvKyszTZo0MZMmTaqw/r777jNZWVk+r6WmpppHHnnEGGOM1+s1brfbTJs2zVleXFxsXC6XWbhwYQB6cHmqut/G/LhB2T9sVxt/+32+pKSkCoPClawzWALR7/Hjx5sbb7yxCltZ9a50bM6dO2caNGhg5s+fb4wJ3e3bZvfbmNDfvst17tzZPPPMM8aY2jPexvj225jQHe9z586ZW265xfznf/7nBX2sqvEOiVNsZ86cUV5entLT053XwsPDlZ6ertzc3Arfk5ub61MvSRkZGU59QUGBCgsLfWpiYmKUmpp60XUGWyD6XW716tWKi4tTu3btNHz4cB05cqTqO3CZLqff1bHOqhbINu7du1dNmjRRy5YtNWDAAB08ePBKm1tlqqLfJ0+e1NmzZ51/2DJUt2+b3e9yobx9G2OUk5Oj/Px89ejRQ1LtGO+K+l0uFMf73//93xUXF6chQ4ZcsKyqxjsk/rHa//mf/1FZWZni4+N9Xo+Pj9eePXsqfE9hYWGF9YWFhc7y8tcuVlPdAtFvScrMzNQ999yjFi1aaP/+/fq3f/s39e7dW7m5uapTp07Vd8RPl9Pv6lhnVQtUG1NTUzVv3jy1a9dOhw4d0nPPPafu3btrx44datCgwZU2+4pVRb9Hjx6tJk2aOL8wQ3X7ttn9lkJ3+y4pKVHTpk1VWlqqOnXq6NVXX9UvfvELSaE93j/Vbyk0x3vt2rV6/fXXtWXLlgqXV9V4h0RAQtXq16+f8/8pKSnq2LGjWrVqpdWrV6tnz57V2DIEQu/evZ3/79ixo1JTU5WUlKTFixdX+NdZTTN58mQtWrRIq1evVlRUVHU3J2gu1u9Q3b4bNGigLVu26MSJE8rJydHIkSPVsmVL3X777dXdtIC6VL9DbbyPHz+ugQMHas6cOWrcuHFAPyskTrE1btxYderUUVFRkc/rRUVFcrvdFb7H7Xb/ZH35f/1ZZ7AFot8VadmypRo3bqx9+/ZdeaOrwOX0uzrWWdWC1cbY2Fi1bds2JMZ7+vTpmjx5sj788EN17NjReT1Ut+9yF+t3RUJl+w4PD1fr1q3VqVMnPfHEE/r1r3+tSZMmSQrt8f6pflekpo/3/v37deDAAd11112KiIhQRESE3njjDb333nuKiIjQ/v37q2y8QyIgRUZGqkuXLsrJyXFe83q9ysnJUVpaWoXvSUtL86mXpOzsbKe+RYsWcrvdPjUej0cbNmy46DqDLRD9rsi3336rI0eOKCEhoWoafoUup9/Vsc6qFqw2njhxQvv376/x4z116lRNnDhRK1euVNeuXX2Wher2Lf10vysSqtu31+tVaWmppNAeb9v5/a5ITR/v5ORkbd++XVu2bHEed999t+644w5t2bJFiYmJVTfe/sw0v5otWrTIuFwuM2/ePLNr1y4zbNgwExsbawoLC40xxgwcONCMGTPGqV+3bp2JiIgw06dPN7t37zbjx4+v8DL/2NhY8+6775pt27aZPn36XJWXhVZlv48fP26efPJJk5ubawoKCsxHH31kbrrpJtOmTRtz+vTpauljRfztd2lpqdm8ebPZvHmzSUhIME8++aTZvHmz2bt3b6XXeTUIRL+feOIJs3r1alNQUGDWrVtn0tPTTePGjc3hw4eD3r+L8bffkydPNpGRkeZvf/ubz+XNx48f96kJte37Uv0O1e37hRdeMB9++KHZv3+/2bVrl5k+fbqJiIgwc+bMcWpCcbwv1e9QHW9bRVfqVcV4h0xAMsaYGTNmmGbNmpnIyEjTrVs389lnnznLfv7zn5tBgwb51C9evNi0bdvWREZGmg4dOpjly5f7LPd6vebZZ5818fHxxuVymZ49e5r8/PxgdMUvVdnvkydPml69epmf/exnpm7duiYpKckMHTr0qgoJ5fzpd0FBgZF0wePnP/95pdd5tajqft9///0mISHBREZGmqZNm5r777/f7Nu3L4g9qhx/+p2UlFRhv8ePH+/UhOL2fal+h+r2/fTTT5vWrVubqKgo07BhQ5OWlmYWLVrks75QHO9L9TtUx9tWUUCqivEOM8aYyh9vAgAACH0hMQcJAACgKhGQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwPL/AUZA44mqcjdbAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "t,p = zip(*barometer_clean.measured_data)\n",
+    "plt.plot(t,p)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_flight.pressure()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

From de2d8bd46332c1ffaff890e8b07bcdad44b0729d Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 11:46:46 +0200
Subject: [PATCH 052/120] MNT: remove .type attribute

---
 rocketpy/prints/sensors_prints.py | 4 ++--
 rocketpy/sensors/accelerometer.py | 1 -
 rocketpy/sensors/gyroscope.py     | 1 -
 3 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 95e3458c0..40d66d2bb 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -12,7 +12,7 @@
 class _SensorsPrints(ABC):
     def __init__(self, sensor):
         self.sensor = sensor
-        self.units = UNITS[sensor.type]
+        self.units = UNITS[sensor.__class__.__name__]
 
     def _print_aligned(self, label, value):
         """Prints a label and a value aligned vertically."""
@@ -22,7 +22,7 @@ def identity(self):
         """Prints the identity of the sensor."""
         print("Identification of the Sensor:\n")
         self._print_aligned("Name:", self.sensor.name)
-        self._print_aligned("Type:", self.sensor.type)
+        self._print_aligned("Type:", self.sensor.__class__.__name__)
 
     def orientation(self):
         """Prints the orientation of the sensor."""
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index b5e447085..256c1efe5 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -191,7 +191,6 @@ def __init__(
             cross_axis_sensitivity=cross_axis_sensitivity,
             name=name,
         )
-        self.type = "Accelerometer"
         self.consider_gravity = consider_gravity
         self.prints = _AccelerometerPrints(self)
 
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 6ba2b945d..466c2d446 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -191,7 +191,6 @@ def __init__(
             cross_axis_sensitivity=cross_axis_sensitivity,
             name=name,
         )
-        self.type = "Gyroscope"
         self.acceleration_sensitivity = self._vectorize_input(
             acceleration_sensitivity, "acceleration_sensitivity"
         )

From fec672512bba1b820bf6fcd606eedb56d09dc609 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 13:21:17 +0200
Subject: [PATCH 053/120] DOC: fix units of transformation_euler_anges

---
 rocketpy/mathutils/vector_matrix.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 9c3efe616..f355a8d09 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1037,11 +1037,11 @@ def transformation_euler_angles(roll, pitch, yaw):
         Parameters
         ----------
         roll : float
-            The roll angle in radians.
+            The roll angle in degrees.
         pitch : float
-            The pitch angle in radians.
+            The pitch angle in degrees.
         yaw : float
-            The yaw angle in radians.
+            The yaw angle in degrees.
 
         Returns
         -------

From ce2a63d7325c0272a2275ad97d8dde19ba4c8f5d Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 13:44:05 +0200
Subject: [PATCH 054/120] DOC: add examples to transformation_euler_angles

---
 rocketpy/mathutils/vector_matrix.py | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index f355a8d09..e5613e4dd 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1047,6 +1047,20 @@ def transformation_euler_angles(roll, pitch, yaw):
         -------
         Matrix
             The transformation matrix from frame B to frame A.
+
+        Examples
+        --------
+        >>> M = Matrix.transformation_euler_angles(0, 0, 0)
+        >>> M
+        Matrix([1.0, 0.0, 0.0],
+               [0.0, 1.0, 0.0],
+               [0.0, 0.0, 1.0])
+
+        >>> M = Matrix.transformation_euler_angles(90, 0, 0)
+        >>> M
+        Matrix([-2.220446049250313e-16, -1.0000000000000002, 0.0],
+               [1.0000000000000002, -2.220446049250313e-16, 0.0],
+               [0.0, 0.0, 1.0])
         """
         return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))
 

From f2656c5d0bc77f193812bcea10394e4ff226de4a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 13:44:57 +0200
Subject: [PATCH 055/120] DOC: mention Euler parameters in docs

---
 rocketpy/tools.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index edea8aada..9941d3793 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -468,7 +468,8 @@ def quaternions_to_nutation(e1, e2):
 
 
 def euler_to_quaternions(roll, pitch, yaw):
-    """Calculates the quaternions from the Euler angles in 3-2-1 sequence.
+    """Calculates the quaternions (Euler parameters) from the Euler angles in
+    3-2-1 sequence.
 
     Parameters
     ----------

From 41bf9e9d5e34aebd252000dda056827f2c5d1f04 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:04:47 +0200
Subject: [PATCH 056/120] TST: test_euler_to_quaternions

---
 tests/unit/test_tools.py | 17 +++++++++++++++++
 1 file changed, 17 insertions(+)
 create mode 100644 tests/unit/test_tools.py

diff --git a/tests/unit/test_tools.py b/tests/unit/test_tools.py
new file mode 100644
index 000000000..e1692720b
--- /dev/null
+++ b/tests/unit/test_tools.py
@@ -0,0 +1,17 @@
+import numpy as np
+import pytest
+
+from rocketpy.tools import euler_to_quaternions
+
+
+def test_euler_to_quaternions():
+    q0, q1, q2, q3 = euler_to_quaternions(0, 0, 0)
+    assert q0 == 1
+    assert q1 == 0
+    assert q2 == 0
+    assert q3 == 0
+    q0, q1, q2, q3 = euler_to_quaternions(90, 90, 90)
+    assert round(q0, 7) == 0.7071068
+    assert round(q1, 7) == 0
+    assert round(q2, 7) == 0.7071068
+    assert round(q3, 7) == 0

From 11873cd6db9340dbd5ebab35725da075eb21158a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:06:09 +0200
Subject: [PATCH 057/120] TST: fix doc tests

---
 rocketpy/mathutils/vector_matrix.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index e5613e4dd..14ea9ba54 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1058,8 +1058,8 @@ def transformation_euler_angles(roll, pitch, yaw):
 
         >>> M = Matrix.transformation_euler_angles(90, 0, 0)
         >>> M
-        Matrix([-2.220446049250313e-16, -1.0000000000000002, 0.0],
-               [1.0000000000000002, -2.220446049250313e-16, 0.0],
+        Matrix([-2.220446049250313e-16, -1, 0.0],
+               [1, -2.220446049250313e-16, 0.0],
                [0.0, 0.0, 1.0])
         """
         return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))

From b795031d1fc686afb3455b39682ae0267ead9423 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:07:56 +0200
Subject: [PATCH 058/120] MNT: privatize components attributes and improve docs

---
 rocketpy/rocket/components.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/rocketpy/rocket/components.py b/rocketpy/rocket/components.py
index f97d54cab..66c9f09a7 100644
--- a/rocketpy/rocket/components.py
+++ b/rocketpy/rocket/components.py
@@ -25,8 +25,8 @@ def __init__(self):
 
         # List of components and their positions to avoid extra for loops in
         # simulation time
-        self._component_list = []
-        self._position_list = []
+        self.__component_list = []
+        self.__position_list = []
 
     def __repr__(self):
         """Return a string representation of the Components instance."""
@@ -66,8 +66,8 @@ def add(self, component, position):
         -------
         None
         """
-        self._component_list.append(component)
-        self._position_list.append(position)
+        self.__component_list.append(component)
+        self.__position_list.append(position)
         self._components.append(self.component_tuple(component, position))
 
     def get_by_type(self, component_type):
@@ -115,10 +115,10 @@ def get_components(self):
 
         Returns
         -------
-        list
+        list[Component]
             A list of all the components in the list of components.
         """
-        return self._component_list
+        return self.__component_list
 
     def get_positions(self):
         """Return a list of all the positions of the components in the list of
@@ -130,7 +130,7 @@ def get_positions(self):
             A list of all the positions of the components in the list of
             components.
         """
-        return self._position_list
+        return self.__position_list
 
     def remove(self, component):
         """Remove a component from the list of components. If more than one

From 968f55adf3439b8a3c09a3335400c576aae51704 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:10:14 +0200
Subject: [PATCH 059/120] TST: add index to var names

---
 tests/unit/test_sensors.py | 90 +++++++++++++++++++-------------------
 1 file changed, 46 insertions(+), 44 deletions(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index ebb0c5b60..d98bd8f4a 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -8,7 +8,7 @@
 from rocketpy.tools import euler_to_quaternions
 
 # calisto standard simulation no wind solution index 200
-SOLUTION = [
+SOLUTION_INDEX_200 = [
     3.338513236767685,
     0.02856482783411794,
     50.919436628139216,
@@ -24,7 +24,7 @@
     0.00010697759229808481,
     19.72526891699468,
 ]
-UDOT = [
+U_DOT_INDEX_200 = [
     0.021620542063162787,
     30.468683793837055,
     284.19140267225384,
@@ -78,21 +78,21 @@ def test_ideal_accelerometer_measure(ideal_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
 
     relative_position = Vector([0, 0, 0])
     gravity = 9.81
-    a_I = Vector(UDOT[3:6])
+    a_I = Vector(U_DOT_INDEX_200[3:6])
     omega = Vector(u[10:13])
-    omega_dot = Vector(UDOT[10:13])
+    omega_dot = Vector(U_DOT_INDEX_200[10:13])
     accel = (
         a_I
         + Vector.cross(omega_dot, relative_position)
         + Vector.cross(omega, Vector.cross(omega, relative_position))
     )
     ax, ay, az = Matrix.transformation(u[6:10]) @ accel
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
 
     # check last measurement
     assert len(ideal_accelerometer.measurement) == 3
@@ -101,7 +101,7 @@ def test_ideal_accelerometer_measure(ideal_accelerometer):
 
     # check measured values
     assert len(ideal_accelerometer.measured_data) == 1
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
     assert len(ideal_accelerometer.measured_data) == 2
 
     assert all(isinstance(i, tuple) for i in ideal_accelerometer.measured_data)
@@ -113,8 +113,8 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
     measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     relative_position = Vector(
         [np.random.randint(-1, 1), np.random.randint(-1, 1), np.random.randint(-1, 1)]
     )
@@ -122,7 +122,7 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
     rot = Matrix.transformation(u[6:10])
     ax, ay, az = rot @ Vector(u[10:13])
 
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
 
     # check last measurement
     assert len(ideal_gyroscope.measurement) == 3
@@ -131,7 +131,7 @@ def test_ideal_gyroscope_measure(ideal_gyroscope):
 
     # check measured values
     assert len(ideal_gyroscope.measured_data) == 1
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
     assert len(ideal_gyroscope.measured_data) == 2
 
     assert all(isinstance(i, tuple) for i in ideal_gyroscope.measured_data)
@@ -143,15 +143,15 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
 
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0.4, 0.4, 1])
     gravity = 9.81
-    a_I = Vector(UDOT[3:6]) + Vector([0, 0, -gravity])
+    a_I = Vector(U_DOT_INDEX_200[3:6]) + Vector([0, 0, -gravity])
     omega = Vector(u[10:13])
-    omega_dot = Vector(UDOT[10:13])
+    omega_dot = Vector(U_DOT_INDEX_200[10:13])
     accel = (
         a_I
         + Vector.cross(omega_dot, relative_position)
@@ -177,7 +177,9 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     az += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    noisy_rotated_accelerometer.measure(
+        t, u, U_DOT_INDEX_200, relative_position, gravity
+    )
     assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.5)
 
 
@@ -185,8 +187,8 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
     measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0.4, 0.4, 1])
     gravity = 9.81
@@ -210,7 +212,7 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     wz += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_gyroscope.measure(t, u, UDOT, relative_position, gravity)
+    noisy_rotated_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
     assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.5)
 
 
@@ -218,14 +220,14 @@ def test_quantization_accelerometer(quantized_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0, 0, 0])
     gravity = 9.81
-    a_I = Vector(UDOT[3:6])
+    a_I = Vector(U_DOT_INDEX_200[3:6])
     omega = Vector(u[10:13])
-    omega_dot = Vector(UDOT[10:13])
+    omega_dot = Vector(U_DOT_INDEX_200[10:13])
     accel = (
         a_I
         + Vector.cross(omega_dot, relative_position)
@@ -243,7 +245,7 @@ def test_quantization_accelerometer(quantized_accelerometer):
     az = round(az / 0.4882) * 0.4882
 
     # check last measurement considering noise error bounds
-    quantized_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    quantized_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
     assert quantized_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
 
 
@@ -251,8 +253,8 @@ def test_quantization_gyroscope(quantized_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
     measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0.4, 0.4, 1])
     gravity = 9.81
@@ -268,7 +270,7 @@ def test_quantization_gyroscope(quantized_gyroscope):
     wz = round(wz / 0.4882) * 0.4882
 
     # check last measurement considering noise error bounds
-    quantized_gyroscope.measure(t, u, UDOT, relative_position, gravity)
+    quantized_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
     assert quantized_gyroscope.measurement == approx([wx, wy, wz], abs=1e-10)
 
 
@@ -281,12 +283,12 @@ def test_export_accel_data_csv(ideal_accelerometer):
     flight_calisto_accel_gyro : Flight
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     relative_position = Vector([0, 0, 0])
     gravity = 9.81
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
 
     file_name = "sensors.csv"
 
@@ -330,12 +332,12 @@ def test_export_accel_data_json(ideal_accelerometer):
         Pytest fixture for the flight of the calisto rocket with an ideal
         accelerometer and a gyroscope.
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     relative_position = Vector([0, 0, 0])
     gravity = 9.81
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
-    ideal_accelerometer.measure(t, u, UDOT, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
+    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
 
     file_name = "sensors.json"
 
@@ -379,11 +381,11 @@ def test_export_gyro_data_csv(ideal_gyroscope):
         Pytest fixture for the flight of the calisto rocket with an ideal
         accelerometer and a gyroscope.
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     relative_position = Vector([0, 0, 0])
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
+    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
 
     file_name = "sensors.csv"
 
@@ -426,11 +428,11 @@ def test_export_gyro_data_json(ideal_gyroscope):
     flight_calisto_accel_gyro : Flight
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
+    t = SOLUTION_INDEX_200[0]
+    u = SOLUTION_INDEX_200[1:]
     relative_position = Vector([0, 0, 0])
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
-    ideal_gyroscope.measure(t, u, UDOT, relative_position)
+    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
+    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
 
     file_name = "sensors.json"
 

From d827b8ed55e524a806ba1bbc88c80afd1d8afcb8 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:12:30 +0200
Subject: [PATCH 060/120] MNT: return temp drift directly

---
 rocketpy/sensors/sensors.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 0a8438840..2196b25bc 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -366,6 +366,4 @@ def apply_temperature_drift(self, value):
             Vector([1, 1, 1])
             + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
         )
-        value = value & scale_factor
-
-        return value
+        return value & scale_factor

From 0b0f20175864f150776d2da37caadc1c05e14c2c Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:29:48 +0200
Subject: [PATCH 061/120] ENH: improve export methods

---
 rocketpy/sensors/accelerometer.py | 10 ++++++----
 rocketpy/sensors/gyroscope.py     | 10 ++++++----
 2 files changed, 12 insertions(+), 8 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 256c1efe5..35c501792 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -259,7 +259,9 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        if format == "csv":
+        if format.lower() not in ["json", "csv"]:
+            raise ValueError("Invalid format")
+        if format.lower() == "csv":
             # if sensor has been added multiple times to the simulated rocket
             if isinstance(self.measured_data[0], list):
                 print("Data saved to", end=" ")
@@ -275,7 +277,8 @@ def export_measured_data(self, filename, format="csv"):
                     for t, ax, ay, az in self.measured_data:
                         f.write(f"{t},{ax},{ay},{az}\n")
                 print(f"Data saved to {filename}")
-        elif format == "json":
+            return
+        if format.lower() == "json":
             if isinstance(self.measured_data[0], list):
                 print("Data saved to", end=" ")
                 for i, data in enumerate(self.measured_data):
@@ -298,5 +301,4 @@ def export_measured_data(self, filename, format="csv"):
                 with open(filename, "w") as f:
                     json.dump(dict, f)
                 print(f"Data saved to {filename}")
-        else:
-            raise ValueError("Invalid format")
+            return
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 466c2d446..743b80c21 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -290,7 +290,9 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        if format == "csv":
+        if format.lower() not in ["csv", "json"]:
+            raise ValueError("Invalid format")
+        if format.lower() == "csv":
             # if sensor has been added multiple times to the simulated rocket
             if isinstance(self.measured_data[0], list):
                 print("Data saved to", end=" ")
@@ -306,7 +308,8 @@ def export_measured_data(self, filename, format="csv"):
                     for t, wx, wy, wz in self.measured_data:
                         f.write(f"{t},{wx},{wy},{wz}\n")
                 print(f"Data saved to {filename}")
-        elif format == "json":
+            return
+        if format.lower() == "json":
             if isinstance(self.measured_data[0], list):
                 print("Data saved to", end=" ")
                 for i, data in enumerate(self.measured_data):
@@ -329,5 +332,4 @@ def export_measured_data(self, filename, format="csv"):
                 with open(filename, "w") as f:
                     json.dump(dict, f)
                 print(f"Data saved to {filename}")
-        else:
-            raise ValueError("Invalid format")
+            return

From bad3b0748ef0394f68071c08c753e39af6dbbc5b Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 15:30:04 +0200
Subject: [PATCH 062/120] DOC: typos

---
 rocketpy/rocket/aero_surface.py | 2 +-
 rocketpy/rocket/rocket.py       | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/rocketpy/rocket/aero_surface.py b/rocketpy/rocket/aero_surface.py
index 9649d1bf0..a5ea26638 100644
--- a/rocketpy/rocket/aero_surface.py
+++ b/rocketpy/rocket/aero_surface.py
@@ -1978,7 +1978,7 @@ def __init__(
             Default is False.
         deployment_level : float, optional
             Initial deployment level, ranging from 0 to 1. Deployment level is
-            the fraction of the total airbrake area that is Deployment. Default
+            the fraction of the total airbrake area that is deployed. Default
             is 0.
         name : str, optional
             Name of the air brakes. Default is "AirBrakes".
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index 7e03d2522..c09e7c160 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -1181,10 +1181,10 @@ def add_sensor(self, sensor, position, x_position=0, y_position=0):
             Position, in meters, of the sensor's coordinate system origin
             relative to the user defined rocket coordinate system.
         x_position : int, float, optional
-            Distance in meters by which the CM is to be translated in the x
+            Distance in meters by which the sensor is to be translated in the x
             direction relative to geometrical center line. Default is 0.
         y_position : int, float, optional
-            Distance in meters by which the CM is to be translated in the y
+            Distance in meters by which the sensor is to be translated in the y
             direction relative to geometrical center line. Default is 0.
 
         Returns

From 0891c6c9c5e5ef185192b61ec88176f8e9235599 Mon Sep 17 00:00:00 2001
From: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date: Mon, 6 May 2024 13:27:20 -0300
Subject: [PATCH 063/120] MNT: improve flight init

Co-authored-by: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
---
 tests/unit/test_sensors.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index d98bd8f4a..365c1165c 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -50,12 +50,12 @@ def test_accelerometer_prints(noisy_rotated_accelerometer, quantized_acceleromet
     assert True
 
 
-def test_gyroscope_prints(noisy_rotated_gyroscope, quantized_gyroscope):
+@pytest.mark.parametrize("gyroscope", ["noisy_rotated_gyroscope", "quantized_gyroscope"])
+def test_gyroscope_prints(gyroscope):
     """Test the print methods of the Gyroscope class. Checks if all
     attributes are printed correctly.
     """
-    noisy_rotated_gyroscope.prints.all()
-    quantized_gyroscope.prints.all()
+    gyroscope.prints.all()
     assert True
 
 

From fa1b6a828817d8fb7dceabc051ff2c67c3a70005 Mon Sep 17 00:00:00 2001
From: Lint Action <lint-action@samuelmeuli.com>
Date: Mon, 6 May 2024 16:27:49 +0000
Subject: [PATCH 064/120] Fix code style issues with Black

---
 tests/unit/test_sensors.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 365c1165c..0240365a3 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -50,7 +50,9 @@ def test_accelerometer_prints(noisy_rotated_accelerometer, quantized_acceleromet
     assert True
 
 
-@pytest.mark.parametrize("gyroscope", ["noisy_rotated_gyroscope", "quantized_gyroscope"])
+@pytest.mark.parametrize(
+    "gyroscope", ["noisy_rotated_gyroscope", "quantized_gyroscope"]
+)
 def test_gyroscope_prints(gyroscope):
     """Test the print methods of the Gyroscope class. Checks if all
     attributes are printed correctly.

From 8c71432dc6e87d028bb774d7ea5dd67441a92adb Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 21:03:59 +0200
Subject: [PATCH 065/120] TST: overall improvements on sensor testing

---
 tests/test_sensors.py      |  41 ----
 tests/unit/test_flight.py  |  42 ++++
 tests/unit/test_sensors.py | 401 ++++++++++++-------------------------
 3 files changed, 166 insertions(+), 318 deletions(-)

diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 92960732e..62c872b90 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -60,44 +60,3 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
     flight_wz = np.array(flight_calisto_accel_gyro.w3(time))
     sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
     assert np.allclose(w, sim_w, atol=1e-12)
-
-
-def test_export_sensor_data(flight_calisto_accel_gyro):
-    """Test the export of sensor data.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
-    """
-    flight_calisto_accel_gyro.export_sensor_data("test_sensor_data.json")
-    # read the json and parse as dict
-    filename = "test_sensor_data.json"
-    with open(filename, "r") as f:
-        data = f.read()
-        sensor_data = json.loads(data)
-    # convert list of tuples into list of lists to compare with the json
-    flight_calisto_accel_gyro.sensors[0].measured_data[0] = [
-        list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[0].measured_data[0]
-    ]
-    flight_calisto_accel_gyro.sensors[1].measured_data[1] = [
-        list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[1].measured_data[1]
-    ]
-    flight_calisto_accel_gyro.sensors[2].measured_data = [
-        list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[2].measured_data
-    ]
-    assert (
-        sensor_data["Accelerometer"]["1"]
-        == flight_calisto_accel_gyro.sensors[0].measured_data[0]
-    )
-    assert (
-        sensor_data["Accelerometer"]["2"]
-        == flight_calisto_accel_gyro.sensors[1].measured_data[1]
-    )
-    assert (
-        sensor_data["Gyroscope"] == flight_calisto_accel_gyro.sensors[2].measured_data
-    )
-    os.remove(filename)
diff --git a/tests/unit/test_flight.py b/tests/unit/test_flight.py
index e6ab6b8b8..59368c268 100644
--- a/tests/unit/test_flight.py
+++ b/tests/unit/test_flight.py
@@ -1,3 +1,4 @@
+import json
 import os
 from unittest.mock import patch
 
@@ -286,3 +287,44 @@ def test_out_of_rail_stability_margin(flight_calisto_custom_wind):
         flight_calisto_custom_wind.out_of_rail_time
     )
     assert np.isclose(res, 2.14, atol=0.1)
+
+
+def test_export_sensor_data(flight_calisto_accel_gyro):
+    """Test the export of sensor data.
+
+    Parameters
+    ----------
+    flight_calisto_accel_gyro : Flight
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+    """
+    flight_calisto_accel_gyro.export_sensor_data("test_sensor_data.json")
+    # read the json and parse as dict
+    filename = "test_sensor_data.json"
+    with open(filename, "r") as f:
+        data = f.read()
+        sensor_data = json.loads(data)
+    # convert list of tuples into list of lists to compare with the json
+    flight_calisto_accel_gyro.sensors[0].measured_data[0] = [
+        list(measurement)
+        for measurement in flight_calisto_accel_gyro.sensors[0].measured_data[0]
+    ]
+    flight_calisto_accel_gyro.sensors[1].measured_data[1] = [
+        list(measurement)
+        for measurement in flight_calisto_accel_gyro.sensors[1].measured_data[1]
+    ]
+    flight_calisto_accel_gyro.sensors[2].measured_data = [
+        list(measurement)
+        for measurement in flight_calisto_accel_gyro.sensors[2].measured_data
+    ]
+    assert (
+        sensor_data["Accelerometer"]["1"]
+        == flight_calisto_accel_gyro.sensors[0].measured_data[0]
+    )
+    assert (
+        sensor_data["Accelerometer"]["2"]
+        == flight_calisto_accel_gyro.sensors[1].measured_data[1]
+    )
+    assert (
+        sensor_data["Gyroscope"] == flight_calisto_accel_gyro.sensors[2].measured_data
+    )
+    os.remove(filename)
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 0240365a3..07ed01f65 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -3,13 +3,14 @@
 
 import numpy as np
 from pytest import approx
+import pytest
 
 from rocketpy.mathutils.vector_matrix import Matrix, Vector
 from rocketpy.tools import euler_to_quaternions
 
 # calisto standard simulation no wind solution index 200
-SOLUTION_INDEX_200 = [
-    3.338513236767685,
+TIME = 3.338513236767685
+U = [
     0.02856482783411794,
     50.919436628139216,
     1898.9056294848442,
@@ -24,7 +25,7 @@
     0.00010697759229808481,
     19.72526891699468,
 ]
-U_DOT_INDEX_200 = [
+U_DOT = [
     0.021620542063162787,
     30.468683793837055,
     284.19140267225384,
@@ -39,25 +40,24 @@
     -0.052789015849051935,
     2.276425320359305,
 ]
-
-
-def test_accelerometer_prints(noisy_rotated_accelerometer, quantized_accelerometer):
-    """Test the print methods of the Accelerometer class. Checks if all
-    attributes are printed correctly.
-    """
-    noisy_rotated_accelerometer.prints.all()
-    quantized_accelerometer.prints.all()
-    assert True
+GRAVITY = 9.81
 
 
 @pytest.mark.parametrize(
-    "gyroscope", ["noisy_rotated_gyroscope", "quantized_gyroscope"]
+    "sensor",
+    [
+        "noisy_rotated_accelerometer",
+        "quantized_accelerometer",
+        "noisy_rotated_gyroscope",
+        "quantized_gyroscope",
+    ],
 )
-def test_gyroscope_prints(gyroscope):
-    """Test the print methods of the Gyroscope class. Checks if all
-    attributes are printed correctly.
+def test_sensors_prints(sensor, request):
+    """Test the print methods of the Sensor class. Checks if all attributes are
+    printed correctly.
     """
-    gyroscope.prints.all()
+    sensor = request.getfixturevalue(sensor)
+    sensor.prints.all()
     assert True
 
 
@@ -65,6 +65,7 @@ def test_rotation_matrix(noisy_rotated_accelerometer):
     """Test the rotation_matrix property of the Accelerometer class. Checks if
     the rotation matrix is correctly calculated.
     """
+    # values from external source
     expected_matrix = np.array(
         [
             [0.2500000, -0.0580127, 0.9665064],
@@ -76,84 +77,67 @@ def test_rotation_matrix(noisy_rotated_accelerometer):
     assert np.allclose(expected_matrix, rotation_matrix, atol=1e-8)
 
 
-def test_ideal_accelerometer_measure(ideal_accelerometer):
-    """Test the measure method of the Accelerometer class. Checks if saved
-    measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
+def test_quantization(quantized_accelerometer):
+    """Test the quantize method of the Sensor class. Checks if returned values
+    are as expected.
     """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-
-    relative_position = Vector([0, 0, 0])
-    gravity = 9.81
-    a_I = Vector(U_DOT_INDEX_200[3:6])
-    omega = Vector(u[10:13])
-    omega_dot = Vector(U_DOT_INDEX_200[10:13])
-    accel = (
-        a_I
-        + Vector.cross(omega_dot, relative_position)
-        + Vector.cross(omega, Vector.cross(omega, relative_position))
+    # expected values calculated by hand
+    assert quantized_accelerometer.quantize(Vector([3, 3, 3])) == Vector(
+        [1.9528, 1.9528, 1.9528]
     )
-    ax, ay, az = Matrix.transformation(u[6:10]) @ accel
-    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-
-    # check last measurement
-    assert len(ideal_accelerometer.measurement) == 3
-    assert all(isinstance(i, float) for i in ideal_accelerometer.measurement)
-    assert ideal_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
-
-    # check measured values
-    assert len(ideal_accelerometer.measured_data) == 1
-    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-    assert len(ideal_accelerometer.measured_data) == 2
-
-    assert all(isinstance(i, tuple) for i in ideal_accelerometer.measured_data)
-    assert ideal_accelerometer.measured_data[0][0] == t
-    assert ideal_accelerometer.measured_data[0][1:] == approx([ax, ay, az], abs=1e-10)
-
-
-def test_ideal_gyroscope_measure(ideal_gyroscope):
-    """Test the measure method of the Gyroscope class. Checks if saved
-    measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
-    """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    relative_position = Vector(
-        [np.random.randint(-1, 1), np.random.randint(-1, 1), np.random.randint(-1, 1)]
+    assert quantized_accelerometer.quantize(Vector([-3, -3, -3])) == Vector(
+        [-1.9528, -1.9528, -1.9528]
+    )
+    assert quantized_accelerometer.quantize(Vector([1, 1, 1])) == Vector(
+        [0.9764, 0.9764, 0.9764]
     )
 
-    rot = Matrix.transformation(u[6:10])
-    ax, ay, az = rot @ Vector(u[10:13])
-
-    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
-
-    # check last measurement
-    assert len(ideal_gyroscope.measurement) == 3
-    assert all(isinstance(i, float) for i in ideal_gyroscope.measurement)
-    assert ideal_gyroscope.measurement == approx([ax, ay, az], abs=1e-10)
-
-    # check measured values
-    assert len(ideal_gyroscope.measured_data) == 1
-    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
-    assert len(ideal_gyroscope.measured_data) == 2
 
-    assert all(isinstance(i, tuple) for i in ideal_gyroscope.measured_data)
-    assert ideal_gyroscope.measured_data[0][0] == t
-    assert ideal_gyroscope.measured_data[0][1:] == approx([ax, ay, az], abs=1e-10)
+@pytest.mark.parametrize(
+    "sensor",
+    [
+        "ideal_accelerometer",
+        "ideal_gyroscope",
+    ],
+)
+def test_measured_data(sensor, request):
+    """Test the measured_data property of the Sensors class. Checks if
+    the measured data is treated properly when the sensor is added once or more
+    than once to the rocket.
+    """
+    sensor = request.getfixturevalue(sensor)
+
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    assert len(sensor.measured_data) == 1
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    assert len(sensor.measured_data) == 2
+    assert all(isinstance(i, tuple) for i in sensor.measured_data)
+
+    # check case when sensor is added more than once to the rocket
+    sensor.measured_data = [
+        sensor.measured_data[:],
+        sensor.measured_data[:],
+    ]
+    sensor._save_data = sensor._save_data_multiple
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    assert len(sensor.measured_data) == 2
+    assert len(sensor.measured_data[0]) == 3
+    assert len(sensor.measured_data[1]) == 2
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    assert len(sensor.measured_data[0]) == 3
+    assert len(sensor.measured_data[1]) == 3
 
 
 def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
 
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0.4, 0.4, 1])
-    gravity = 9.81
-    a_I = Vector(U_DOT_INDEX_200[3:6]) + Vector([0, 0, -gravity])
-    omega = Vector(u[10:13])
-    omega_dot = Vector(U_DOT_INDEX_200[10:13])
+    a_I = Vector(U_DOT[3:6]) + Vector([0, 0, -GRAVITY])
+    omega = Vector(U[10:13])
+    omega_dot = Vector(U_DOT[10:13])
     accel = (
         a_I
         + Vector.cross(omega_dot, relative_position)
@@ -170,7 +154,7 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     )
     sensor_rotation = Matrix.transformation(euler_to_quaternions(60, 60, 60))
     total_rotation = sensor_rotation @ cross_axis_sensitivity
-    rocket_rotation = Matrix.transformation(u[6:10])
+    rocket_rotation = Matrix.transformation(U[6:10])
     # expected measurement without noise
     ax, ay, az = total_rotation @ (rocket_rotation @ accel)
     # expected measurement with constant bias
@@ -179,22 +163,22 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     az += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_accelerometer.measure(
-        t, u, U_DOT_INDEX_200, relative_position, gravity
+    noisy_rotated_accelerometer.measure(TIME, U, U_DOT, relative_position, GRAVITY)
+    assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.1)
+    assert len(noisy_rotated_accelerometer.measurement) == 3
+    assert noisy_rotated_accelerometer.measured_data[0][1:] == approx(
+        [ax, ay, az], rel=0.1
     )
-    assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.5)
+    assert noisy_rotated_accelerometer.measured_data[0][0] == TIME
 
 
 def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     """Test the measure method of the Gyroscope class. Checks if saved
     measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0.4, 0.4, 1])
-    gravity = 9.81
-    omega = Vector(u[10:13])
+    omega = Vector(U[10:13])
     # calculate total rotation matrix
     cross_axis_sensitivity = Matrix(
         [
@@ -205,7 +189,7 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     )
     sensor_rotation = Matrix.transformation(euler_to_quaternions(-60, -60, -60))
     total_rotation = sensor_rotation @ cross_axis_sensitivity
-    rocket_rotation = Matrix.transformation(u[6:10])
+    rocket_rotation = Matrix.transformation(U[6:10])
     # expected measurement without noise
     wx, wy, wz = total_rotation @ (rocket_rotation @ omega)
     # expected measurement with constant bias
@@ -214,69 +198,21 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     wz += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-    assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.5)
+    noisy_rotated_gyroscope.measure(TIME, U, U_DOT, relative_position, GRAVITY)
+    assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.2)
+    assert len(noisy_rotated_gyroscope.measurement) == 3
+    assert noisy_rotated_gyroscope.measured_data[0][1:] == approx([wx, wy, wz], rel=0.2)
+    assert noisy_rotated_gyroscope.measured_data[0][0] == TIME
 
 
-def test_quantization_accelerometer(quantized_accelerometer):
-    """Test the measure method of the Accelerometer class. Checks if saved
-    measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
-    """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    # calculate acceleration at sensor position in inertial frame
-    relative_position = Vector([0, 0, 0])
-    gravity = 9.81
-    a_I = Vector(U_DOT_INDEX_200[3:6])
-    omega = Vector(u[10:13])
-    omega_dot = Vector(U_DOT_INDEX_200[10:13])
-    accel = (
-        a_I
-        + Vector.cross(omega_dot, relative_position)
-        + Vector.cross(omega, Vector.cross(omega, relative_position))
-    )
-
-    # calculate total rotation matrix
-    rocket_rotation = Matrix.transformation(u[6:10])
-    # expected measurement without noise
-    ax, ay, az = rocket_rotation @ accel
-    # expected measurement with quantization
-    az = 2  # saturated
-    ax = round(ax / 0.4882) * 0.4882
-    ay = round(ay / 0.4882) * 0.4882
-    az = round(az / 0.4882) * 0.4882
-
-    # check last measurement considering noise error bounds
-    quantized_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-    assert quantized_accelerometer.measurement == approx([ax, ay, az], abs=1e-10)
-
-
-def test_quantization_gyroscope(quantized_gyroscope):
-    """Test the measure method of the Gyroscope class. Checks if saved
-    measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
-    """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    # calculate acceleration at sensor position in inertial frame
-    relative_position = Vector([0.4, 0.4, 1])
-    gravity = 9.81
-    omega = Vector(u[10:13])
-    # calculate total rotation matrix
-    rocket_rotation = Matrix.transformation(u[6:10])
-    # expected measurement without noise
-    wx, wy, wz = rocket_rotation @ omega
-    # expected measurement with quantization
-    wz = 15  # saturated
-    wx = round(wx / 0.4882) * 0.4882
-    wy = round(wy / 0.4882) * 0.4882
-    wz = round(wz / 0.4882) * 0.4882
-
-    # check last measurement considering noise error bounds
-    quantized_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-    assert quantized_gyroscope.measurement == approx([wx, wy, wz], abs=1e-10)
-
-
-def test_export_accel_data_csv(ideal_accelerometer):
+@pytest.mark.parametrize(
+    "sensor, expected_string",
+    [
+        ("ideal_accelerometer", "t,ax,ay,az\n"),
+        ("ideal_gyroscope", "t,wx,wy,wz\n"),
+    ],
+)
+def test_export_data_csv(sensor, expected_string, request):
     """Test the export_data method of accelerometer. Checks if the data is
     exported correctly.
 
@@ -285,32 +221,29 @@ def test_export_accel_data_csv(ideal_accelerometer):
     flight_calisto_accel_gyro : Flight
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    relative_position = Vector([0, 0, 0])
-    gravity = 9.81
-    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
+    sensor = request.getfixturevalue(sensor)
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
 
     file_name = "sensors.csv"
 
-    ideal_accelerometer.export_measured_data(file_name, format="csv")
+    sensor.export_measured_data(file_name, format="csv")
 
     with open(file_name, "r") as file:
         contents = file.read()
 
-    expected_data = "t,ax,ay,az\n"
-    for t, ax, ay, az in ideal_accelerometer.measured_data:
-        expected_data += f"{t},{ax},{ay},{az}\n"
+    expected_data = expected_string
+    for t, x, y, z in sensor.measured_data:
+        expected_data += f"{t},{x},{y},{z}\n"
 
     assert contents == expected_data
 
     # check exports for accelerometers added more than once to the rocket
-    ideal_accelerometer.measured_data = [
-        ideal_accelerometer.measured_data[:],
-        ideal_accelerometer.measured_data[:],
+    sensor.measured_data = [
+        sensor.measured_data[:],
+        sensor.measured_data[:],
     ]
-    ideal_accelerometer.export_measured_data(file_name, format="csv")
+    sensor.export_measured_data(file_name, format="csv")
     with open(file_name + "_1", "r") as file:
         contents = file.read()
     assert contents == expected_data
@@ -324,7 +257,14 @@ def test_export_accel_data_csv(ideal_accelerometer):
     os.remove(file_name + "_2")
 
 
-def test_export_accel_data_json(ideal_accelerometer):
+@pytest.mark.parametrize(
+    "sensor, expected_string",
+    [
+        ("ideal_accelerometer", ("ax", "ay", "az")),
+        ("ideal_gyroscope", ("wx", "wy", "wz")),
+    ],
+)
+def test_export_data_json(sensor, expected_string, request):
     """Test the export_data method of the accelerometer. Checks if the data is
     exported correctly.
 
@@ -334,129 +274,36 @@ def test_export_accel_data_json(ideal_accelerometer):
         Pytest fixture for the flight of the calisto rocket with an ideal
         accelerometer and a gyroscope.
     """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    relative_position = Vector([0, 0, 0])
-    gravity = 9.81
-    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
-    ideal_accelerometer.measure(t, u, U_DOT_INDEX_200, relative_position, gravity)
+    sensor = request.getfixturevalue(sensor)
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
 
     file_name = "sensors.json"
 
-    ideal_accelerometer.export_measured_data(file_name, format="json")
+    sensor.export_measured_data(file_name, format="json")
 
     contents = json.load(open(file_name, "r"))
 
-    expected_data = {"t": [], "ax": [], "ay": [], "az": []}
-    for t, ax, ay, az in ideal_accelerometer.measured_data:
+    expected_data = {
+        "t": [],
+        expected_string[0]: [],
+        expected_string[1]: [],
+        expected_string[2]: [],
+    }
+    for t, x, y, z in sensor.measured_data:
         expected_data["t"].append(t)
-        expected_data["ax"].append(ax)
-        expected_data["ay"].append(ay)
-        expected_data["az"].append(az)
+        expected_data[expected_string[0]].append(x)
+        expected_data[expected_string[1]].append(y)
+        expected_data[expected_string[2]].append(z)
 
     assert contents == expected_data
 
     # check exports for accelerometers added more than once to the rocket
-    ideal_accelerometer.measured_data = [
-        ideal_accelerometer.measured_data[:],
-        ideal_accelerometer.measured_data[:],
-    ]
-    ideal_accelerometer.export_measured_data(file_name, format="json")
-    contents = json.load(open(file_name + "_1", "r"))
-    assert contents == expected_data
-
-    contents = json.load(open(file_name + "_2", "r"))
-    assert contents == expected_data
-
-    os.remove(file_name)
-    os.remove(file_name + "_1")
-    os.remove(file_name + "_2")
-
-
-def test_export_gyro_data_csv(ideal_gyroscope):
-    """Test the export_data method of the gyroscope. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal
-        accelerometer and a gyroscope.
-    """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    relative_position = Vector([0, 0, 0])
-    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
-    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
-
-    file_name = "sensors.csv"
-
-    ideal_gyroscope.export_measured_data(file_name, format="csv")
-
-    with open(file_name, "r") as file:
-        contents = file.read()
-
-    expected_data = "t,wx,wy,wz\n"
-    for t, wx, wy, wz in ideal_gyroscope.measured_data:
-        expected_data += f"{t},{wx},{wy},{wz}\n"
-
-    assert contents == expected_data
-
-    # check exports for gyroscopes added more than once to the rocket
-    ideal_gyroscope.measured_data = [
-        ideal_gyroscope.measured_data[:],
-        ideal_gyroscope.measured_data[:],
-    ]
-    ideal_gyroscope.export_measured_data(file_name, format="csv")
-    with open(file_name + "_1", "r") as file:
-        contents = file.read()
-    assert contents == expected_data
-
-    with open(file_name + "_2", "r") as file:
-        contents = file.read()
-    assert contents == expected_data
-
-    os.remove(file_name)
-    os.remove(file_name + "_1")
-    os.remove(file_name + "_2")
-
-
-def test_export_gyro_data_json(ideal_gyroscope):
-    """Test the export_data method of the gyroscope. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
-    """
-    t = SOLUTION_INDEX_200[0]
-    u = SOLUTION_INDEX_200[1:]
-    relative_position = Vector([0, 0, 0])
-    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
-    ideal_gyroscope.measure(t, u, U_DOT_INDEX_200, relative_position)
-
-    file_name = "sensors.json"
-
-    ideal_gyroscope.export_measured_data(file_name, format="json")
-
-    contents = json.load(open(file_name, "r"))
-
-    expected_data = {"t": [], "wx": [], "wy": [], "wz": []}
-    for t, wx, wy, wz in ideal_gyroscope.measured_data:
-        expected_data["t"].append(t)
-        expected_data["wx"].append(wx)
-        expected_data["wy"].append(wy)
-        expected_data["wz"].append(wz)
-
-    assert contents == expected_data
-
-    # check exports for gyroscopes added more than once to the rocket
-    ideal_gyroscope.measured_data = [
-        ideal_gyroscope.measured_data[:],
-        ideal_gyroscope.measured_data[:],
+    sensor.measured_data = [
+        sensor.measured_data[:],
+        sensor.measured_data[:],
     ]
-    ideal_gyroscope.export_measured_data(file_name, format="json")
+    sensor.export_measured_data(file_name, format="json")
     contents = json.load(open(file_name + "_1", "r"))
     assert contents == expected_data
 

From 58859926b4e907f7edda15d4d22ab74f7c34d172 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 21:04:06 +0200
Subject: [PATCH 066/120] ENH: change format of sensor_data dict

---
 rocketpy/simulation/flight.py | 11 ++---------
 1 file changed, 2 insertions(+), 9 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 6386157d3..250b909bb 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -1288,6 +1288,7 @@ def __cache_post_process_variables(self):
         ]
 
     def __cache_sensor_data(self):
+        """Cache sensor data for simulations with sensors."""
         sensor_data = {}
         sensors = []
         for sensor in self.sensors:
@@ -1295,15 +1296,7 @@ def __cache_sensor_data(self):
             if sensor not in sensors:
                 sensors.append(sensor)
                 num_instances = sensor._attached_rockets[self.rocket]
-                # sensor added only once
-                if num_instances == 1:
-                    sensor_data[sensor] = sensor.measured_data[:]
-                # sensor added more then once
-                if num_instances > 1:
-                    sensor_data[sensor] = {}
-                    # iterate through each of the same sensor instances
-                    for index in range(num_instances):
-                        sensor_data[sensor][index + 1] = sensor.measured_data[index][:]
+                sensor_data[sensor] = sensor.measured_data[:]
         self.sensor_data = sensor_data
 
     @cached_property

From 02cad058a996a86aae4b3fdf376685acd582862b Mon Sep 17 00:00:00 2001
From: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date: Mon, 6 May 2024 16:05:42 -0300
Subject: [PATCH 067/120] MNT: improve flight init

Co-authored-by: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
---
 rocketpy/simulation/flight.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 250b909bb..f5d37a323 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -606,11 +606,8 @@ def __init__(
         self.terminate_on_apogee = terminate_on_apogee
         self.name = name
         self.equations_of_motion = equations_of_motion
-
-        # Controller initialization
-        self.__init_controllers()
-
         # Flight initialization
+        self.__init_controllers()
         self.__init_post_process_variables()
         self.__init_solution_monitors()
         self.__init_equations_of_motion()

From 69f17cdfa33a3dba0f61a9d2ba48c807dfcddac4 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 21:15:23 +0200
Subject: [PATCH 068/120] TST: increase rel tolerances

---
 tests/unit/test_sensors.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 07ed01f65..4e08dfcea 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -199,9 +199,9 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
 
     # check last measurement considering noise error bounds
     noisy_rotated_gyroscope.measure(TIME, U, U_DOT, relative_position, GRAVITY)
-    assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.2)
+    assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.3)
     assert len(noisy_rotated_gyroscope.measurement) == 3
-    assert noisy_rotated_gyroscope.measured_data[0][1:] == approx([wx, wy, wz], rel=0.2)
+    assert noisy_rotated_gyroscope.measured_data[0][1:] == approx([wx, wy, wz], rel=0.3)
     assert noisy_rotated_gyroscope.measured_data[0][0] == TIME
 
 

From 8d96e58a284148ac60e2d8a86848668946e02535 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 21:21:31 +0200
Subject: [PATCH 069/120] TST: fix export sensor data test

---
 tests/unit/test_flight.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/unit/test_flight.py b/tests/unit/test_flight.py
index 59368c268..10ecbe4fe 100644
--- a/tests/unit/test_flight.py
+++ b/tests/unit/test_flight.py
@@ -317,11 +317,11 @@ def test_export_sensor_data(flight_calisto_accel_gyro):
         for measurement in flight_calisto_accel_gyro.sensors[2].measured_data
     ]
     assert (
-        sensor_data["Accelerometer"]["1"]
+        sensor_data["Accelerometer"][0]
         == flight_calisto_accel_gyro.sensors[0].measured_data[0]
     )
     assert (
-        sensor_data["Accelerometer"]["2"]
+        sensor_data["Accelerometer"][1]
         == flight_calisto_accel_gyro.sensors[1].measured_data[1]
     )
     assert (

From ec4e25ea354fe628a9cf7120d60223333234fd01 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 23:16:16 +0200
Subject: [PATCH 070/120] TST: fix doctests

---
 rocketpy/mathutils/vector_matrix.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 14ea9ba54..5157f5463 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1058,8 +1058,8 @@ def transformation_euler_angles(roll, pitch, yaw):
 
         >>> M = Matrix.transformation_euler_angles(90, 0, 0)
         >>> M
-        Matrix([-2.220446049250313e-16, -1, 0.0],
-               [1, -2.220446049250313e-16, 0.0],
+        Matrix([-2.220446049250313e-16, -1.0, 0.0],
+               [1.0, -2.220446049250313e-16, 0.0],
                [0.0, 0.0, 1.0])
         """
         return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))

From adb2dbbac406cd2dccf4be22f1ff076f10d573c2 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 6 May 2024 23:35:03 +0200
Subject: [PATCH 071/120] TST: fix doctests

---
 rocketpy/mathutils/vector_matrix.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 5157f5463..8a59469b5 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -1058,8 +1058,8 @@ def transformation_euler_angles(roll, pitch, yaw):
 
         >>> M = Matrix.transformation_euler_angles(90, 0, 0)
         >>> M
-        Matrix([-2.220446049250313e-16, -1.0, 0.0],
-               [1.0, -2.220446049250313e-16, 0.0],
+        Matrix([2.220446049250313e-16, -1.0, 0.0],
+               [1.0, 2.220446049250313e-16, 0.0],
                [0.0, 0.0, 1.0])
         """
         return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))

From e0812a2244c7e6b5710e502e8cea8c3125e89c32 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 9 May 2024 13:36:39 +0200
Subject: [PATCH 072/120] ENH: change units in prints

---
 rocketpy/prints/sensors_prints.py | 10 +---------
 rocketpy/sensors/accelerometer.py |  2 ++
 rocketpy/sensors/gyroscope.py     |  2 ++
 3 files changed, 5 insertions(+), 9 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 40d66d2bb..9ec0e492d 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -1,18 +1,10 @@
 from abc import ABC, abstractmethod
 
-UNITS = {
-    "Gyroscope": "rad/s",
-    "Accelerometer": "m/s^2",
-    "Magnetometer": "T",
-    "PressureSensor": "Pa",
-    "TemperatureSensor": "K",
-}
-
 
 class _SensorsPrints(ABC):
     def __init__(self, sensor):
         self.sensor = sensor
-        self.units = UNITS[sensor.__class__.__name__]
+        self.units = sensor.__units__
 
     def _print_aligned(self, label, value):
         """Prints a label and a value aligned vertically."""
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 35c501792..29fe7f0ec 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -61,6 +61,8 @@ class Accelerometer(Sensors):
         temperature drift.
     """
 
+    __units__ = "m/s^2"
+
     def __init__(
         self,
         sampling_rate,
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 743b80c21..0f8629d77 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -61,6 +61,8 @@ class Gyroscope(Sensors):
         temperature drift.
     """
 
+    __units__ = "rad/s"
+
     def __init__(
         self,
         sampling_rate,

From 6ec4c0ba2cbb318c426309313c95e748fc29602e Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 10 May 2024 14:01:16 +0200
Subject: [PATCH 073/120] ENH: add .round to Matrix and remove broken doctests

---
 rocketpy/mathutils/vector_matrix.py | 55 +++++++++++++++++++++--------
 rocketpy/sensors/sensors.py         |  6 +++-
 rocketpy/tools.py                   | 31 ++++++++--------
 3 files changed, 62 insertions(+), 30 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index 8a59469b5..c10ec5faf 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -949,6 +949,47 @@ def dot(self, other):
         """
         return self.__matmul__(other)
 
+    def round(self, decimals=0):
+        """Round the matrix to a given number of decimals.
+
+        Parameters
+        ----------
+        decimals : int, optional
+            Number of decimal places to round to. Defaults to 0.
+
+        Returns
+        -------
+        Matrix
+            The rounded matrix.
+
+        Examples
+        --------
+        >>> M = Matrix([[1.1234, 2.3456, 3.4567], [4.5678, 5.6789, 6.7890], [7.8901, 8.9012, 9.0123]])
+        >>> M.round(2)
+        Matrix([1.12, 2.35, 3.46],
+               [4.57, 5.68, 6.79],
+               [7.89, 8.9, 9.01])
+        """
+        return Matrix(
+            [
+                [
+                    round(self.xx, decimals),
+                    round(self.xy, decimals),
+                    round(self.xz, decimals),
+                ],
+                [
+                    round(self.yx, decimals),
+                    round(self.yy, decimals),
+                    round(self.yz, decimals),
+                ],
+                [
+                    round(self.zx, decimals),
+                    round(self.zy, decimals),
+                    round(self.zz, decimals),
+                ],
+            ]
+        )
+
     def __str__(self):
         return (
             f"[{self.xx}, {self.xy}, {self.xz}]\n"
@@ -1047,20 +1088,6 @@ def transformation_euler_angles(roll, pitch, yaw):
         -------
         Matrix
             The transformation matrix from frame B to frame A.
-
-        Examples
-        --------
-        >>> M = Matrix.transformation_euler_angles(0, 0, 0)
-        >>> M
-        Matrix([1.0, 0.0, 0.0],
-               [0.0, 1.0, 0.0],
-               [0.0, 0.0, 1.0])
-
-        >>> M = Matrix.transformation_euler_angles(90, 0, 0)
-        >>> M
-        Matrix([2.220446049250313e-16, -1.0, 0.0],
-               [1.0, 2.220446049250313e-16, 0.0],
-               [0.0, 0.0, 1.0])
         """
         return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))
 
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 2196b25bc..d3d7f16d8 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -87,6 +87,8 @@ def __init__(
               standard rotation sequence is z-y-x (3-2-1) is used, meaning the
               sensor is first rotated by ψ around the z axis, then by θ around
               the new y axis and finally by φ around the new x axis.
+              TODO: x and y are not defined in the rocket class. User has no
+              way to know which axis is which.
             - A list of lists (matrix) of shape 3x3, representing the rotation
               matrix from the sensor frame to the rocket frame. The sensor frame
               of reference is defined as to have z axis along the sensor's normal
@@ -206,7 +208,9 @@ def __init__(
         if any(isinstance(row, (tuple, list)) for row in orientation):  # matrix
             self.rotation_matrix = Matrix(orientation)
         elif len(orientation) == 3:  # euler angles
-            self.rotation_matrix = Matrix.transformation_euler_angles(*orientation)
+            self.rotation_matrix = Matrix.transformation_euler_angles(
+                *orientation
+            ).round(12)
         else:
             raise ValueError("Invalid orientation format")
         self.normal_vector = Vector(
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 9941d3793..213225410 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -3,6 +3,7 @@
 import importlib.metadata
 import re
 import time
+import math
 from bisect import bisect_left
 
 import numpy as np
@@ -467,33 +468,33 @@ def quaternions_to_nutation(e1, e2):
     return (180 / np.pi) * 2 * np.arcsin(-((e1**2 + e2**2) ** 0.5))
 
 
-def euler_to_quaternions(roll, pitch, yaw):
+def euler_to_quaternions(yaw, pitch, roll):
     """Calculates the quaternions (Euler parameters) from the Euler angles in
-    3-2-1 sequence.
+    yaw, pitch, and roll sequence (3-2-1).
 
     Parameters
     ----------
-    roll : float
-        Euler angle due to roll (psi) in degrees
-    pitch : float
-        Euler angle due to pitch (theta) in degrees
     yaw : float
         Euler angle due to yaw (phi) in degrees
+    pitch : float
+        Euler angle due to pitch (theta) in degrees
+    roll : float
+        Euler angle due to roll (psi) in degrees
 
     Returns
     -------
     tuple
         Tuple containing the Euler parameters e0, e1, e2, e3
     """
-    psi = np.radians(roll)
-    theta = np.radians(pitch)
-    phi = np.radians(yaw)
-    cr = np.cos(phi / 2)
-    sr = np.sin(phi / 2)
-    cp = np.cos(theta / 2)
-    sp = np.sin(theta / 2)
-    cy = np.cos(psi / 2)
-    sy = np.sin(psi / 2)
+    phi = math.radians(yaw)
+    theta = math.radians(pitch)
+    psi = math.radians(roll)
+    cr = math.cos(phi / 2)
+    sr = math.sin(phi / 2)
+    cp = math.cos(theta / 2)
+    sp = math.sin(theta / 2)
+    cy = math.cos(psi / 2)
+    sy = math.sin(psi / 2)
     e0 = cr * cp * cy + sr * sp * sy
     e1 = sr * cp * cy - cr * sp * sy
     e2 = cr * sp * cy + sr * cp * sy

From 78e67f240f3cf289f104df6e5206717f063bb8b5 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 10 May 2024 14:01:33 +0200
Subject: [PATCH 074/120] TST: test transfromation euler angles

---
 tests/unit/test_tools_matrix.py | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/tests/unit/test_tools_matrix.py b/tests/unit/test_tools_matrix.py
index b43818450..bd33c4940 100644
--- a/tests/unit/test_tools_matrix.py
+++ b/tests/unit/test_tools_matrix.py
@@ -242,3 +242,21 @@ def test_matrix_transformation():
     q1, q2, q3 = np.sin(phi / 2) * n
     matrix = Matrix.transformation((q0, q1, q2, q3))
     assert matrix @ Vector([0, 0, 1]) == Vector([0, -1, 0])
+
+
+def test_matrix_transformation_euler_angles():
+    phi = 90
+    theta = 0
+    psi = 0
+    matrix = Matrix.transformation_euler_angles(phi, theta, psi)
+    matrix = matrix.round(12)
+    # Check that the matrix is orthogonal
+    assert matrix @ matrix.transpose == Matrix.identity()
+    # Check that the matrix rotates the vector correctly
+    assert matrix @ Vector([0, 0, 1]) == Vector([0, -1, 0])
+
+
+def test_matrix_round():
+    matrix = [[2e-10, -2e-10, 0], [5.1234, -5.1234, 0], [0, 0, 9]]
+    matrix = Matrix(matrix).round(3)
+    assert matrix == Matrix([[0, 0, 0], [5.123, -5.123, 0], [0, 0, 9]])

From d49b5c48d599244672497b1863ad21ccf81c2c28 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 10 May 2024 14:03:21 +0200
Subject: [PATCH 075/120] TST: imrpove test_euler_to_quaternions

---
 tests/unit/test_tools.py | 21 ++++++++++-----------
 1 file changed, 10 insertions(+), 11 deletions(-)

diff --git a/tests/unit/test_tools.py b/tests/unit/test_tools.py
index e1692720b..476451c85 100644
--- a/tests/unit/test_tools.py
+++ b/tests/unit/test_tools.py
@@ -4,14 +4,13 @@
 from rocketpy.tools import euler_to_quaternions
 
 
-def test_euler_to_quaternions():
-    q0, q1, q2, q3 = euler_to_quaternions(0, 0, 0)
-    assert q0 == 1
-    assert q1 == 0
-    assert q2 == 0
-    assert q3 == 0
-    q0, q1, q2, q3 = euler_to_quaternions(90, 90, 90)
-    assert round(q0, 7) == 0.7071068
-    assert round(q1, 7) == 0
-    assert round(q2, 7) == 0.7071068
-    assert round(q3, 7) == 0
+@pytest.mark.parametrize(
+    "angles, expected_quaternions",
+    [((0, 0, 0), (1, 0, 0, 0)), ((90, 90, 90), (0.7071068, 0, 0.7071068, 0))],
+)
+def test_euler_to_quaternions(angles, expected_quaternions):
+    q0, q1, q2, q3 = euler_to_quaternions(*angles)
+    assert round(q0, 7) == expected_quaternions[0]
+    assert round(q1, 7) == expected_quaternions[1]
+    assert round(q2, 7) == expected_quaternions[2]
+    assert round(q3, 7) == expected_quaternions[3]

From 57b41ab641faeed4c2d28f3db84aaf2a4302dec1 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Wed, 15 May 2024 06:20:53 -0400
Subject: [PATCH 076/120] DEV: update sensors_testing notebook

---
 docs/notebooks/sensors_testing.ipynb | 448 ++++++++-------------------
 1 file changed, 121 insertions(+), 327 deletions(-)

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors_testing.ipynb
index 797dcb232..842558dbd 100644
--- a/docs/notebooks/sensors_testing.ipynb
+++ b/docs/notebooks/sensors_testing.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -23,12 +23,15 @@
    },
    "outputs": [],
    "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
     "from rocketpy import Environment, SolidMotor, Rocket, Flight"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -41,74 +44,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "colab": {},
     "colab_type": "code",
     "id": "5kl-Je8dNVFI"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Gravity Details\n",
-      "\n",
-      "Acceleration of gravity at surface level:    9.7913 m/s²\n",
-      "Acceleration of gravity at  10.000 km (ASL): 9.7649 m/s²\n",
-      "\n",
-      "\n",
-      "Launch Site Details\n",
-      "\n",
-      "Launch Site Latitude: 32.99025°\n",
-      "Launch Site Longitude: -106.97500°\n",
-      "Reference Datum: SIRGAS2000\n",
-      "Launch Site UTM coordinates: 315468.64 W    3651938.65 N\n",
-      "Launch Site UTM zone: 13S\n",
-      "Launch Site Surface Elevation: 1400.0 m\n",
-      "\n",
-      "\n",
-      "Atmospheric Model Details\n",
-      "\n",
-      "Atmospheric Model Type: custom_atmosphere\n",
-      "custom_atmosphere Maximum Height: 10.000 km\n",
-      "\n",
-      "\n",
-      "Surface Atmospheric Conditions\n",
-      "\n",
-      "Surface Wind Speed: 4.69 m/s\n",
-      "Surface Wind Direction: 219.81°\n",
-      "Surface Wind Heading: 39.81°\n",
-      "Surface Pressure: 856.02 hPa\n",
-      "Surface Temperature: 279.07 K\n",
-      "Surface Air Density: 1.069 kg/m³\n",
-      "Surface Speed of Sound: 334.55 m/s\n",
-      "\n",
-      "\n",
-      "Earth Model Details\n",
-      "\n",
-      "Earth Radius at Launch site: 6371.83 km\n",
-      "Semi-major Axis: 6378.14 km\n",
-      "Semi-minor Axis: 6356.75 km\n",
-      "Flattening: 0.0034\n",
-      "\n",
-      "\n",
-      "Atmospheric Model Plots\n",
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 900x450 with 4 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "env = Environment(latitude=32.990254, longitude=-106.974998, elevation=1400)\n",
     "env.set_atmospheric_model(\n",
@@ -119,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -149,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -194,177 +136,97 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from rocketpy import Accelerometer, Gyroscope\n",
-    "accel_noisy_nosecone = Accelerometer(sampling_rate=100,\n",
-    "                  consider_gravity=False,\n",
-    "                  orientation=(60,60,60),\n",
-    "                  measurement_range=70,\n",
-    "                  resolution=0.4882,\n",
-    "                  noise_density=0.05,\n",
-    "                  random_walk=0.02,\n",
-    "                  constant_bias=1 ,\n",
-    "                  operating_temperature=25,\n",
-    "                  temperature_bias=0.02,\n",
-    "                  temperature_scale_factor=0.02,\n",
-    "                  cross_axis_sensitivity=0.02,\n",
-    "                  name='Accelerometer in Nosecone'\n",
-    "                )\n",
-    "accel_clean_cdm = Accelerometer(sampling_rate=100,\n",
-    "                  consider_gravity=False,\n",
-    "                  orientation=[[0.25, -0.0581, 0.9665],\n",
-    "                               [0.433, 0.8995, -0.0581],\n",
-    "                               [-0.8661, 0.433, 0.25]\n",
-    "                               ],\n",
-    "                  name='Accelerometer in CDM'\n",
-    "                  )\n",
+    "\n",
+    "accel_noisy_nosecone = Accelerometer(\n",
+    "    sampling_rate=100,\n",
+    "    consider_gravity=False,\n",
+    "    orientation=(60, 60, 60),\n",
+    "    measurement_range=70,\n",
+    "    resolution=0.4882,\n",
+    "    noise_density=0.05,\n",
+    "    random_walk_density=0.02,\n",
+    "    constant_bias=1,\n",
+    "    operating_temperature=25,\n",
+    "    temperature_bias=0.02,\n",
+    "    temperature_scale_factor=0.02,\n",
+    "    cross_axis_sensitivity=0.02,\n",
+    "    name=\"Accelerometer in Nosecone\",\n",
+    ")\n",
+    "accel_clean_cdm = Accelerometer(\n",
+    "    sampling_rate=100,\n",
+    "    consider_gravity=False,\n",
+    "    orientation=[\n",
+    "        [0.25, -0.0581, 0.9665],\n",
+    "        [0.433, 0.8995, -0.0581],\n",
+    "        [-0.8661, 0.433, 0.25],\n",
+    "    ],\n",
+    "    name=\"Accelerometer in CDM\",\n",
+    ")\n",
     "calisto.add_sensor(accel_noisy_nosecone, 1.278)\n",
-    "calisto.add_sensor(accel_clean_cdm, -0.10482544178314143)#, 127/2000)\n"
+    "calisto.add_sensor(accel_clean_cdm, -0.10482544178314143)  # , 127/2000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Identification of the Sensor:\n",
-      "\n",
-      "Name:                      Accelerometer in Nosecone\n",
-      "Type:                      Accelerometer\n",
-      "\n",
-      "Orientation of the Sensor:\n",
-      "\n",
-      "Orientation:               (60, 60, 60)\n",
-      "Normal Vector:             (0.9665063509461097, -0.05801270189221941, 0.2500000000000002)\n",
-      "Rotation Matrix:\n",
-      "                           [0.25, -0.06, 0.97]\n",
-      "                           [0.43, 0.9, -0.06]\n",
-      "                           [-0.87, 0.43, 0.25]\n",
-      "\n",
-      "Quantization of the Sensor:\n",
-      "\n",
-      "Measurement Range:         -70 to 70 (m/s^2)\n",
-      "Resolution:                0.4882 m/s^2/LSB\n",
-      "\n",
-      "Noise of the Sensor:\n",
-      "\n",
-      "Noise Density:             (0.05, 0.05, 0.05) m/s^2/√Hz\n",
-      "Random Walk:               (0.02, 0.02, 0.02) m/s^2/√Hz\n",
-      "Constant Bias:             (1, 1, 1) m/s^2\n",
-      "Operating Temperature:     25 °C\n",
-      "Temperature Bias:          (0.02, 0.02, 0.02) m/s^2/°C\n",
-      "Temperature Scale Factor:  (0.02, 0.02, 0.02) %/°C\n",
-      "Cross Axis Sensitivity:    0.02 %\n",
-      "Identification of the Sensor:\n",
-      "\n",
-      "Name:                      Accelerometer in CDM\n",
-      "Type:                      Accelerometer\n",
-      "\n",
-      "Orientation of the Sensor:\n",
-      "\n",
-      "Orientation:               [[0.25, -0.0581, 0.9665], [0.433, 0.8995, -0.0581], [-0.8661, 0.433, 0.25]]\n",
-      "Normal Vector:             (0.9665010341566599, -0.05810006216709978, 0.25000026750042936)\n",
-      "Rotation Matrix:\n",
-      "                           [0.25, -0.06, 0.97]\n",
-      "                           [0.43, 0.9, -0.06]\n",
-      "                           [-0.87, 0.43, 0.25]\n",
-      "\n",
-      "Quantization of the Sensor:\n",
-      "\n",
-      "Measurement Range:         -inf to inf (m/s^2)\n",
-      "Resolution:                0 m/s^2/LSB\n",
-      "\n",
-      "Noise of the Sensor:\n",
-      "\n",
-      "Noise Density:             (0, 0, 0) m/s^2/√Hz\n",
-      "Random Walk:               (0, 0, 0) m/s^2/√Hz\n",
-      "Constant Bias:             (0, 0, 0) m/s^2\n",
-      "Operating Temperature:     25 °C\n",
-      "Temperature Bias:          (0, 0, 0) m/s^2/°C\n",
-      "Temperature Scale Factor:  (0, 0, 0) %/°C\n",
-      "Cross Axis Sensitivity:    0 %\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "accel_noisy_nosecone.prints.all()\n",
-    "accel_clean_cdm.prints.all() # should have the same rotation matrix"
+    "accel_clean_cdm.prints.all()  # should have the same rotation matrix"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "gyro_clean = Gyroscope(sampling_rate=100)\n",
-    "gyro_noisy = Gyroscope(sampling_rate=100, \n",
-    "              orientation=(180, 0, 0),\n",
-    "              acceleration_sensitivity=0.02,\n",
-    "                  measurement_range=70,\n",
-    "                  resolution=0.4882,\n",
-    "                  noise_density=0.05,\n",
-    "                  random_walk=0.02,\n",
-    "                  constant_bias=1 ,\n",
-    "                  operating_temperature=25,\n",
-    "                  temperature_bias=0.02,\n",
-    "                  temperature_scale_factor=0.02,\n",
-    "                  cross_axis_sensitivity=0.02,\n",
-    "                  )\n",
-    "calisto.add_sensor(gyro_clean, -0.10482544178314143+0.5, 127/2000)\n",
-    "calisto.add_sensor(gyro_noisy, 1.278-0.4, 127/2000-127/4000)"
+    "gyro_noisy = Gyroscope(\n",
+    "    sampling_rate=100,\n",
+    "    orientation=(180, 0, 0),\n",
+    "    acceleration_sensitivity=0.02,\n",
+    "    measurement_range=70,\n",
+    "    resolution=0.4882,\n",
+    "    noise_density=0.05,\n",
+    "    random_walk_density=0.02,\n",
+    "    constant_bias=1,\n",
+    "    operating_temperature=25,\n",
+    "    temperature_bias=0.02,\n",
+    "    temperature_scale_factor=0.02,\n",
+    "    cross_axis_sensitivity=0.02,\n",
+    ")\n",
+    "calisto.add_sensor(gyro_clean, -0.10482544178314143 + 0.5, 127 / 2000)\n",
+    "calisto.add_sensor(gyro_noisy, 1.278 - 0.4, 127 / 2000 - 127 / 4000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x600 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "calisto.draw(plane=\"xz\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x600 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "calisto.draw(plane=\"yz\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -392,7 +254,6 @@
     "    # If we wanted to we could get the returned values from observed_variables:\n",
     "    # returned_time, deployment_level, drag_coefficient = observed_variables[-1]\n",
     "\n",
-    "\n",
     "    # Check if the rocket has reached burnout\n",
     "    accelerometer = sensors[0]\n",
     "    if accelerometer.measurement[2] > 0:\n",
@@ -429,7 +290,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -448,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -457,7 +318,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -478,173 +339,106 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "test_flight.altitude()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# get first column of every row as time from [(time,(ax,ay,az)),...] = a.measured_data\n",
     "time1, ax, ay, az = zip(*accel_noisy_nosecone.measured_data)\n",
     "time2, bx, by, bz = zip(*accel_clean_cdm.measured_data)\n",
     "\n",
     "\n",
-    "import matplotlib.pyplot as plt\n",
-    "plt.plot(time1, ax, label='Noisy Accelerometer')\n",
-    "plt.plot(time2, bx, label='Clean Accelerometer')\n",
+    "plt.plot(time1, ax, label=\"Noisy Accelerometer\")\n",
+    "plt.plot(time2, bx, label=\"Clean Accelerometer\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Acceleration ax (m/s^2)\")\n",
     "plt.legend()\n",
     "plt.show()\n",
     "\n",
-    "plt.plot(time1, ay, label='Noisy Accelerometer')\n",
-    "plt.plot(time2, by, label='Clean Accelerometer')\n",
+    "plt.plot(time1, ay, label=\"Noisy Accelerometer\")\n",
+    "plt.plot(time2, by, label=\"Clean Accelerometer\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Acceleration ay (m/s^2)\")\n",
     "plt.legend()\n",
     "plt.show()\n",
     "\n",
-    "plt.plot(time1, az, label='Noisy Accelerometer')\n",
-    "plt.plot(time2, bz, label='Clean Accelerometer')\n",
+    "plt.plot(time1, az, label=\"Noisy Accelerometer\")\n",
+    "plt.plot(time2, bz, label=\"Clean Accelerometer\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Acceleration az (m/s^2)\")\n",
     "plt.legend()\n",
     "plt.show()\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(0.0, 4.0)"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "import numpy as np\n",
-    "abs_a = (np.array(ax)**2 + np.array(ay)**2 + np.array(az)**2)**0.5\n",
-    "abs_b = (np.array(bx)**2 + np.array(by)**2 + np.array(bz)**2)**0.5\n",
-    "plt.plot(time1, abs_a, label='noisy')\n",
-    "plt.plot(time2, abs_b, label='clean')\n",
+    "# now plot the total acceleration\n",
+    "\n",
+    "abs_a = (np.array(ax) ** 2 + np.array(ay) ** 2 + np.array(az) ** 2) ** 0.5\n",
+    "abs_b = (np.array(bx) ** 2 + np.array(by) ** 2 + np.array(bz) ** 2) ** 0.5\n",
+    "plt.plot(time1, abs_a, label=\"noisy\")\n",
+    "plt.plot(time2, abs_b, label=\"clean\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Acceleration (m/s^2)\")\n",
     "plt.legend()\n",
-    "plt.xlim(0,4)"
+    "plt.xlim(0, 10)\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "time1, wx, wy, wz = zip(*gyro_noisy.measured_data)\n",
     "time2, zx, zy, zz = zip(*gyro_clean.measured_data)\n",
     "\n",
-    "plt.plot(time1, wx, label='Noisy Gyroscope')\n",
-    "plt.plot(time2, zx, label='Clean Gyroscope')\n",
+    "plt.plot(time1, wx, label=\"Noisy Gyroscope\")\n",
+    "plt.plot(time2, zx, label=\"Clean Gyroscope\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Angular Velocity wx (rad/s)\")\n",
     "plt.legend()\n",
     "plt.show()\n",
     "\n",
-    "plt.plot(time1, wy, label='Noisy Gyroscope')\n",
-    "plt.plot(time2, zy, label='Clean Gyroscope')\n",
+    "plt.plot(time1, wy, label=\"Noisy Gyroscope\")\n",
+    "plt.plot(time2, zy, label=\"Clean Gyroscope\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Angular Velocity wy (rad/s)\")\n",
     "plt.legend()\n",
     "plt.show()\n",
     "\n",
-    "plt.plot(time1, wz, label='Noisy Gyroscope')\n",
-    "plt.plot(time2, zz, label='Clean Gyroscope')\n",
+    "plt.plot(time1, wz, label=\"Noisy Gyroscope\")\n",
+    "plt.plot(time2, zz, label=\"Clean Gyroscope\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Angular Velocity wz (rad/s)\")\n",
     "plt.legend()\n",
-    "plt.show()\n"
+    "plt.show()\n",
+    "\n",
+    "# now plot the total angular velocity\n",
+    "\n",
+    "abs_w = (np.array(wx) ** 2 + np.array(wy) ** 2 + np.array(wz) ** 2) ** 0.5\n",
+    "abs_z = (np.array(zx) ** 2 + np.array(zy) ** 2 + np.array(zz) ** 2) ** 0.5\n",
+    "plt.plot(time1, abs_w, label=\"noisy\")\n",
+    "plt.plot(time2, abs_z, label=\"clean\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Angular Velocity (rad/s)\")\n",
+    "plt.legend()\n",
+    "plt.xlim(0, 10)\n",
+    "plt.show()"
    ]
   },
   {
@@ -677,7 +471,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.10.11"
   },
   "vscode": {
    "interpreter": {

From 7a2e50a7467e5119ca1e5becf12092491769cac0 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Wed, 15 May 2024 06:26:05 -0400
Subject: [PATCH 077/120] MNT: minor fixes - typos and isort

---
 rocketpy/mathutils/vector_matrix.py | 4 ++--
 rocketpy/sensors/accelerometer.py   | 2 +-
 rocketpy/tools.py                   | 2 +-
 tests/test_sensors.py               | 3 ++-
 tests/unit/test_sensors.py          | 2 +-
 5 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index c10ec5faf..fb884a672 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -950,7 +950,7 @@ def dot(self, other):
         return self.__matmul__(other)
 
     def round(self, decimals=0):
-        """Round the matrix to a given number of decimals.
+        """Round all the values matrix to a given number of decimals.
 
         Parameters
         ----------
@@ -1040,7 +1040,7 @@ def transformation(quaternion):
         q_x /= q_norm
         q_y /= q_norm
         q_z /= q_norm
-        # precompute common terms
+        # pre-compute common terms
         q_x2 = q_x**2
         q_y2 = q_y**2
         q_z2 = q_z**2
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 29fe7f0ec..38628fcbc 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -237,7 +237,7 @@ def measure(self, t, u, u_dot, relative_position, gravity, *args):
         )
         A = inertial_to_sensor @ A
 
-        # Apply noise + bias and quatize
+        # Apply noise + bias and quantize
         A = self.apply_noise(A)
         A = self.apply_temperature_drift(A)
         A = self.quantize(A)
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 213225410..d5526c1d1 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -1,9 +1,9 @@
 import functools
 import importlib
 import importlib.metadata
+import math
 import re
 import time
-import math
 from bisect import bisect_left
 
 import numpy as np
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 62c872b90..99ae7a0dd 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -1,5 +1,6 @@
 import json
 import os
+
 import numpy as np
 
 from rocketpy.mathutils.vector_matrix import Vector
@@ -25,7 +26,7 @@ def test_sensor_on_rocket(calisto_accel_gyro):
 
 
 def test_ideal_sensors(flight_calisto_accel_gyro):
-    """Test the ideal sensors. All types of sensors are here to reduvce
+    """Test the ideal sensors. All types of sensors are here to reduce
     testing time.
 
     Parameters
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 4e08dfcea..ff746e4ae 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -2,8 +2,8 @@
 import os
 
 import numpy as np
-from pytest import approx
 import pytest
+from pytest import approx
 
 from rocketpy.mathutils.vector_matrix import Matrix, Vector
 from rocketpy.tools import euler_to_quaternions

From a57308d10a6815ef984a01f8bea175cc3432afaa Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 14:46:54 +0200
Subject: [PATCH 078/120] MNT: remove aft double underscore from __units

---
 rocketpy/prints/sensors_prints.py | 2 +-
 rocketpy/sensors/accelerometer.py | 2 +-
 rocketpy/sensors/gyroscope.py     | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 9ec0e492d..1d6bb88ab 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -4,7 +4,7 @@
 class _SensorsPrints(ABC):
     def __init__(self, sensor):
         self.sensor = sensor
-        self.units = sensor.__units__
+        self.units = sensor.__units
 
     def _print_aligned(self, label, value):
         """Prints a label and a value aligned vertically."""
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 38628fcbc..42f6e7eb7 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -61,7 +61,7 @@ class Accelerometer(Sensors):
         temperature drift.
     """
 
-    __units__ = "m/s^2"
+    __units = "m/s^2"
 
     def __init__(
         self,
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 0f8629d77..6ef6f6b9b 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -61,7 +61,7 @@ class Gyroscope(Sensors):
         temperature drift.
     """
 
-    __units__ = "rad/s"
+    __units = "rad/s"
 
     def __init__(
         self,

From 11a8ab60486f3032ec1fae1b9d9328a46168e607 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 14:51:36 +0200
Subject: [PATCH 079/120] DOC: remove .type

---
 rocketpy/sensors/accelerometer.py | 2 --
 rocketpy/sensors/gyroscope.py     | 2 --
 rocketpy/sensors/sensors.py       | 2 --
 3 files changed, 6 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 42f6e7eb7..170402f7f 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -12,8 +12,6 @@ class Accelerometer(Sensors):
 
     Attributes
     ----------
-    type : str
-        Type of the sensor, in this case "Accelerometer".
     consider_gravity : bool
         Whether the sensor considers the effect of gravity on the acceleration.
     prints : _AccelerometerPrints
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 6ef6f6b9b..8928419a0 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -12,8 +12,6 @@ class Gyroscope(Sensors):
 
     Attributes
     ----------
-    type : str
-        Type of the sensor, in this case "Gyroscope".
     acceleration_sensitivity : float, list
         Sensitivity of the sensor to linear acceleration in rad/s/g.
     prints : _GyroscopePrints
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index d3d7f16d8..c7df1b9fe 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -10,8 +10,6 @@ class Sensors(ABC):
 
     Attributes
     ----------
-    type : str
-        Type of the sensor (e.g. Accelerometer, Gyroscope).
     sampling_rate : float
         Sample rate of the sensor in Hz.
     orientation : tuple, list

From 298406568508bc6529458da192ac1443a917e1be Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 14:59:46 +0200
Subject: [PATCH 080/120] MNT: remove .units underscores

---
 rocketpy/prints/sensors_prints.py | 2 +-
 rocketpy/sensors/accelerometer.py | 2 +-
 rocketpy/sensors/gyroscope.py     | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 1d6bb88ab..41f5fd937 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -4,7 +4,7 @@
 class _SensorsPrints(ABC):
     def __init__(self, sensor):
         self.sensor = sensor
-        self.units = sensor.__units
+        self.units = sensor.units
 
     def _print_aligned(self, label, value):
         """Prints a label and a value aligned vertically."""
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 170402f7f..00fbe25ef 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -59,7 +59,7 @@ class Accelerometer(Sensors):
         temperature drift.
     """
 
-    __units = "m/s^2"
+    units = "m/s^2"
 
     def __init__(
         self,
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 8928419a0..d40be7758 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -59,7 +59,7 @@ class Gyroscope(Sensors):
         temperature drift.
     """
 
-    __units = "rad/s"
+    units = "rad/s"
 
     def __init__(
         self,

From 82f79e7433d97f09ea6c9acb54d0ef72dfb030c7 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 15:01:33 +0200
Subject: [PATCH 081/120] MNT: remove repetition from sensors prints

---
 rocketpy/prints/sensors_prints.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 41f5fd937..2d646a4f4 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -12,13 +12,13 @@ def _print_aligned(self, label, value):
 
     def identity(self):
         """Prints the identity of the sensor."""
-        print("Identification of the Sensor:\n")
+        print("Identification:\n")
         self._print_aligned("Name:", self.sensor.name)
         self._print_aligned("Type:", self.sensor.__class__.__name__)
 
     def orientation(self):
         """Prints the orientation of the sensor."""
-        print("\nOrientation of the Sensor:\n")
+        print("\nOrientation:\n")
         self._print_aligned("Orientation:", self.sensor.orientation)
         self._print_aligned("Normal Vector:", self.sensor.normal_vector)
         print("Rotation Matrix:")
@@ -29,7 +29,7 @@ def orientation(self):
 
     def quantization(self):
         """Prints the quantization of the sensor."""
-        print("\nQuantization of the Sensor:\n")
+        print("\nQuantization:\n")
         self._print_aligned(
             "Measurement Range:",
             f"{self.sensor.measurement_range[0]} to {self.sensor.measurement_range[1]} ({self.units})",
@@ -43,7 +43,7 @@ def noise(self):
 
     def _general_noise(self):
         """Prints the noise of the sensor."""
-        print("\nNoise of the Sensor:\n")
+        print("\nNoise:\n")
         self._print_aligned(
             "Noise Density:", f"{self.sensor.noise_density} {self.units}/√Hz"
         )

From 5016283c190bdb431404c696396fe8a8c7be1d12 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 15:15:42 +0200
Subject: [PATCH 082/120] ENH: normalize_quaternions in tools.py

---
 rocketpy/mathutils/vector_matrix.py | 12 +++---------
 rocketpy/tools.py                   | 22 ++++++++++++++++++++++
 2 files changed, 25 insertions(+), 9 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index fb884a672..2776b3aa7 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -2,7 +2,7 @@
 from functools import cached_property
 from itertools import product
 
-from rocketpy.tools import euler_to_quaternions
+from rocketpy.tools import euler_to_quaternions, normalize_quaternions
 
 
 class Vector:
@@ -1031,15 +1031,9 @@ def transformation(quaternion):
         Matrix
             The transformation matrix from frame B to frame A.
         """
-        q_w, q_x, q_y, q_z = quaternion
         # normalize quaternion
-        q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
-        if q_norm == 0:
-            return Matrix.identity()
-        q_w /= q_norm
-        q_x /= q_norm
-        q_y /= q_norm
-        q_z /= q_norm
+        q_w, q_x, q_y, q_z = normalize_quaternions(quaternion)
+
         # pre-compute common terms
         q_x2 = q_x**2
         q_y2 = q_y**2
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index d5526c1d1..f3943a91b 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -11,6 +11,8 @@
 from cftime import num2pydate
 from packaging import version as packaging_version
 
+from rocketpy.mathutils.vector_matrix import Matrix
+
 # Mapping of module name and the name of the package that should be installed
 INSTALL_MAPPING = {"IPython": "ipython"}
 
@@ -502,6 +504,26 @@ def euler_to_quaternions(yaw, pitch, roll):
     return e0, e1, e2, e3
 
 
+def normalize_quaternions(quaternions):
+    """Normalizes the quaternions (Euler parameters) to have unit magnitude.
+
+    Parameters
+    ----------
+    quaternions : tuple
+        Tuple containing the Euler parameters e0, e1, e2, e3
+
+    Returns
+    -------
+    tuple
+        Tuple containing the Euler parameters e0, e1, e2, e3
+    """
+    q_w, q_x, q_y, q_z = quaternions
+    q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
+    if q_norm == 0:
+        return Matrix.identity()
+    return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
+
+
 if __name__ == "__main__":
     import doctest
 

From 6806912003576cf4559ac2c0f57ed7067f4e90da Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 17:27:03 +0200
Subject: [PATCH 083/120] BUG: remove Matrix circuklar import in tools

---
 rocketpy/tools.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index f3943a91b..0cbd16628 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -11,8 +11,6 @@
 from cftime import num2pydate
 from packaging import version as packaging_version
 
-from rocketpy.mathutils.vector_matrix import Matrix
-
 # Mapping of module name and the name of the package that should be installed
 INSTALL_MAPPING = {"IPython": "ipython"}
 
@@ -520,7 +518,7 @@ def normalize_quaternions(quaternions):
     q_w, q_x, q_y, q_z = quaternions
     q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
     if q_norm == 0:
-        return Matrix.identity()
+        return 1, 0, 0, 0
     return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
 
 

From b99b301feb49c3da37444ac32209ebd733c27d9f Mon Sep 17 00:00:00 2001
From: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date: Thu, 16 May 2024 12:45:46 -0300
Subject: [PATCH 084/120] MNT: remove unused variable

Co-authored-by: Gui-FernandesBR <63590233+Gui-FernandesBR@users.noreply.github.com>
---
 rocketpy/simulation/flight.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index f5d37a323..49460aeea 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -1292,7 +1292,6 @@ def __cache_sensor_data(self):
             # skip sensors that are used more then once in the rocket
             if sensor not in sensors:
                 sensors.append(sensor)
-                num_instances = sensor._attached_rockets[self.rocket]
                 sensor_data[sensor] = sensor.measured_data[:]
         self.sensor_data = sensor_data
 

From 75f8d9e47900ba2798661d88fb279bd44704f0cd Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 17:50:22 +0200
Subject: [PATCH 085/120] ENH: explicit for loop variables

---
 rocketpy/simulation/flight.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index f5d37a323..3e5c56b3e 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -3401,8 +3401,8 @@ def export_sensor_data(self, file_name, sensor=None):
         """
         if sensor is None:
             data_dict = {}
-            for key, value in self.sensor_data.items():
-                data_dict[key.name] = value
+            for used_sensor, measured_data in self.sensor_data.items():
+                data_dict[used_sensor.name] = measured_data
         else:
             # export data of only that sensor
             data_dict = {}

From a20d31dbb3853e4aa4ad5a0cc8a9def7c4e66962 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 16 May 2024 17:59:15 +0200
Subject: [PATCH 086/120] DOC: improve orientation docs

---
 rocketpy/sensors/accelerometer.py | 6 +++---
 rocketpy/sensors/gyroscope.py     | 6 +++---
 rocketpy/sensors/sensors.py       | 6 +++---
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 00fbe25ef..f4a637b66 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -90,10 +90,10 @@ def __init__(
             Orientation of the sensor in the rocket. The orientation can be
             given as:
             - A list of length 3, where the elements are the Euler angles for
-              the rotation roll (φ), pitch (θ) and yaw (ψ) in radians. The
+              the rotation yaw (ψ), pitch (θ) and roll (φ) in radians. The
               standard rotation sequence is z-y-x (3-2-1) is used, meaning the
-              sensor is first rotated by ψ around the z axis, then by θ around
-              the new y axis and finally by φ around the new x axis.
+              sensor is first rotated by ψ around the x axis, then by θ around
+              the new y axis and finally by φ around the new z axis.
             - A list of lists (matrix) of shape 3x3, representing the rotation
               matrix from the sensor frame to the rocket frame. The sensor frame
               of reference is defined as to have z axis along the sensor's normal
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index d40be7758..26df61d4d 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -90,10 +90,10 @@ def __init__(
             Orientation of the sensor in the rocket. The orientation can be
             given as:
             - A list of length 3, where the elements are the Euler angles for
-              the rotation roll (φ), pitch (θ) and yaw (ψ) in radians. The
+              the rotation yaw (ψ), pitch (θ) and roll (φ) in radians. The
               standard rotation sequence is z-y-x (3-2-1) is used, meaning the
-              sensor is first rotated by ψ around the z axis, then by θ around
-              the new y axis and finally by φ around the new x axis.
+              sensor is first rotated by ψ around the x axis, then by θ around
+              the new y axis and finally by φ around the new z axis.
             - A list of lists (matrix) of shape 3x3, representing the rotation
               matrix from the sensor frame to the rocket frame. The sensor frame
               of reference is defined as to have z axis along the sensor's normal
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index c7df1b9fe..eea0b9384 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -81,10 +81,10 @@ def __init__(
             Orientation of the sensor in the rocket. The orientation can be
             given as:
             - A list of length 3, where the elements are the Euler angles for
-              the rotation roll (φ), pitch (θ) and yaw (ψ) in radians. The
+              the rotation yaw (ψ), pitch (θ) and roll (φ) in radians. The
               standard rotation sequence is z-y-x (3-2-1) is used, meaning the
-              sensor is first rotated by ψ around the z axis, then by θ around
-              the new y axis and finally by φ around the new x axis.
+              sensor is first rotated by ψ around the x axis, then by θ around
+              the new y axis and finally by φ around the new z axis.
               TODO: x and y are not defined in the rocket class. User has no
               way to know which axis is which.
             - A list of lists (matrix) of shape 3x3, representing the rotation

From ce1d179412115965cee9a561fbe8d846477683a1 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 17 May 2024 01:33:10 +0200
Subject: [PATCH 087/120] ENH: x_position to x_offset

---
 rocketpy/rocket/rocket.py | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index c09e7c160..c7bbd380a 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -1170,7 +1170,7 @@ def add_parachute(
         self.parachutes.append(parachute)
         return self.parachutes[-1]
 
-    def add_sensor(self, sensor, position, x_position=0, y_position=0):
+    def add_sensor(self, sensor, position, x_offset=0, y_offset=0):
         """Adds a sensor to the rocket.
 
         Parameters
@@ -1180,18 +1180,20 @@ def add_sensor(self, sensor, position, x_position=0, y_position=0):
         position : int, float, tuple
             Position, in meters, of the sensor's coordinate system origin
             relative to the user defined rocket coordinate system.
-        x_position : int, float, optional
-            Distance in meters by which the sensor is to be translated in the x
-            direction relative to geometrical center line. Default is 0.
-        y_position : int, float, optional
-            Distance in meters by which the sensor is to be translated in the y
-            direction relative to geometrical center line. Default is 0.
+        x_offset : int, float, optional
+            Distance in meters by which the sensor is to be translated in the
+            rocket's x direction relative to geometrical center line.
+            Default is 0.
+        y_offset : int, float, optional
+            Distance in meters by which the sensor is to be translated in the
+            rocket's y direction relative to geometrical center line.
+            Default is 0.
 
         Returns
         -------
         None
         """
-        self.sensors.add(sensor, Vector([x_position, y_position, position]))
+        self.sensors.add(sensor, Vector([x_offset, y_offset, position]))
         try:
             sensor._attached_rockets[self] += 1
         except KeyError:

From 1e36391b287b84b207017b98ab4dfd393f8545a7 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Wed, 22 May 2024 20:27:55 +0200
Subject: [PATCH 088/120] TST: merge tests

---
 rocketpy/sensors/barometer.py |   4 +-
 tests/test_sensors.py         |  87 +++++++++-----
 tests/unit/test_sensors.py    | 217 ++++++++++++++++++++++++++++------
 3 files changed, 241 insertions(+), 67 deletions(-)

diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 7bbc8c02a..6fac2deee 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -50,6 +50,8 @@ class Barometer(ScalarSensors):
         temperature drift.
     """
 
+    units = "Pa"
+
     def __init__(
         self,
         sampling_rate,
@@ -173,7 +175,7 @@ def measure(self, time, **kwargs):
         P = self.quantize(P)
 
         self.measurement = P
-        self.measured_data.append((time, P))
+        self._save_data((time, P))
 
     def export_measured_data(self, filename, format="csv"):
         """Export the measured values to a file
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 5c2e6289d..c9440f568 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -2,6 +2,7 @@
 import os
 
 import numpy as np
+import pytest
 
 from rocketpy.mathutils.vector_matrix import Vector
 from rocketpy.rocket.components import Components
@@ -25,7 +26,24 @@ def test_sensor_on_rocket(calisto_sensors):
     assert isinstance(sensors[2].position, Vector)
 
 
-def test_ideal_sensors(flight_calisto_accel_gyro):
+@pytest.mark.parametrize(
+    "sensor_index, measured_data_key, sim_method, tolerance",
+    [
+        (0, "measured_data[0]", lambda flight, time: flight.acceleration(time), 1e-12),
+        (
+            2,
+            "measured_data",
+            lambda flight, time: np.sqrt(
+                flight.w1(time) ** 2 + flight.w2(time) ** 2 + flight.w3(time) ** 2
+            ),
+            1e-12,
+        ),
+        (3, "measured_data", lambda flight, time: flight.pressure(time), 1e-12),
+    ],
+)
+def test_ideal_sensors(
+    flight_calisto_sensors, sensor_index, measured_data_key, sim_method, tolerance
+):
     """Test the ideal sensors. All types of sensors are here to reduce
     testing time.
 
@@ -34,40 +52,47 @@ def test_ideal_sensors(flight_calisto_accel_gyro):
     flight_calisto_sensors : Flight
         Pytest fixture for the flight of the calisto rocket with a set of ideal
         sensors.
+    sensor_index : int
+        Index of the sensor in the rocket's sensor list.
+    measured_data_key : str
+        Key to access the measured data from the sensor component.
+    sim_method : function
+        Function to compute the simulated data.
+    tolerance : float
+        Tolerance level for the comparison between measured and simulated data.
     """
-    accelerometer = flight_calisto_sensors.rocket.sensors[0].component
-    time, ax, ay, az = zip(*accelerometer.measured_data[0])
-    ax = np.array(ax)
-    ay = np.array(ay)
-    az = np.array(az)
-    a = np.sqrt(ax**2 + ay**2 + az**2)
-    sim_accel = flight_calisto_sensors.acceleration(time)
+    sensor = flight_calisto_sensors.rocket.sensors[sensor_index].component
+    measured_data = eval(f"sensor.{measured_data_key}")
 
-    # tolerance is bounded to numerical errors in the transformation matrixes
-    assert np.allclose(a, sim_accel, atol=1e-12)
-    # check if both added accelerometer instances saved the same data
-    assert (
-        flight_calisto_sensors.sensors[0].measured_data[0]
-        == flight_calisto_sensors.sensors[0].measured_data[1]
-    )
+    if sensor_index == 0:  # Accelerometer
+        time, ax, ay, az = zip(*measured_data)
+        ax = np.array(ax)
+        ay = np.array(ay)
+        az = np.array(az)
+        a = np.sqrt(ax**2 + ay**2 + az**2)
+        sim_data = sim_method(flight_calisto_sensors, time)
+        assert np.allclose(a, sim_data, atol=tolerance)
+
+        # Check if both added accelerometer instances saved the same data
+        assert (
+            flight_calisto_sensors.sensors[0].measured_data[0]
+            == flight_calisto_sensors.sensors[0].measured_data[1]
+        )
 
-    gyroscope = flight_calisto_sensors.rocket.sensors[2].component
-    time, wx, wy, wz = zip(*gyroscope.measured_data)
-    wx = np.array(wx)
-    wy = np.array(wy)
-    wz = np.array(wz)
-    w = np.sqrt(wx**2 + wy**2 + wz**2)
-    flight_wx = np.array(flight_calisto_sensors.w1(time))
-    flight_wy = np.array(flight_calisto_sensors.w2(time))
-    flight_wz = np.array(flight_calisto_sensors.w3(time))
-    sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
-    assert np.allclose(w, sim_w, atol=1e-12)
+    elif sensor_index == 2:  # Gyroscope
+        time, wx, wy, wz = zip(*measured_data)
+        wx = np.array(wx)
+        wy = np.array(wy)
+        wz = np.array(wz)
+        w = np.sqrt(wx**2 + wy**2 + wz**2)
+        sim_data = sim_method(flight_calisto_sensors, time)
+        assert np.allclose(w, sim_data, atol=tolerance)
 
-    barometer = flight_calisto_sensors.rocket.sensors[3].component
-    time, pressure = zip(*barometer.measured_data)
-    pressure = np.array(pressure)
-    sim_pressure = np.array(flight_calisto_sensors.pressure(time))
-    assert np.allclose(pressure, sim_pressure, atol=1e-12)
+    elif sensor_index == 3:  # Barometer
+        time, pressure = zip(*measured_data)
+        pressure = np.array(pressure)
+        sim_data = sim_method(flight_calisto_sensors, time)
+        assert np.allclose(pressure, sim_data, atol=tolerance)
 
 
 def test_export_sensor_data(flight_calisto_sensors):
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 9cf604bc6..6b99bee79 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -50,6 +50,8 @@
         "quantized_accelerometer",
         "noisy_rotated_gyroscope",
         "quantized_gyroscope",
+        "noisy_barometer",
+        "quantized_barometer",
     ],
 )
 def test_sensors_prints(sensor, request):
@@ -62,7 +64,7 @@ def test_sensors_prints(sensor, request):
 
 
 def test_rotation_matrix(noisy_rotated_accelerometer):
-    """Test the rotation_matrix property of the Accelerometer class. Checks if
+    """Test the rotation_matrix property of the InertialSensors class. Checks if
     the rotation matrix is correctly calculated.
     """
     # values from external source
@@ -77,8 +79,8 @@ def test_rotation_matrix(noisy_rotated_accelerometer):
     assert np.allclose(expected_matrix, rotation_matrix, atol=1e-8)
 
 
-def test_quantization(quantized_accelerometer):
-    """Test the quantize method of the Sensor class. Checks if returned values
+def test_inertial_quantization(quantized_accelerometer):
+    """Test the quantize method of the InertialSensors class. Checks if returned values
     are as expected.
     """
     # expected values calculated by hand
@@ -93,6 +95,60 @@ def test_quantization(quantized_accelerometer):
     )
 
 
+def test_scalar_quantization(quantized_barometer):
+    """Test the quantize method of the ScalarSensors class. Checks if returned values
+    are as expected.
+    """
+    # expected values calculated by hand
+    assert quantized_barometer.quantize(7e5) == 7e4
+    assert quantized_barometer.quantize(-7e5) == -7e4
+    assert quantized_barometer.quantize(1001) == 1000.96
+
+
+import pytest
+
+
+@pytest.mark.parametrize(
+    "sensor, input_value, expected_output",
+    [
+        (
+            "quantized_accelerometer",
+            Vector([3, 3, 3]),
+            Vector([1.9528, 1.9528, 1.9528]),
+        ),
+        (
+            "quantized_accelerometer",
+            Vector([-3, -3, -3]),
+            Vector([-1.9528, -1.9528, -1.9528]),
+        ),
+        (
+            "quantized_accelerometer",
+            Vector([1, 1, 1]),
+            Vector([0.9764, 0.9764, 0.9764]),
+        ),
+        ("quantized_barometer", 7e5, 7e4),
+        ("quantized_barometer", -7e5, -7e4),
+        ("quantized_barometer", 1001, 1000.96),
+    ],
+)
+def test_quantization(sensor, input_value, expected_output, request):
+    """Test the quantize method of various sensor classes. Checks if returned values
+    are as expected.
+
+    Parameters
+    ----------
+    sensor : str
+        Fixture name of the sensor to be tested.
+    input_value : any
+        Input value to be quantized by the sensor.
+    expected_output : any
+        Expected output value after quantization.
+    """
+    sensor = request.getfixturevalue(sensor)
+    result = sensor.quantize(input_value)
+    assert result == expected_output
+
+
 @pytest.mark.parametrize(
     "sensor",
     [
@@ -100,16 +156,28 @@ def test_quantization(quantized_accelerometer):
         "ideal_gyroscope",
     ],
 )
-def test_measured_data(sensor, request):
+def test_inertial_measured_data(sensor, request):
     """Test the measured_data property of the Sensors class. Checks if
     the measured data is treated properly when the sensor is added once or more
     than once to the rocket.
     """
     sensor = request.getfixturevalue(sensor)
 
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
     assert len(sensor.measured_data) == 1
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
     assert len(sensor.measured_data) == 2
     assert all(isinstance(i, tuple) for i in sensor.measured_data)
 
@@ -119,52 +187,73 @@ def test_measured_data(sensor, request):
         sensor.measured_data[:],
     ]
     sensor._save_data = sensor._save_data_multiple
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
     assert len(sensor.measured_data) == 2
     assert len(sensor.measured_data[0]) == 3
     assert len(sensor.measured_data[1]) == 2
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
     assert len(sensor.measured_data[0]) == 3
     assert len(sensor.measured_data[1]) == 3
 
 
-def test_ideal_barometer_measure(ideal_barometer, example_plain_env):
-    """Test the measure method of the Barometer class. Checks if saved
+def test_scalar_measured_data(ideal_barometer, example_plain_env):
+    """Test the measure method of ScalarSensors. Checks if saved
     measurement is (P) and if measured_data is [(t, P), ...]
     """
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
-    relative_position = Vector(
-        [np.random.randint(-1, 1), np.random.randint(-1, 1), np.random.randint(-1, 1)]
-    )
-
-    rot = Matrix.transformation(u[6:10])
-    P = example_plain_env.pressure((rot @ relative_position).z + u[2])
+    t = TIME
+    u = U
 
     ideal_barometer.measure(
         t,
         u=u,
-        relative_position=relative_position,
+        relative_position=Vector([0, 0, 0]),
         pressure=example_plain_env.pressure,
     )
-
-    # check last measurement
-    assert isinstance(ideal_barometer.measurement, (int, float))
-    assert ideal_barometer.measurement == approx(P, abs=1e-10)
-
-    # check measured values
     assert len(ideal_barometer.measured_data) == 1
     ideal_barometer.measure(
         t,
         u=u,
-        relative_position=relative_position,
+        relative_position=Vector([0, 0, 0]),
         pressure=example_plain_env.pressure,
     )
     assert len(ideal_barometer.measured_data) == 2
-
     assert all(isinstance(i, tuple) for i in ideal_barometer.measured_data)
-    assert ideal_barometer.measured_data[0][0] == t
-    assert ideal_barometer.measured_data[0][1] == approx(P, abs=1e-10)
+
+    # check case when sensor is added more than once to the rocket
+    ideal_barometer.measured_data = [
+        ideal_barometer.measured_data[:],
+        ideal_barometer.measured_data[:],
+    ]
+    ideal_barometer._save_data = ideal_barometer._save_data_multiple
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=Vector([0, 0, 0]),
+        pressure=example_plain_env.pressure,
+    )
+    assert len(ideal_barometer.measured_data) == 2
+    assert len(ideal_barometer.measured_data[0]) == 3
+    assert len(ideal_barometer.measured_data[1]) == 2
+    ideal_barometer.measure(
+        t,
+        u=u,
+        relative_position=Vector([0, 0, 0]),
+        pressure=example_plain_env.pressure,
+    )
+    assert len(ideal_barometer.measured_data[0]) == 3
+    assert len(ideal_barometer.measured_data[1]) == 3
 
 
 def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
@@ -202,7 +291,13 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     az += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_accelerometer.measure(TIME, U, U_DOT, relative_position, GRAVITY)
+    noisy_rotated_accelerometer.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=relative_position,
+        gravity=GRAVITY,
+    )
     assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.1)
     assert len(noisy_rotated_accelerometer.measurement) == 3
     assert noisy_rotated_accelerometer.measured_data[0][1:] == approx(
@@ -237,13 +332,41 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
     wz += 0.5
 
     # check last measurement considering noise error bounds
-    noisy_rotated_gyroscope.measure(TIME, U, U_DOT, relative_position, GRAVITY)
+    noisy_rotated_gyroscope.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=relative_position,
+        gravity=GRAVITY,
+    )
     assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.3)
     assert len(noisy_rotated_gyroscope.measurement) == 3
     assert noisy_rotated_gyroscope.measured_data[0][1:] == approx([wx, wy, wz], rel=0.3)
     assert noisy_rotated_gyroscope.measured_data[0][0] == TIME
 
 
+def test_noisy_barometer(noisy_barometer, example_plain_env):
+    """Test the measure method of the Barometer class. Checks if saved
+    measurement is (P) and if measured_data is [(t, P), ...]
+    """
+    # expected measurement without noise
+    relative_position = Vector([0.4, 0.4, 1])
+    relative_altitude = (Matrix.transformation(U[6:10]) @ relative_position).z
+    P = example_plain_env.pressure(relative_altitude + U[2])
+    # expected measurement with constant bias
+    P += 0.5
+
+    noisy_barometer.measure(
+        time=TIME,
+        u=U,
+        relative_position=relative_position,
+        pressure=example_plain_env.pressure,
+    )
+    assert noisy_barometer.measurement == approx(P, rel=0.03)
+    assert noisy_barometer.measured_data[0][1] == approx(P, rel=0.03)
+    assert noisy_barometer.measured_data[0][0] == TIME
+
+
 @pytest.mark.parametrize(
     "sensor, expected_string",
     [
@@ -261,8 +384,20 @@ def test_export_data_csv(sensor, expected_string, request):
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
     sensor = request.getfixturevalue(sensor)
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
 
     file_name = "sensors.csv"
 
@@ -314,8 +449,20 @@ def test_export_data_json(sensor, expected_string, request):
         accelerometer and a gyroscope.
     """
     sensor = request.getfixturevalue(sensor)
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
-    sensor.measure(TIME, U, U_DOT, Vector([0, 0, 0]), GRAVITY)
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        gravity=GRAVITY,
+    )
 
     file_name = "sensors.json"
 

From f78e764cbc9fb8b794c987e050c35517a2220727 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Wed, 22 May 2024 21:18:03 +0200
Subject: [PATCH 089/120] ENH: inherited export method

---
 rocketpy/sensors/accelerometer.py | 46 ++---------------------
 rocketpy/sensors/barometer.py     | 40 ++------------------
 rocketpy/sensors/gyroscope.py     | 46 ++---------------------
 rocketpy/sensors/sensors.py       | 61 +++++++++++++++++++++++++++++++
 4 files changed, 70 insertions(+), 123 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index f0005914d..176f6d9ef 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -267,46 +267,6 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        if format.lower() not in ["json", "csv"]:
-            raise ValueError("Invalid format")
-        if format.lower() == "csv":
-            # if sensor has been added multiple times to the simulated rocket
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    with open(filename + f"_{i+1}", "w") as f:
-                        f.write("t,ax,ay,az\n")
-                        for t, ax, ay, az in data:
-                            f.write(f"{t},{ax},{ay},{az}\n")
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                with open(filename, "w") as f:
-                    f.write("t,ax,ay,az\n")
-                    for t, ax, ay, az in self.measured_data:
-                        f.write(f"{t},{ax},{ay},{az}\n")
-                print(f"Data saved to {filename}")
-            return
-        if format.lower() == "json":
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    dict = {"t": [], "ax": [], "ay": [], "az": []}
-                    for t, ax, ay, az in data:
-                        dict["t"].append(t)
-                        dict["ax"].append(ax)
-                        dict["ay"].append(ay)
-                        dict["az"].append(az)
-                    with open(filename + f"_{i+1}", "w") as f:
-                        json.dump(dict, f)
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                dict = {"t": [], "ax": [], "ay": [], "az": []}
-                for t, ax, ay, az in self.measured_data:
-                    dict["t"].append(t)
-                    dict["ax"].append(ax)
-                    dict["ay"].append(ay)
-                    dict["az"].append(az)
-                with open(filename, "w") as f:
-                    json.dump(dict, f)
-                print(f"Data saved to {filename}")
-            return
+        super().export_measured_data(
+            filename=filename, format=format, data_labels=("t", "ax", "ay", "az")
+        )
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 6fac2deee..f7f70fb70 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -192,40 +192,6 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        if format == "csv":
-            # if sensor has been added multiple times to the simulated rocket
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    with open(filename + f"_{i+1}", "w") as f:
-                        f.write("t,pressure\n")
-                        for t, pressure in data:
-                            f.write(f"{t},{pressure}\n")
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                with open(filename, "w") as f:
-                    f.write("t,pressure\n")
-                    for t, pressure in self.measured_data:
-                        f.write(f"{t},{pressure}\n")
-                print(f"Data saved to {filename}")
-        elif format == "json":
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    dict = {"t": [], "pressure": []}
-                    for t, pressure in data:
-                        dict["t"].append(t)
-                        dict["pressure"].append(pressure)
-                    with open(filename + f"_{i+1}", "w") as f:
-                        json.dump(dict, f)
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                dict = {"t": [], "pressure": []}
-                for t, pressure in self.measured_data:
-                    dict["t"].append(t)
-                    dict["pressure"].append(pressure)
-                with open(filename, "w") as f:
-                    json.dump(dict, f)
-                print(f"Data saved to {filename}")
-        else:
-            raise ValueError("Invalid format")
+        super().export_measured_data(
+            filename=filename, format=format, data_labels=("t", "pressure")
+        )
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 78503cac1..007f0a797 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -299,46 +299,6 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        if format.lower() not in ["csv", "json"]:
-            raise ValueError("Invalid format")
-        if format.lower() == "csv":
-            # if sensor has been added multiple times to the simulated rocket
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    with open(filename + f"_{i+1}", "w") as f:
-                        f.write("t,wx,wy,wz\n")
-                        for t, wx, wy, wz in data:
-                            f.write(f"{t},{wx},{wy},{wz}\n")
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                with open(filename, "w") as f:
-                    f.write("t,wx,wy,wz\n")
-                    for t, wx, wy, wz in self.measured_data:
-                        f.write(f"{t},{wx},{wy},{wz}\n")
-                print(f"Data saved to {filename}")
-            return
-        if format.lower() == "json":
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    dict = {"t": [], "wx": [], "wy": [], "wz": []}
-                    for t, wx, wy, wz in data:
-                        dict["t"].append(t)
-                        dict["wx"].append(wx)
-                        dict["wy"].append(wy)
-                        dict["wz"].append(wz)
-                    with open(filename + f"_{i+1}", "w") as f:
-                        json.dump(dict, f)
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                dict = {"t": [], "wx": [], "wy": [], "wz": []}
-                for t, wx, wy, wz in self.measured_data:
-                    dict["t"].append(t)
-                    dict["wx"].append(wx)
-                    dict["wy"].append(wy)
-                    dict["wz"].append(wz)
-                with open(filename, "w") as f:
-                    json.dump(dict, f)
-                print(f"Data saved to {filename}")
-            return
+        super().export_measured_data(
+            filename=filename, format=format, data_labels=("t", "wx", "wy", "wz")
+        )
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 5056ded1b..610c55c8e 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+import json
 
 import numpy as np
 
@@ -203,6 +204,66 @@ def apply_temperature_drift(self, value):
         """Apply temperature drift to the sensor measurement"""
         pass
 
+    def export_measured_data(self, filename, format, data_labels):
+        """
+        Export the measured values to a file
+
+        Parameters
+        ----------
+        filename : str
+            Name of the file to export the values to
+        format : str
+            Format of the file to export the values to. Options are "csv" and
+            "json". Default is "csv".
+        data_labels : tuple
+            Tuple of strings representing the labels for the data columns
+
+        Returns
+        -------
+        None
+        """
+        if format.lower() not in ["json", "csv"]:
+            raise ValueError("Invalid format")
+
+        if format.lower() == "csv":
+            # if sensor has been added multiple times to the simulated rocket
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    with open(filename + f"_{i+1}", "w") as f:
+                        f.write(",".join(data_labels) + "\n")
+                        for entry in data:
+                            f.write(",".join(map(str, entry)) + "\n")
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                with open(filename, "w") as f:
+                    f.write(",".join(data_labels) + "\n")
+                    for entry in self.measured_data:
+                        f.write(",".join(map(str, entry)) + "\n")
+                print(f"Data saved to {filename}")
+            return
+
+        if format.lower() == "json":
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    data_dict = {label: [] for label in data_labels}
+                    for entry in data:
+                        for label, value in zip(data_labels, entry):
+                            data_dict[label].append(value)
+                    with open(filename + f"_{i+1}", "w") as f:
+                        json.dump(data_dict, f)
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                data_dict = {label: [] for label in data_labels}
+                for entry in self.measured_data:
+                    for label, value in zip(data_labels, entry):
+                        data_dict[label].append(value)
+                with open(filename, "w") as f:
+                    json.dump(data_dict, f)
+                print(f"Data saved to {filename}")
+            return
+
 
 class InertialSensors(Sensors):
     """Abstract class for sensors

From fbaac5381d2ea61d371347e4c06c5abc8a5c238b Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Wed, 22 May 2024 21:18:34 +0200
Subject: [PATCH 090/120] TST: improve export data tests

---
 tests/unit/test_sensors.py | 245 ++++++++-----------------------------
 1 file changed, 53 insertions(+), 192 deletions(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 6b99bee79..8d1a20dcc 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -368,28 +368,31 @@ def test_noisy_barometer(noisy_barometer, example_plain_env):
 
 
 @pytest.mark.parametrize(
-    "sensor, expected_string",
+    "sensor, format, expected_header, expected_keys",
     [
-        ("ideal_accelerometer", "t,ax,ay,az\n"),
-        ("ideal_gyroscope", "t,wx,wy,wz\n"),
+        ("ideal_accelerometer", "csv", "t,ax,ay,az\n", ("ax", "ay", "az")),
+        ("ideal_gyroscope", "csv", "t,wx,wy,wz\n", ("wx", "wy", "wz")),
+        ("ideal_accelerometer", "json", None, ("ax", "ay", "az")),
+        ("ideal_gyroscope", "json", None, ("wx", "wy", "wz")),
+        ("ideal_barometer", "csv", "t,pressure\n", ("pressure",)),
+        ("ideal_barometer", "json", None, ("pressure",)),
     ],
 )
-def test_export_data_csv(sensor, expected_string, request):
-    """Test the export_data method of accelerometer. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
+def test_export_data(
+    sensor, format, expected_header, expected_keys, request, example_plain_env
+):
+    """Test the export_data method of the sensors. Checks if the data is
+    exported correctly in the specified format.
     """
     sensor = request.getfixturevalue(sensor)
+
     sensor.measure(
         time=TIME,
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
         gravity=GRAVITY,
+        pressure=example_plain_env.pressure,
     )
     sensor.measure(
         time=TIME,
@@ -397,205 +400,63 @@ def test_export_data_csv(sensor, expected_string, request):
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
         gravity=GRAVITY,
+        pressure=example_plain_env.pressure,
     )
 
-    file_name = "sensors.csv"
+    file_name = f"sensors.{format}"
 
-    sensor.export_measured_data(file_name, format="csv")
+    sensor.export_measured_data(file_name, format=format)
 
-    with open(file_name, "r") as file:
-        contents = file.read()
+    if format == "csv":
+        with open(file_name, "r") as file:
+            contents = file.read()
 
-    expected_data = expected_string
-    for t, x, y, z in sensor.measured_data:
-        expected_data += f"{t},{x},{y},{z}\n"
-
-    assert contents == expected_data
-
-    # check exports for accelerometers added more than once to the rocket
-    sensor.measured_data = [
-        sensor.measured_data[:],
-        sensor.measured_data[:],
-    ]
-    sensor.export_measured_data(file_name, format="csv")
-    with open(file_name + "_1", "r") as file:
-        contents = file.read()
-    assert contents == expected_data
-
-    with open(file_name + "_2", "r") as file:
-        contents = file.read()
-    assert contents == expected_data
-
-    os.remove(file_name)
-    os.remove(file_name + "_1")
-    os.remove(file_name + "_2")
-
-
-@pytest.mark.parametrize(
-    "sensor, expected_string",
-    [
-        ("ideal_accelerometer", ("ax", "ay", "az")),
-        ("ideal_gyroscope", ("wx", "wy", "wz")),
-    ],
-)
-def test_export_data_json(sensor, expected_string, request):
-    """Test the export_data method of the accelerometer. Checks if the data is
-    exported correctly.
-
-    Parameters
-    ----------
-    flight_calisto_accel_gyro : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal
-        accelerometer and a gyroscope.
-    """
-    sensor = request.getfixturevalue(sensor)
-    sensor.measure(
-        time=TIME,
-        u=U,
-        u_dot=U_DOT,
-        relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
-    )
-    sensor.measure(
-        time=TIME,
-        u=U,
-        u_dot=U_DOT,
-        relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
-    )
+        expected_data = expected_header
+        for data in sensor.measured_data:
+            expected_data += ",".join(map(str, data)) + "\n"
 
-    file_name = "sensors.json"
+        assert contents == expected_data
 
-    sensor.export_measured_data(file_name, format="json")
+    elif format == "json":
+        with open(file_name, "r") as file:
+            contents = json.load(file)
 
-    contents = json.load(open(file_name, "r"))
+        expected_data = {"t": []}
+        for key in expected_keys:
+            expected_data[key] = []
 
-    expected_data = {
-        "t": [],
-        expected_string[0]: [],
-        expected_string[1]: [],
-        expected_string[2]: [],
-    }
-    for t, x, y, z in sensor.measured_data:
-        expected_data["t"].append(t)
-        expected_data[expected_string[0]].append(x)
-        expected_data[expected_string[1]].append(y)
-        expected_data[expected_string[2]].append(z)
+        for data in sensor.measured_data:
+            expected_data["t"].append(data[0])
+            for i, key in enumerate(expected_keys):
+                expected_data[key].append(data[i + 1])
 
-    assert contents == expected_data
+        assert contents == expected_data
 
-    # check exports for accelerometers added more than once to the rocket
+    # check exports for sensors added more than once to the rocket
     sensor.measured_data = [
         sensor.measured_data[:],
         sensor.measured_data[:],
     ]
-    sensor.export_measured_data(file_name, format="json")
-    contents = json.load(open(file_name + "_1", "r"))
-    assert contents == expected_data
+    sensor.export_measured_data(file_name, format=format)
 
-    contents = json.load(open(file_name + "_2", "r"))
-    assert contents == expected_data
+    if format == "csv":
+        with open(f"{file_name}_1", "r") as file:
+            contents = file.read()
+        assert contents == expected_data
 
-    os.remove(file_name)
-    os.remove(file_name + "_1")
-    os.remove(file_name + "_2")
+        with open(f"{file_name}_2", "r") as file:
+            contents = file.read()
+        assert contents == expected_data
 
+    elif format == "json":
+        with open(f"{file_name}_1", "r") as file:
+            contents = json.load(file)
+        assert contents == expected_data
 
-def test_export_barometer_data_csv(ideal_barometer, example_plain_env):
-    """Test the export_data method of the barometer. Checks if the data is
-    exported correctly."""
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
-    relative_position = Vector([0, 0, 0])
-    ideal_barometer.measure(
-        t,
-        u=u,
-        relative_position=relative_position,
-        pressure=example_plain_env.pressure,
-    )
-    ideal_barometer.measure(
-        t,
-        u=u,
-        relative_position=relative_position,
-        pressure=example_plain_env.pressure,
-    )
-
-    file_name = "sensors.csv"
-
-    ideal_barometer.export_measured_data(file_name, format="csv")
-
-    with open(file_name, "r") as file:
-        contents = file.read()
-
-    expected_data = "t,pressure\n"
-    for t, pressure in ideal_barometer.measured_data:
-        expected_data += f"{t},{pressure}\n"
-
-    assert contents == expected_data
-
-    # check exports for gyroscopes added more than once to the rocket
-    ideal_barometer.measured_data = [
-        ideal_barometer.measured_data[:],
-        ideal_barometer.measured_data[:],
-    ]
-    ideal_barometer.export_measured_data(file_name, format="csv")
-    with open(file_name + "_1", "r") as file:
-        contents = file.read()
-    assert contents == expected_data
-
-    with open(file_name + "_2", "r") as file:
-        contents = file.read()
-    assert contents == expected_data
-
-    os.remove(file_name)
-    os.remove(file_name + "_1")
-    os.remove(file_name + "_2")
-
-
-def test_export_barometer_data_json(ideal_barometer, example_plain_env):
-    """Test the export_data method of the barometer. Checks if the data is
-    exported correctly."""
-    t = SOLUTION[0]
-    u = SOLUTION[1:]
-    relative_position = Vector([0, 0, 0])
-    ideal_barometer.measure(
-        t,
-        u=u,
-        relative_position=relative_position,
-        pressure=example_plain_env.pressure,
-    )
-    ideal_barometer.measure(
-        t,
-        u=u,
-        relative_position=relative_position,
-        pressure=example_plain_env.pressure,
-    )
-
-    file_name = "sensors.json"
-
-    ideal_barometer.export_measured_data(file_name, format="json")
-
-    contents = json.load(open(file_name, "r"))
-
-    expected_data = {"t": [], "pressure": []}
-    for t, pressure in ideal_barometer.measured_data:
-        expected_data["t"].append(t)
-        expected_data["pressure"].append(pressure)
-
-    assert contents == expected_data
-
-    # check exports for gyroscopes added more than once to the rocket
-    ideal_barometer.measured_data = [
-        ideal_barometer.measured_data[:],
-        ideal_barometer.measured_data[:],
-    ]
-    ideal_barometer.export_measured_data(file_name, format="json")
-    contents = json.load(open(file_name + "_1", "r"))
-    assert contents == expected_data
-
-    contents = json.load(open(file_name + "_2", "r"))
-    assert contents == expected_data
+        with open(f"{file_name}_2", "r") as file:
+            contents = json.load(file)
+        assert contents == expected_data
 
     os.remove(file_name)
-    os.remove(file_name + "_1")
-    os.remove(file_name + "_2")
+    os.remove(f"{file_name}_1")
+    os.remove(f"{file_name}_2")

From cdb54b1f6098d344f6463326ab365d311b6bc7bc Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 23 May 2024 20:01:07 +0200
Subject: [PATCH 091/120] TST: Refactor sensor tests and export method

---
 tests/test_sensors.py | 98 +++++++++++++++----------------------------
 1 file changed, 34 insertions(+), 64 deletions(-)

diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index c9440f568..3b8caeec7 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -26,76 +26,51 @@ def test_sensor_on_rocket(calisto_sensors):
     assert isinstance(sensors[2].position, Vector)
 
 
-@pytest.mark.parametrize(
-    "sensor_index, measured_data_key, sim_method, tolerance",
-    [
-        (0, "measured_data[0]", lambda flight, time: flight.acceleration(time), 1e-12),
-        (
-            2,
-            "measured_data",
-            lambda flight, time: np.sqrt(
-                flight.w1(time) ** 2 + flight.w2(time) ** 2 + flight.w3(time) ** 2
-            ),
-            1e-12,
-        ),
-        (3, "measured_data", lambda flight, time: flight.pressure(time), 1e-12),
-    ],
-)
-def test_ideal_sensors(
-    flight_calisto_sensors, sensor_index, measured_data_key, sim_method, tolerance
-):
+def test_ideal_sensors(flight_calisto_sensors):
     """Test the ideal sensors. All types of sensors are here to reduce
     testing time.
 
     Parameters
     ----------
     flight_calisto_sensors : Flight
-        Pytest fixture for the flight of the calisto rocket with a set of ideal
-        sensors.
-    sensor_index : int
-        Index of the sensor in the rocket's sensor list.
-    measured_data_key : str
-        Key to access the measured data from the sensor component.
-    sim_method : function
-        Function to compute the simulated data.
-    tolerance : float
-        Tolerance level for the comparison between measured and simulated data.
+        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    sensor = flight_calisto_sensors.rocket.sensors[sensor_index].component
-    measured_data = eval(f"sensor.{measured_data_key}")
+    accelerometer = flight_calisto_sensors.rocket.sensors[0].component
+    time, ax, ay, az = zip(*accelerometer.measured_data[0])
+    ax = np.array(ax)
+    ay = np.array(ay)
+    az = np.array(az)
+    a = np.sqrt(ax**2 + ay**2 + az**2)
+    sim_accel = flight_calisto_sensors.acceleration(time)
 
-    if sensor_index == 0:  # Accelerometer
-        time, ax, ay, az = zip(*measured_data)
-        ax = np.array(ax)
-        ay = np.array(ay)
-        az = np.array(az)
-        a = np.sqrt(ax**2 + ay**2 + az**2)
-        sim_data = sim_method(flight_calisto_sensors, time)
-        assert np.allclose(a, sim_data, atol=tolerance)
-
-        # Check if both added accelerometer instances saved the same data
-        assert (
-            flight_calisto_sensors.sensors[0].measured_data[0]
-            == flight_calisto_sensors.sensors[0].measured_data[1]
-        )
+    # tolerance is bounded to numerical errors in the transformation matrixes
+    assert np.allclose(a, sim_accel, atol=1e-12)
+    # check if both added accelerometer instances saved the same data
+    assert (
+        flight_calisto_sensors.sensors[0].measured_data[0]
+        == flight_calisto_sensors.sensors[0].measured_data[1]
+    )
 
-    elif sensor_index == 2:  # Gyroscope
-        time, wx, wy, wz = zip(*measured_data)
-        wx = np.array(wx)
-        wy = np.array(wy)
-        wz = np.array(wz)
-        w = np.sqrt(wx**2 + wy**2 + wz**2)
-        sim_data = sim_method(flight_calisto_sensors, time)
-        assert np.allclose(w, sim_data, atol=tolerance)
+    gyroscope = flight_calisto_sensors.rocket.sensors[2].component
+    time, wx, wy, wz = zip(*gyroscope.measured_data)
+    wx = np.array(wx)
+    wy = np.array(wy)
+    wz = np.array(wz)
+    w = np.sqrt(wx**2 + wy**2 + wz**2)
+    flight_wx = np.array(flight_calisto_sensors.w1(time))
+    flight_wy = np.array(flight_calisto_sensors.w2(time))
+    flight_wz = np.array(flight_calisto_sensors.w3(time))
+    sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
+    assert np.allclose(w, sim_w, atol=1e-12)
 
-    elif sensor_index == 3:  # Barometer
-        time, pressure = zip(*measured_data)
-        pressure = np.array(pressure)
-        sim_data = sim_method(flight_calisto_sensors, time)
-        assert np.allclose(pressure, sim_data, atol=tolerance)
+    barometer = flight_calisto_sensors.rocket.sensors[3].component
+    time, pressure = zip(*barometer.measured_data)
+    pressure = np.array(pressure)
+    sim_data = flight_calisto_sensors.pressure(time)
+    assert np.allclose(pressure, sim_data, atol=1e-12)
 
 
-def test_export_sensor_data(flight_calisto_sensors):
+def test_export_all_sensors_data(flight_calisto_sensors):
     """Test the export of sensor data.
 
     Parameters
@@ -128,12 +103,7 @@ def test_export_sensor_data(flight_calisto_sensors):
         for measurement in flight_calisto_sensors.sensors[3].measured_data
     ]
     assert (
-        sensor_data["Accelerometer"]["1"]
-        == flight_calisto_sensors.sensors[0].measured_data[0]
-    )
-    assert (
-        sensor_data["Accelerometer"]["2"]
-        == flight_calisto_sensors.sensors[1].measured_data[1]
+        sensor_data["Accelerometer"] == flight_calisto_sensors.sensors[0].measured_data
     )
     assert sensor_data["Gyroscope"] == flight_calisto_sensors.sensors[2].measured_data
     assert sensor_data["Barometer"] == flight_calisto_sensors.sensors[3].measured_data

From 612176dd9fbfccfcfb9d53309c8ec9c9e272dc49 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 23 May 2024 22:57:46 +0200
Subject: [PATCH 092/120] TST: fix fixture names

---
 tests/test_sensors.py     |  2 +-
 tests/unit/test_flight.py | 26 ++++++++++++--------------
 2 files changed, 13 insertions(+), 15 deletions(-)

diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 3b8caeec7..06f9b6178 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -15,7 +15,7 @@ def test_sensor_on_rocket(calisto_sensors):
 
     Parameters
     ----------
-    calisto_accel_gyro : Rocket
+    calisto_sensors : Rocket
         Pytest fixture for the calisto rocket with a set of ideal sensors.
     """
     sensors = calisto_sensors.sensors
diff --git a/tests/unit/test_flight.py b/tests/unit/test_flight.py
index 10ecbe4fe..d775d4175 100644
--- a/tests/unit/test_flight.py
+++ b/tests/unit/test_flight.py
@@ -289,42 +289,40 @@ def test_out_of_rail_stability_margin(flight_calisto_custom_wind):
     assert np.isclose(res, 2.14, atol=0.1)
 
 
-def test_export_sensor_data(flight_calisto_accel_gyro):
+def test_export_sensor_data(flight_calisto_sensors):
     """Test the export of sensor data.
 
     Parameters
     ----------
-    flight_calisto_accel_gyro : Flight
+    flight_calisto_sensors : Flight
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    flight_calisto_accel_gyro.export_sensor_data("test_sensor_data.json")
+    flight_calisto_sensors.export_sensor_data("test_sensor_data.json")
     # read the json and parse as dict
     filename = "test_sensor_data.json"
     with open(filename, "r") as f:
         data = f.read()
         sensor_data = json.loads(data)
     # convert list of tuples into list of lists to compare with the json
-    flight_calisto_accel_gyro.sensors[0].measured_data[0] = [
+    flight_calisto_sensors.sensors[0].measured_data[0] = [
         list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[0].measured_data[0]
+        for measurement in flight_calisto_sensors.sensors[0].measured_data[0]
     ]
-    flight_calisto_accel_gyro.sensors[1].measured_data[1] = [
+    flight_calisto_sensors.sensors[1].measured_data[1] = [
         list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[1].measured_data[1]
+        for measurement in flight_calisto_sensors.sensors[1].measured_data[1]
     ]
-    flight_calisto_accel_gyro.sensors[2].measured_data = [
+    flight_calisto_sensors.sensors[2].measured_data = [
         list(measurement)
-        for measurement in flight_calisto_accel_gyro.sensors[2].measured_data
+        for measurement in flight_calisto_sensors.sensors[2].measured_data
     ]
     assert (
         sensor_data["Accelerometer"][0]
-        == flight_calisto_accel_gyro.sensors[0].measured_data[0]
+        == flight_calisto_sensors.sensors[0].measured_data[0]
     )
     assert (
         sensor_data["Accelerometer"][1]
-        == flight_calisto_accel_gyro.sensors[1].measured_data[1]
-    )
-    assert (
-        sensor_data["Gyroscope"] == flight_calisto_accel_gyro.sensors[2].measured_data
+        == flight_calisto_sensors.sensors[1].measured_data[1]
     )
+    assert sensor_data["Gyroscope"] == flight_calisto_sensors.sensors[2].measured_data
     os.remove(filename)

From 0bd0f5113f8ec7718fc5de342fa237be2d5b339a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 24 May 2024 14:28:07 +0200
Subject: [PATCH 093/120] BUG: duplicate IntertialSensors

---
 rocketpy/sensors/sensors.py | 197 ------------------------------------
 1 file changed, 197 deletions(-)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 610c55c8e..99b4d2549 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -265,203 +265,6 @@ def export_measured_data(self, filename, format, data_labels):
             return
 
 
-class InertialSensors(Sensors):
-    """Abstract class for sensors
-
-    Attributes
-    ----------
-    sampling_rate : float
-        Sample rate of the sensor in Hz.
-    measurement_range : float, tuple
-        The measurement range of the sensor in the sensor units.
-    resolution : float
-        The resolution of the sensor in sensor units/LSB.
-    noise_density : float, list
-        The noise density of the sensor in sensor units/√Hz.
-    noise_variance : float, list
-        The variance of the noise of the sensor in sensor units^2.
-    random_walk_density : float, list
-        The random walk density of the sensor in sensor units/√Hz.
-    random_walk_variance : float, list
-        The variance of the random walk of the sensor in sensor units^2.
-    constant_bias : float, list
-        The constant bias of the sensor in sensor units.
-    operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
-    temperature_bias : float, list
-        The temperature bias of the sensor in sensor units/°C.
-    temperature_scale_factor : float, list
-        The temperature scale factor of the sensor in %/°C.
-    name : str
-        The name of the sensor.
-    measurement : float
-        The measurement of the sensor after quantization, noise and temperature
-        drift.
-    measured_data : list
-        The stored measured data of the sensor after quantization, noise and
-        temperature drift.
-    """
-
-    def __init__(
-        self,
-        sampling_rate,
-        measurement_range=np.inf,
-        resolution=0,
-        noise_density=0,
-        noise_variance=1,
-        random_walk_density=0,
-        random_walk_variance=1,
-        constant_bias=0,
-        operating_temperature=25,
-        temperature_bias=0,
-        temperature_scale_factor=0,
-        name="Sensor",
-    ):
-        """
-        Initialize the accelerometer sensor
-
-        Parameters
-        ----------
-        sampling_rate : float
-            Sample rate of the sensor
-        measurement_range : float, tuple, optional
-            The measurement range of the sensor in the sensor units. If a float,
-            the same range is applied both for positive and negative values. If
-            a tuple, the first value is the positive range and the second value
-            is the negative range. Default is np.inf.
-        resolution : float, optional
-            The resolution of the sensor in sensor units/LSB. Default is 0,
-            meaning no quantization is applied.
-        noise_density : float, list, optional
-            The noise density of the sensor for a Gaussian white noise in sensor
-            units/√Hz. Sometimes called "white noise drift",
-            "angular random walk" for gyroscopes, "velocity random walk" for
-            accelerometers or "(rate) noise density". Default is 0, meaning no
-            noise is applied.
-        noise_variance : float, list, optional
-            The noise variance of the sensor for a Gaussian white noise in
-            sensor units^2. Default is 1, meaning the noise is normally
-            distributed with a standard deviation of 1 unit.
-        random_walk_density : float, list, optional
-            The random walk density of the sensor for a Gaussian random walk in
-            sensor units/√Hz. Sometimes called "bias (in)stability" or
-            "bias drift". Default is 0, meaning no random walk is applied.
-        random_walk_variance : float, list, optional
-            The random walk variance of the sensor for a Gaussian random walk in
-            sensor units^2. Default is 1, meaning the noise is normally
-            distributed with a standard deviation of 1 unit.
-        constant_bias : float, list, optional
-            The constant bias of the sensor in sensor units. Default is 0,
-            meaning no constant bias is applied.
-        operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
-        temperature_bias : float, list, optional
-            The temperature bias of the sensor in sensor units/°C. Default is 0,
-            meaning no temperature bias is applied.
-        temperature_scale_factor : float, list, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
-            meaning no temperature scale factor is applied.
-        name : str, optional
-            The name of the sensor. Default is "Sensor".
-
-        Returns
-        -------
-        None
-
-        See Also
-        --------
-        TODO link to documentation on noise model
-        """
-        self.sampling_rate = sampling_rate
-        self.resolution = resolution
-        self.operating_temperature = operating_temperature
-        self.noise_density = noise_density
-        self.noise_variance = noise_variance
-        self.random_walk_density = random_walk_density
-        self.random_walk_variance = random_walk_variance
-        self.constant_bias = constant_bias
-        self.temperature_bias = temperature_bias
-        self.temperature_scale_factor = temperature_scale_factor
-        self.name = name
-        self.measurement = None
-        self.measured_data = []
-        self._counter = 0
-        self._save_data = self._save_data_single
-        self._random_walk_drift = 0
-        self.normal_vector = Vector([0, 0, 0])
-
-        # handle measurement range
-        if isinstance(measurement_range, (tuple, list)):
-            if len(measurement_range) != 2:
-                raise ValueError("Invalid measurement range format")
-            self.measurement_range = measurement_range
-        elif isinstance(measurement_range, (int, float)):
-            self.measurement_range = (-measurement_range, measurement_range)
-        else:
-            raise ValueError("Invalid measurement range format")
-
-        # map which rocket(s) the sensor is attached to and how many times
-        self._attached_rockets = {}
-
-    def __repr__(self):
-        return f"{self.name}"
-
-    def __call__(self, *args, **kwargs):
-        return self.measure(*args, **kwargs)
-
-    def _reset(self, simulated_rocket):
-        """Reset the sensor data for a new simulation."""
-        self._random_walk_drift = (
-            Vector([0, 0, 0]) if isinstance(self._random_walk_drift, Vector) else 0
-        )
-        self.measured_data = []
-        if self._attached_rockets[simulated_rocket] > 1:
-            self.measured_data = [
-                [] for _ in range(self._attached_rockets[simulated_rocket])
-            ]
-            self._save_data = self._save_data_multiple
-        else:
-            self._save_data = self._save_data_single
-
-    def _save_data_single(self, data):
-        """Save the measured data to the sensor data list for a sensor that is
-        added only once to the simulated rocket."""
-        self.measured_data.append(data)
-
-    def _save_data_multiple(self, data):
-        """Save the measured data to the sensor data list for a sensor that is
-        added multiple times to the simulated rocket."""
-        self.measured_data[self._counter].append(data)
-        # counter for cases where the sensor is added multiple times in a rocket
-        self._counter += 1
-        if self._counter == len(self.measured_data):
-            self._counter = 0
-
-    @abstractmethod
-    def measure(self, time, **kwargs):
-        pass
-
-    @abstractmethod
-    def export_measured_data(self):
-        pass
-
-    @abstractmethod
-    def quantize(self, value):
-        """Quantize the sensor measurement"""
-        pass
-
-    @abstractmethod
-    def apply_noise(self, value):
-        """Add noise to the sensor measurement"""
-        pass
-
-    @abstractmethod
-    def apply_temperature_drift(self, value):
-        """Apply temperature drift to the sensor measurement"""
-        pass
-
-
 class InertialSensors(Sensors):
     """Abstract class for sensors
 

From 332f3a949639ff2478e3c5c512cbdaf63b8c8394 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 21:21:38 +0200
Subject: [PATCH 094/120] TST: calisto_sensors to calisto_with_sensors

---
 tests/fixtures/flight/flight_fixtures.py  |  6 +--
 tests/fixtures/rockets/rocket_fixtures.py |  2 +-
 tests/test_sensors.py                     | 63 ++++++++++++-----------
 tests/unit/test_flight.py                 | 26 +++++-----
 4 files changed, 52 insertions(+), 45 deletions(-)

diff --git a/tests/fixtures/flight/flight_fixtures.py b/tests/fixtures/flight/flight_fixtures.py
index 0b47707b1..c8fe437ca 100644
--- a/tests/fixtures/flight/flight_fixtures.py
+++ b/tests/fixtures/flight/flight_fixtures.py
@@ -161,14 +161,14 @@ def flight_calisto_air_brakes(calisto_air_brakes_clamp_on, example_plain_env):
 
 
 @pytest.fixture
-def flight_calisto_sensors(calisto_sensors, example_plain_env):
+def flight_calisto_with_sensors(calisto_with_sensors, example_plain_env):
     """A rocketpy.Flight object of the Calisto rocket. This uses the calisto
     with a set of ideal sensors. The environment is the simplest possible, with
     no parameters set.
 
     Parameters
     ----------
-    calisto_sensors : rocketpy.Rocket
+    calisto_with_sensors : rocketpy.Rocket
         An object of the Rocket class.
     example_plain_env : rocketpy.Environment
         An object of the Environment class.
@@ -180,7 +180,7 @@ def flight_calisto_sensors(calisto_sensors, example_plain_env):
         condition.
     """
     return Flight(
-        rocket=calisto_sensors,
+        rocket=calisto_with_sensors,
         environment=example_plain_env,
         rail_length=5.2,
         inclination=85,
diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index 9e971f124..a973e433b 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -244,7 +244,7 @@ def calisto_air_brakes_clamp_off(calisto_robust, controller_function):
 
 
 @pytest.fixture
-def calisto_sensors(
+def calisto_with_sensors(
     calisto,
     calisto_nose_cone,
     calisto_tail,
diff --git a/tests/test_sensors.py b/tests/test_sensors.py
index 06f9b6178..ba9a32b75 100644
--- a/tests/test_sensors.py
+++ b/tests/test_sensors.py
@@ -10,15 +10,15 @@
 from rocketpy.sensors.gyroscope import Gyroscope
 
 
-def test_sensor_on_rocket(calisto_sensors):
+def test_sensor_on_rocket(calisto_with_sensors):
     """Test the sensor on the rocket.
 
     Parameters
     ----------
-    calisto_sensors : Rocket
+    calisto_with_sensors : Rocket
         Pytest fixture for the calisto rocket with a set of ideal sensors.
     """
-    sensors = calisto_sensors.sensors
+    sensors = calisto_with_sensors.sensors
     assert isinstance(sensors, Components)
     assert isinstance(sensors[0].component, Accelerometer)
     assert isinstance(sensors[1].position, Vector)
@@ -26,85 +26,90 @@ def test_sensor_on_rocket(calisto_sensors):
     assert isinstance(sensors[2].position, Vector)
 
 
-def test_ideal_sensors(flight_calisto_sensors):
+def test_ideal_sensors(flight_calisto_with_sensors):
     """Test the ideal sensors. All types of sensors are here to reduce
     testing time.
 
     Parameters
     ----------
-    flight_calisto_sensors : Flight
+    flight_calisto_with_sensors : Flight
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    accelerometer = flight_calisto_sensors.rocket.sensors[0].component
+    accelerometer = flight_calisto_with_sensors.rocket.sensors[0].component
     time, ax, ay, az = zip(*accelerometer.measured_data[0])
     ax = np.array(ax)
     ay = np.array(ay)
     az = np.array(az)
     a = np.sqrt(ax**2 + ay**2 + az**2)
-    sim_accel = flight_calisto_sensors.acceleration(time)
+    sim_accel = flight_calisto_with_sensors.acceleration(time)
 
     # tolerance is bounded to numerical errors in the transformation matrixes
     assert np.allclose(a, sim_accel, atol=1e-12)
     # check if both added accelerometer instances saved the same data
     assert (
-        flight_calisto_sensors.sensors[0].measured_data[0]
-        == flight_calisto_sensors.sensors[0].measured_data[1]
+        flight_calisto_with_sensors.sensors[0].measured_data[0]
+        == flight_calisto_with_sensors.sensors[0].measured_data[1]
     )
 
-    gyroscope = flight_calisto_sensors.rocket.sensors[2].component
+    gyroscope = flight_calisto_with_sensors.rocket.sensors[2].component
     time, wx, wy, wz = zip(*gyroscope.measured_data)
     wx = np.array(wx)
     wy = np.array(wy)
     wz = np.array(wz)
     w = np.sqrt(wx**2 + wy**2 + wz**2)
-    flight_wx = np.array(flight_calisto_sensors.w1(time))
-    flight_wy = np.array(flight_calisto_sensors.w2(time))
-    flight_wz = np.array(flight_calisto_sensors.w3(time))
+    flight_wx = np.array(flight_calisto_with_sensors.w1(time))
+    flight_wy = np.array(flight_calisto_with_sensors.w2(time))
+    flight_wz = np.array(flight_calisto_with_sensors.w3(time))
     sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
     assert np.allclose(w, sim_w, atol=1e-12)
 
-    barometer = flight_calisto_sensors.rocket.sensors[3].component
+    barometer = flight_calisto_with_sensors.rocket.sensors[3].component
     time, pressure = zip(*barometer.measured_data)
     pressure = np.array(pressure)
-    sim_data = flight_calisto_sensors.pressure(time)
+    sim_data = flight_calisto_with_sensors.pressure(time)
     assert np.allclose(pressure, sim_data, atol=1e-12)
 
 
-def test_export_all_sensors_data(flight_calisto_sensors):
+def test_export_all_sensors_data(flight_calisto_with_sensors):
     """Test the export of sensor data.
 
     Parameters
     ----------
-    flight_calisto_sensors : Flight
+    flight_calisto_with_sensors : Flight
         Pytest fixture for the flight of the calisto rocket with a set of ideal
         sensors.
     """
-    flight_calisto_sensors.export_sensor_data("test_sensor_data.json")
+    flight_calisto_with_sensors.export_sensor_data("test_sensor_data.json")
     # read the json and parse as dict
     filename = "test_sensor_data.json"
     with open(filename, "r") as f:
         data = f.read()
         sensor_data = json.loads(data)
     # convert list of tuples into list of lists to compare with the json
-    flight_calisto_sensors.sensors[0].measured_data[0] = [
+    flight_calisto_with_sensors.sensors[0].measured_data[0] = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[0].measured_data[0]
+        for measurement in flight_calisto_with_sensors.sensors[0].measured_data[0]
     ]
-    flight_calisto_sensors.sensors[1].measured_data[1] = [
+    flight_calisto_with_sensors.sensors[1].measured_data[1] = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[1].measured_data[1]
+        for measurement in flight_calisto_with_sensors.sensors[1].measured_data[1]
     ]
-    flight_calisto_sensors.sensors[2].measured_data = [
+    flight_calisto_with_sensors.sensors[2].measured_data = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[2].measured_data
+        for measurement in flight_calisto_with_sensors.sensors[2].measured_data
     ]
-    flight_calisto_sensors.sensors[3].measured_data = [
+    flight_calisto_with_sensors.sensors[3].measured_data = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[3].measured_data
+        for measurement in flight_calisto_with_sensors.sensors[3].measured_data
     ]
     assert (
-        sensor_data["Accelerometer"] == flight_calisto_sensors.sensors[0].measured_data
+        sensor_data["Accelerometer"]
+        == flight_calisto_with_sensors.sensors[0].measured_data
+    )
+    assert (
+        sensor_data["Gyroscope"] == flight_calisto_with_sensors.sensors[2].measured_data
+    )
+    assert (
+        sensor_data["Barometer"] == flight_calisto_with_sensors.sensors[3].measured_data
     )
-    assert sensor_data["Gyroscope"] == flight_calisto_sensors.sensors[2].measured_data
-    assert sensor_data["Barometer"] == flight_calisto_sensors.sensors[3].measured_data
     os.remove(filename)
diff --git a/tests/unit/test_flight.py b/tests/unit/test_flight.py
index d775d4175..e09657d82 100644
--- a/tests/unit/test_flight.py
+++ b/tests/unit/test_flight.py
@@ -289,40 +289,42 @@ def test_out_of_rail_stability_margin(flight_calisto_custom_wind):
     assert np.isclose(res, 2.14, atol=0.1)
 
 
-def test_export_sensor_data(flight_calisto_sensors):
+def test_export_sensor_data(flight_calisto_with_sensors):
     """Test the export of sensor data.
 
     Parameters
     ----------
-    flight_calisto_sensors : Flight
+    flight_calisto_with_sensors : Flight
         Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
     """
-    flight_calisto_sensors.export_sensor_data("test_sensor_data.json")
+    flight_calisto_with_sensors.export_sensor_data("test_sensor_data.json")
     # read the json and parse as dict
     filename = "test_sensor_data.json"
     with open(filename, "r") as f:
         data = f.read()
         sensor_data = json.loads(data)
     # convert list of tuples into list of lists to compare with the json
-    flight_calisto_sensors.sensors[0].measured_data[0] = [
+    flight_calisto_with_sensors.sensors[0].measured_data[0] = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[0].measured_data[0]
+        for measurement in flight_calisto_with_sensors.sensors[0].measured_data[0]
     ]
-    flight_calisto_sensors.sensors[1].measured_data[1] = [
+    flight_calisto_with_sensors.sensors[1].measured_data[1] = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[1].measured_data[1]
+        for measurement in flight_calisto_with_sensors.sensors[1].measured_data[1]
     ]
-    flight_calisto_sensors.sensors[2].measured_data = [
+    flight_calisto_with_sensors.sensors[2].measured_data = [
         list(measurement)
-        for measurement in flight_calisto_sensors.sensors[2].measured_data
+        for measurement in flight_calisto_with_sensors.sensors[2].measured_data
     ]
     assert (
         sensor_data["Accelerometer"][0]
-        == flight_calisto_sensors.sensors[0].measured_data[0]
+        == flight_calisto_with_sensors.sensors[0].measured_data[0]
     )
     assert (
         sensor_data["Accelerometer"][1]
-        == flight_calisto_sensors.sensors[1].measured_data[1]
+        == flight_calisto_with_sensors.sensors[1].measured_data[1]
+    )
+    assert (
+        sensor_data["Gyroscope"] == flight_calisto_with_sensors.sensors[2].measured_data
     )
-    assert sensor_data["Gyroscope"] == flight_calisto_sensors.sensors[2].measured_data
     os.remove(filename)

From b88257983650a40ff82c34c9adb3a8edab5fbc5e Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 21:21:53 +0200
Subject: [PATCH 095/120] MNT: isort

---
 rocketpy/__init__.py         | 2 +-
 rocketpy/sensors/__init__.py | 4 ++--
 rocketpy/sensors/sensors.py  | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/rocketpy/__init__.py b/rocketpy/__init__.py
index 1e0c0bef5..43a6ebc67 100644
--- a/rocketpy/__init__.py
+++ b/rocketpy/__init__.py
@@ -37,5 +37,5 @@
     Tail,
     TrapezoidalFins,
 )
-from .sensors import Accelerometer, Gyroscope, Barometer
+from .sensors import Accelerometer, Barometer, Gyroscope
 from .simulation import Flight
diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 754a3f704..50a105551 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1,4 +1,4 @@
 from .accelerometer import Accelerometer
-from .gyroscope import Gyroscope
-from .sensors import Sensors, InertialSensors, ScalarSensors
 from .barometer import Barometer
+from .gyroscope import Gyroscope
+from .sensors import InertialSensors, ScalarSensors, Sensors
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 99b4d2549..a5efdd8e0 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -1,5 +1,5 @@
-from abc import ABC, abstractmethod
 import json
+from abc import ABC, abstractmethod
 
 import numpy as np
 

From 5d5f9e9b68b1961a408f3de1a0891d0d27541ee3 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:08:26 +0200
Subject: [PATCH 096/120] MNT: remove type docs

---
 rocketpy/sensors/sensors.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index a5efdd8e0..0f0cd8f1e 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -11,8 +11,6 @@ class Sensors(ABC):
 
     Attributes
     ----------
-    type : str
-        Type of the sensor (e.g. Accelerometer, Gyroscope).
     sampling_rate : float
         Sample rate of the sensor in Hz.
     measurement_range : float, tuple

From f913f8602ccdbaf74e2a379bd3bf8b500202e3fd Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:09:59 +0200
Subject: [PATCH 097/120] ENH: move export_sensor_measured_data to tools.py

---
 rocketpy/sensors/accelerometer.py |  4 +-
 rocketpy/sensors/barometer.py     |  4 +-
 rocketpy/sensors/gyroscope.py     |  4 +-
 rocketpy/sensors/sensors.py       | 62 ++-----------------------------
 rocketpy/tools.py                 | 62 +++++++++++++++++++++++++++++++
 5 files changed, 74 insertions(+), 62 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 176f6d9ef..e1241406e 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -2,6 +2,8 @@
 
 import numpy as np
 
+from rocketpy.tools import export_sensors_measured_data
+
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _AccelerometerPrints
 from ..sensors.sensors import InertialSensors
@@ -267,6 +269,6 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        super().export_measured_data(
+        export_sensors_measured_data(
             filename=filename, format=format, data_labels=("t", "ax", "ay", "az")
         )
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index f7f70fb70..5eb2199c2 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -2,6 +2,8 @@
 
 import numpy as np
 
+from rocketpy.tools import export_sensors_measured_data
+
 from ..mathutils.vector_matrix import Matrix
 from ..prints.sensors_prints import _BarometerPrints
 from ..sensors.sensors import ScalarSensors
@@ -192,6 +194,6 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        super().export_measured_data(
+        export_sensors_measured_data(
             filename=filename, format=format, data_labels=("t", "pressure")
         )
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 007f0a797..f6b6db779 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -2,6 +2,8 @@
 
 import numpy as np
 
+from rocketpy.tools import export_sensors_measured_data
+
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
 from ..sensors.sensors import InertialSensors
@@ -299,6 +301,6 @@ def export_measured_data(self, filename, format="csv"):
         -------
         None
         """
-        super().export_measured_data(
+        export_sensors_measured_data(
             filename=filename, format=format, data_labels=("t", "wx", "wy", "wz")
         )
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 0f0cd8f1e..a29b932f3 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -202,65 +202,9 @@ def apply_temperature_drift(self, value):
         """Apply temperature drift to the sensor measurement"""
         pass
 
-    def export_measured_data(self, filename, format, data_labels):
-        """
-        Export the measured values to a file
-
-        Parameters
-        ----------
-        filename : str
-            Name of the file to export the values to
-        format : str
-            Format of the file to export the values to. Options are "csv" and
-            "json". Default is "csv".
-        data_labels : tuple
-            Tuple of strings representing the labels for the data columns
-
-        Returns
-        -------
-        None
-        """
-        if format.lower() not in ["json", "csv"]:
-            raise ValueError("Invalid format")
-
-        if format.lower() == "csv":
-            # if sensor has been added multiple times to the simulated rocket
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    with open(filename + f"_{i+1}", "w") as f:
-                        f.write(",".join(data_labels) + "\n")
-                        for entry in data:
-                            f.write(",".join(map(str, entry)) + "\n")
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                with open(filename, "w") as f:
-                    f.write(",".join(data_labels) + "\n")
-                    for entry in self.measured_data:
-                        f.write(",".join(map(str, entry)) + "\n")
-                print(f"Data saved to {filename}")
-            return
-
-        if format.lower() == "json":
-            if isinstance(self.measured_data[0], list):
-                print("Data saved to", end=" ")
-                for i, data in enumerate(self.measured_data):
-                    data_dict = {label: [] for label in data_labels}
-                    for entry in data:
-                        for label, value in zip(data_labels, entry):
-                            data_dict[label].append(value)
-                    with open(filename + f"_{i+1}", "w") as f:
-                        json.dump(data_dict, f)
-                    print(filename + f"_{i+1},", end=" ")
-            else:
-                data_dict = {label: [] for label in data_labels}
-                for entry in self.measured_data:
-                    for label, value in zip(data_labels, entry):
-                        data_dict[label].append(value)
-                with open(filename, "w") as f:
-                    json.dump(data_dict, f)
-                print(f"Data saved to {filename}")
-            return
+    @abstractmethod
+    def export_measured_data(self, filename, format="csv"):
+        pass
 
 
 class InertialSensors(Sensors):
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 0cbd16628..be70516c8 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -1,6 +1,7 @@
 import functools
 import importlib
 import importlib.metadata
+import json
 import math
 import re
 import time
@@ -522,6 +523,67 @@ def normalize_quaternions(quaternions):
     return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
 
 
+def export_sensors_measured_data(self, filename, format, data_labels):
+    """
+    Export the measured values to a file
+
+    Parameters
+    ----------
+    filename : str
+        Name of the file to export the values to
+    format : str
+        Format of the file to export the values to. Options are "csv" and
+        "json". Default is "csv".
+    data_labels : tuple
+        Tuple of strings representing the labels for the data columns
+
+    Returns
+    -------
+    None
+    """
+    if format.lower() not in ["json", "csv"]:
+        raise ValueError("Invalid format")
+
+    if format.lower() == "csv":
+        # if sensor has been added multiple times to the simulated rocket
+        if isinstance(self.measured_data[0], list):
+            print("Data saved to", end=" ")
+            for i, data in enumerate(self.measured_data):
+                with open(filename + f"_{i+1}", "w") as f:
+                    f.write(",".join(data_labels) + "\n")
+                    for entry in data:
+                        f.write(",".join(map(str, entry)) + "\n")
+                print(filename + f"_{i+1},", end=" ")
+        else:
+            with open(filename, "w") as f:
+                f.write(",".join(data_labels) + "\n")
+                for entry in self.measured_data:
+                    f.write(",".join(map(str, entry)) + "\n")
+            print(f"Data saved to {filename}")
+        return
+
+    if format.lower() == "json":
+        if isinstance(self.measured_data[0], list):
+            print("Data saved to", end=" ")
+            for i, data in enumerate(self.measured_data):
+                data_dict = {label: [] for label in data_labels}
+                for entry in data:
+                    for label, value in zip(data_labels, entry):
+                        data_dict[label].append(value)
+                with open(filename + f"_{i+1}", "w") as f:
+                    json.dump(data_dict, f)
+                print(filename + f"_{i+1},", end=" ")
+        else:
+            data_dict = {label: [] for label in data_labels}
+            for entry in self.measured_data:
+                for label, value in zip(data_labels, entry):
+                    data_dict[label].append(value)
+            with open(filename, "w") as f:
+                json.dump(data_dict, f)
+            print(f"Data saved to {filename}")
+        return
+
+
 if __name__ == "__main__":
     import doctest
 

From 3558effbe477cb89871c3f0e90424708a076693a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:35:41 +0200
Subject: [PATCH 098/120] MNT: pylint fixes

---
 rocketpy/control/controller.py    |  1 +
 rocketpy/prints/sensors_prints.py | 20 ++++----------------
 rocketpy/sensors/accelerometer.py | 15 ++++++++-------
 rocketpy/sensors/barometer.py     | 13 +++++++------
 rocketpy/sensors/gyroscope.py     | 17 +++++++++--------
 rocketpy/sensors/sensors.py       |  9 +++------
 rocketpy/tools.py                 | 28 +++++++++++++++-------------
 7 files changed, 47 insertions(+), 56 deletions(-)

diff --git a/rocketpy/control/controller.py b/rocketpy/control/controller.py
index c2617f8eb..93a13ecfd 100644
--- a/rocketpy/control/controller.py
+++ b/rocketpy/control/controller.py
@@ -101,6 +101,7 @@ def __init_controller_function(self, controller_function):
         sig = signature(controller_function)
         if len(sig.parameters) == 6:
 
+            # pylint: disable=unused-argument
             def new_controller_function(
                 time,
                 sampling_rate,
diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index af3979e04..89c851e3c 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -1,4 +1,4 @@
-from abc import ABC, abstractmethod
+from abc import ABC
 
 
 class _SensorsPrints(ABC):
@@ -32,7 +32,8 @@ def quantization(self):
         print("\nQuantization:\n")
         self._print_aligned(
             "Measurement Range:",
-            f"{self.sensor.measurement_range[0]} to {self.sensor.measurement_range[1]} ({self.units})",
+            f"{self.sensor.measurement_range[0]} "
+            + f"to {self.sensor.measurement_range[1]} ({self.units})",
         )
         self._print_aligned("Resolution:", f"{self.sensor.resolution} {self.units}/LSB")
 
@@ -78,8 +79,6 @@ def all(self):
 
 
 class _InertialSensorsPrints(_SensorsPrints):
-    def __init__(self, sensor):
-        super().__init__(sensor)
 
     def orientation(self):
         """Prints the orientation of the sensor."""
@@ -109,18 +108,10 @@ def all(self):
 class _AccelerometerPrints(_InertialSensorsPrints):
     """Class that contains all accelerometer prints."""
 
-    def __init__(self, accelerometer):
-        """Initialize the class."""
-        super().__init__(accelerometer)
-
 
 class _GyroscopePrints(_InertialSensorsPrints):
     """Class that contains all gyroscope prints."""
 
-    def __init__(self, gyroscope):
-        """Initialize the class."""
-        super().__init__(gyroscope)
-
     def noise(self):
         """Prints the noise of the sensor."""
         self._general_noise()
@@ -130,9 +121,6 @@ def noise(self):
         )
 
 
+# TODO: simplify prints
 class _BarometerPrints(_SensorsPrints):
     """Class that contains all barometer prints."""
-
-    def __init__(self, barometer):
-        """Initialize the class."""
-        super().__init__(barometer)
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index e1241406e..5a407f528 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -1,5 +1,3 @@
-import json
-
 import numpy as np
 
 from rocketpy.tools import export_sensors_measured_data
@@ -225,7 +223,7 @@ def measure(self, time, **kwargs):
         gravity = (
             Vector([0, 0, -gravity]) if self.consider_gravity else Vector([0, 0, 0])
         )
-        a_I = Vector(u_dot[3:6]) + gravity
+        inertial_acceleration = Vector(u_dot[3:6]) + gravity
 
         # Vector from rocket cdm to sensor in rocket frame
         r = relative_position
@@ -236,7 +234,7 @@ def measure(self, time, **kwargs):
 
         # Measured acceleration at sensor position in inertial frame
         A = (
-            a_I
+            inertial_acceleration
             + Vector.cross(omega_dot, r)
             + Vector.cross(omega, Vector.cross(omega, r))
         )
@@ -254,14 +252,14 @@ def measure(self, time, **kwargs):
         self.measurement = tuple([*A])
         self._save_data((time, *A))
 
-    def export_measured_data(self, filename, format="csv"):
+    def export_measured_data(self, filename, file_format="csv"):
         """Export the measured values to a file
 
         Parameters
         ----------
         filename : str
             Name of the file to export the values to
-        format : str
+        file_format : str
             Format of the file to export the values to. Options are "csv" and
             "json". Default is "csv".
 
@@ -270,5 +268,8 @@ def export_measured_data(self, filename, format="csv"):
         None
         """
         export_sensors_measured_data(
-            filename=filename, format=format, data_labels=("t", "ax", "ay", "az")
+            sensor=self,
+            filename=filename,
+            file_format=file_format,
+            data_labels=("t", "ax", "ay", "az"),
         )
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 5eb2199c2..2c143e982 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -1,5 +1,3 @@
-import json
-
 import numpy as np
 
 from rocketpy.tools import export_sensors_measured_data
@@ -179,15 +177,15 @@ def measure(self, time, **kwargs):
         self.measurement = P
         self._save_data((time, P))
 
-    def export_measured_data(self, filename, format="csv"):
+    def export_measured_data(self, filename, file_format="csv"):
         """Export the measured values to a file
 
         Parameters
         ----------
         filename : str
             Name of the file to export the values to
-        format : str
-            Format of the file to export the values to. Options are "csv" and
+        file_format : str
+            file_format of the file to export the values to. Options are "csv" and
             "json". Default is "csv".
 
         Returns
@@ -195,5 +193,8 @@ def export_measured_data(self, filename, format="csv"):
         None
         """
         export_sensors_measured_data(
-            filename=filename, format=format, data_labels=("t", "pressure")
+            sensor=self,
+            filename=filename,
+            file_format=file_format,
+            data_labels=("t", "pressure"),
         )
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index f6b6db779..92ba89d47 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -1,5 +1,3 @@
-import json
-
 import numpy as np
 
 from rocketpy.tools import export_sensors_measured_data
@@ -270,14 +268,14 @@ def apply_acceleration_sensitivity(
             The angular velocity with the acceleration sensitivity applied
         """
         # Linear acceleration of rocket cdm in inertial frame
-        a_I = Vector(u_dot[3:6])
+        inertial_acceleration = Vector(u_dot[3:6])
 
         # Angular velocity and accel of rocket
         omega_dot = Vector(u_dot[10:13])
 
         # Acceleration felt in sensor
         A = (
-            a_I
+            inertial_acceleration
             + Vector.cross(omega_dot, relative_position)
             + Vector.cross(omega, Vector.cross(omega, relative_position))
         )
@@ -286,15 +284,15 @@ def apply_acceleration_sensitivity(
 
         return self.acceleration_sensitivity & A
 
-    def export_measured_data(self, filename, format="csv"):
+    def export_measured_data(self, filename, file_format="csv"):
         """Export the measured values to a file
 
         Parameters
         ----------
         filename : str
             Name of the file to export the values to
-        format : str
-            Format of the file to export the values to. Options are "csv" and
+        file_format : str
+            file_Format of the file to export the values to. Options are "csv" and
             "json". Default is "csv".
 
         Returns
@@ -302,5 +300,8 @@ def export_measured_data(self, filename, format="csv"):
         None
         """
         export_sensors_measured_data(
-            filename=filename, format=format, data_labels=("t", "wx", "wy", "wz")
+            sensor=self,
+            filename=filename,
+            file_format=file_format,
+            data_labels=("t", "wx", "wy", "wz"),
         )
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index a29b932f3..8a3050d9d 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -1,4 +1,3 @@
-import json
 from abc import ABC, abstractmethod
 
 import numpy as np
@@ -181,10 +180,7 @@ def _save_data_multiple(self, data):
 
     @abstractmethod
     def measure(self, time, **kwargs):
-        pass
-
-    @abstractmethod
-    def export_measured_data(self):
+        """Measure the sensor data at a given time"""
         pass
 
     @abstractmethod
@@ -203,7 +199,8 @@ def apply_temperature_drift(self, value):
         pass
 
     @abstractmethod
-    def export_measured_data(self, filename, format="csv"):
+    def export_measured_data(self, filename, file_format="csv"):
+        """Export the measured values to a file"""
         pass
 
 
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index be70516c8..e540e3fd4 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -523,16 +523,18 @@ def normalize_quaternions(quaternions):
     return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
 
 
-def export_sensors_measured_data(self, filename, format, data_labels):
+def export_sensors_measured_data(sensor, filename, file_format, data_labels):
     """
     Export the measured values to a file
 
     Parameters
     ----------
+    sensor : Sensor
+        Sensor object to export the measured values from.
     filename : str
         Name of the file to export the values to
-    format : str
-        Format of the file to export the values to. Options are "csv" and
+    file_format : str
+        file_format of the file to export the values to. Options are "csv" and
         "json". Default is "csv".
     data_labels : tuple
         Tuple of strings representing the labels for the data columns
@@ -541,14 +543,14 @@ def export_sensors_measured_data(self, filename, format, data_labels):
     -------
     None
     """
-    if format.lower() not in ["json", "csv"]:
-        raise ValueError("Invalid format")
+    if file_format.lower() not in ["json", "csv"]:
+        raise ValueError("Invalid file_format")
 
-    if format.lower() == "csv":
+    if file_format.lower() == "csv":
         # if sensor has been added multiple times to the simulated rocket
-        if isinstance(self.measured_data[0], list):
+        if isinstance(sensor.measured_data[0], list):
             print("Data saved to", end=" ")
-            for i, data in enumerate(self.measured_data):
+            for i, data in enumerate(sensor.measured_data):
                 with open(filename + f"_{i+1}", "w") as f:
                     f.write(",".join(data_labels) + "\n")
                     for entry in data:
@@ -557,15 +559,15 @@ def export_sensors_measured_data(self, filename, format, data_labels):
         else:
             with open(filename, "w") as f:
                 f.write(",".join(data_labels) + "\n")
-                for entry in self.measured_data:
+                for entry in sensor.measured_data:
                     f.write(",".join(map(str, entry)) + "\n")
             print(f"Data saved to {filename}")
         return
 
-    if format.lower() == "json":
-        if isinstance(self.measured_data[0], list):
+    if file_format.lower() == "json":
+        if isinstance(sensor.measured_data[0], list):
             print("Data saved to", end=" ")
-            for i, data in enumerate(self.measured_data):
+            for i, data in enumerate(sensor.measured_data):
                 data_dict = {label: [] for label in data_labels}
                 for entry in data:
                     for label, value in zip(data_labels, entry):
@@ -575,7 +577,7 @@ def export_sensors_measured_data(self, filename, format, data_labels):
                 print(filename + f"_{i+1},", end=" ")
         else:
             data_dict = {label: [] for label in data_labels}
-            for entry in self.measured_data:
+            for entry in sensor.measured_data:
                 for label, value in zip(data_labels, entry):
                     data_dict[label].append(value)
             with open(filename, "w") as f:

From 7e419b096ebb0e058cef10ff85df1d09a8cef133 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:37:31 +0200
Subject: [PATCH 099/120] ENH: simplify sensors prints

---
 rocketpy/prints/sensors_prints.py | 9 ---------
 rocketpy/sensors/accelerometer.py | 6 +++---
 rocketpy/sensors/barometer.py     | 6 +++---
 3 files changed, 6 insertions(+), 15 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 89c851e3c..5c5f9a9b3 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -105,10 +105,6 @@ def all(self):
         self.noise()
 
 
-class _AccelerometerPrints(_InertialSensorsPrints):
-    """Class that contains all accelerometer prints."""
-
-
 class _GyroscopePrints(_InertialSensorsPrints):
     """Class that contains all gyroscope prints."""
 
@@ -119,8 +115,3 @@ def noise(self):
             "Acceleration Sensitivity:",
             f"{self.sensor.acceleration_sensitivity} rad/s/g",
         )
-
-
-# TODO: simplify prints
-class _BarometerPrints(_SensorsPrints):
-    """Class that contains all barometer prints."""
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 5a407f528..86d2a972f 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -3,7 +3,7 @@
 from rocketpy.tools import export_sensors_measured_data
 
 from ..mathutils.vector_matrix import Matrix, Vector
-from ..prints.sensors_prints import _AccelerometerPrints
+from ..prints.sensors_prints import _InertialSensorsPrints
 from ..sensors.sensors import InertialSensors
 
 
@@ -14,7 +14,7 @@ class Accelerometer(InertialSensors):
     ----------
     consider_gravity : bool
         Whether the sensor considers the effect of gravity on the acceleration.
-    prints : _AccelerometerPrints
+    prints : _InertialSensorsPrints
         Object that contains the print functions for the sensor.
     sampling_rate : float
         Sample rate of the sensor in Hz.
@@ -192,7 +192,7 @@ def __init__(
             name=name,
         )
         self.consider_gravity = consider_gravity
-        self.prints = _AccelerometerPrints(self)
+        self.prints = _InertialSensorsPrints(self)
 
     def measure(self, time, **kwargs):
         """Measure the acceleration of the rocket
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 2c143e982..79844a4b2 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -3,7 +3,7 @@
 from rocketpy.tools import export_sensors_measured_data
 
 from ..mathutils.vector_matrix import Matrix
-from ..prints.sensors_prints import _BarometerPrints
+from ..prints.sensors_prints import _SensorsPrints
 from ..sensors.sensors import ScalarSensors
 
 
@@ -14,7 +14,7 @@ class Barometer(ScalarSensors):
     ----------
     type : str
         Type of the sensor, in this case "Barometer".
-    prints : _BarometerPrints
+    prints : _SensorsPrints
         Object that contains the print functions for the sensor.
     sampling_rate : float
         Sample rate of the sensor in Hz.
@@ -137,7 +137,7 @@ def __init__(
             name=name,
         )
         self.type = "Barometer"
-        self.prints = _BarometerPrints(self)
+        self.prints = _SensorsPrints(self)
 
     def measure(self, time, **kwargs):
         """Measures the pressure at barometer location

From 4e5ad4e2ace90d62103d4aba70426cb73361c12a Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:42:24 +0200
Subject: [PATCH 100/120] MNT: rename sensors classes

---
 rocketpy/prints/sensors_prints.py |  6 +++---
 rocketpy/rocket/rocket.py         |  2 +-
 rocketpy/sensors/__init__.py      |  2 +-
 rocketpy/sensors/accelerometer.py | 10 +++++-----
 rocketpy/sensors/barometer.py     | 10 +++++-----
 rocketpy/sensors/gyroscope.py     |  4 ++--
 rocketpy/sensors/sensors.py       |  6 +++---
 tests/unit/test_sensors.py        | 10 +++++-----
 8 files changed, 25 insertions(+), 25 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index 5c5f9a9b3..ad9c693e9 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -1,7 +1,7 @@
 from abc import ABC
 
 
-class _SensorsPrints(ABC):
+class _SensorPrints(ABC):
     def __init__(self, sensor):
         self.sensor = sensor
         self.units = sensor.units
@@ -78,7 +78,7 @@ def all(self):
         self.noise()
 
 
-class _InertialSensorsPrints(_SensorsPrints):
+class _InertialSensorPrints(_SensorPrints):
 
     def orientation(self):
         """Prints the orientation of the sensor."""
@@ -105,7 +105,7 @@ def all(self):
         self.noise()
 
 
-class _GyroscopePrints(_InertialSensorsPrints):
+class _GyroscopePrints(_InertialSensorPrints):
     """Class that contains all gyroscope prints."""
 
     def noise(self):
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index c7bbd380a..117a6d95f 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -286,7 +286,7 @@ def __init__(
         self.thrust_eccentricity_y = 0
         self.thrust_eccentricity_x = 0
 
-        # Parachute, Aerodynamic, Buttons, Controllers, Sensors data initialization
+        # Parachute, Aerodynamic, Buttons, Controllers, Sensor data initialization
         self.parachutes = []
         self._controllers = []
         self.air_brakes = []
diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 50a105551..28d9273ec 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1,4 +1,4 @@
 from .accelerometer import Accelerometer
 from .barometer import Barometer
 from .gyroscope import Gyroscope
-from .sensors import InertialSensors, ScalarSensors, Sensors
+from .sensors import InertialSensor, ScalarSensor, Sensor
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 86d2a972f..ea58d65da 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -3,18 +3,18 @@
 from rocketpy.tools import export_sensors_measured_data
 
 from ..mathutils.vector_matrix import Matrix, Vector
-from ..prints.sensors_prints import _InertialSensorsPrints
-from ..sensors.sensors import InertialSensors
+from ..prints.sensors_prints import _InertialSensorPrints
+from ..sensors.sensors import InertialSensor
 
 
-class Accelerometer(InertialSensors):
+class Accelerometer(InertialSensor):
     """Class for the accelerometer sensor
 
     Attributes
     ----------
     consider_gravity : bool
         Whether the sensor considers the effect of gravity on the acceleration.
-    prints : _InertialSensorsPrints
+    prints : _InertialSensorPrints
         Object that contains the print functions for the sensor.
     sampling_rate : float
         Sample rate of the sensor in Hz.
@@ -192,7 +192,7 @@ def __init__(
             name=name,
         )
         self.consider_gravity = consider_gravity
-        self.prints = _InertialSensorsPrints(self)
+        self.prints = _InertialSensorPrints(self)
 
     def measure(self, time, **kwargs):
         """Measure the acceleration of the rocket
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 79844a4b2..615c8bacc 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -3,18 +3,18 @@
 from rocketpy.tools import export_sensors_measured_data
 
 from ..mathutils.vector_matrix import Matrix
-from ..prints.sensors_prints import _SensorsPrints
-from ..sensors.sensors import ScalarSensors
+from ..prints.sensors_prints import _SensorPrints
+from ..sensors.sensors import ScalarSensor
 
 
-class Barometer(ScalarSensors):
+class Barometer(ScalarSensor):
     """Class for the barometer sensor
 
     Attributes
     ----------
     type : str
         Type of the sensor, in this case "Barometer".
-    prints : _SensorsPrints
+    prints : _SensorPrints
         Object that contains the print functions for the sensor.
     sampling_rate : float
         Sample rate of the sensor in Hz.
@@ -137,7 +137,7 @@ def __init__(
             name=name,
         )
         self.type = "Barometer"
-        self.prints = _SensorsPrints(self)
+        self.prints = _SensorPrints(self)
 
     def measure(self, time, **kwargs):
         """Measures the pressure at barometer location
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 92ba89d47..09d35ccab 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -4,10 +4,10 @@
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
-from ..sensors.sensors import InertialSensors
+from ..sensors.sensors import InertialSensor
 
 
-class Gyroscope(InertialSensors):
+class Gyroscope(InertialSensor):
     """Class for the gyroscope sensor
 
     Attributes
diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensors.py
index 8a3050d9d..f8c185a13 100644
--- a/rocketpy/sensors/sensors.py
+++ b/rocketpy/sensors/sensors.py
@@ -5,7 +5,7 @@
 from rocketpy.mathutils.vector_matrix import Matrix, Vector
 
 
-class Sensors(ABC):
+class Sensor(ABC):
     """Abstract class for sensors
 
     Attributes
@@ -204,7 +204,7 @@ def export_measured_data(self, filename, file_format="csv"):
         pass
 
 
-class InertialSensors(Sensors):
+class InertialSensor(Sensor):
     """Abstract class for sensors
 
     Attributes
@@ -502,7 +502,7 @@ def apply_temperature_drift(self, value):
         return value & scale_factor
 
 
-class ScalarSensors(Sensors):
+class ScalarSensor(Sensor):
     """Abstract class for sensors
 
     Attributes
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 8d1a20dcc..8bb506d40 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -64,7 +64,7 @@ def test_sensors_prints(sensor, request):
 
 
 def test_rotation_matrix(noisy_rotated_accelerometer):
-    """Test the rotation_matrix property of the InertialSensors class. Checks if
+    """Test the rotation_matrix property of the InertialSensor class. Checks if
     the rotation matrix is correctly calculated.
     """
     # values from external source
@@ -80,7 +80,7 @@ def test_rotation_matrix(noisy_rotated_accelerometer):
 
 
 def test_inertial_quantization(quantized_accelerometer):
-    """Test the quantize method of the InertialSensors class. Checks if returned values
+    """Test the quantize method of the InertialSensor class. Checks if returned values
     are as expected.
     """
     # expected values calculated by hand
@@ -96,7 +96,7 @@ def test_inertial_quantization(quantized_accelerometer):
 
 
 def test_scalar_quantization(quantized_barometer):
-    """Test the quantize method of the ScalarSensors class. Checks if returned values
+    """Test the quantize method of the ScalarSensor class. Checks if returned values
     are as expected.
     """
     # expected values calculated by hand
@@ -157,7 +157,7 @@ def test_quantization(sensor, input_value, expected_output, request):
     ],
 )
 def test_inertial_measured_data(sensor, request):
-    """Test the measured_data property of the Sensors class. Checks if
+    """Test the measured_data property of the Sensor class. Checks if
     the measured data is treated properly when the sensor is added once or more
     than once to the rocket.
     """
@@ -209,7 +209,7 @@ def test_inertial_measured_data(sensor, request):
 
 
 def test_scalar_measured_data(ideal_barometer, example_plain_env):
-    """Test the measure method of ScalarSensors. Checks if saved
+    """Test the measure method of ScalarSensor. Checks if saved
     measurement is (P) and if measured_data is [(t, P), ...]
     """
     t = TIME

From 4a2eb07ecf8ef9c73a5034b2f3c253694d0792ac Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:44:23 +0200
Subject: [PATCH 101/120] MNT: sensor.py rename

---
 rocketpy/sensors/{sensors.py => sensor.py} | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename rocketpy/sensors/{sensors.py => sensor.py} (100%)

diff --git a/rocketpy/sensors/sensors.py b/rocketpy/sensors/sensor.py
similarity index 100%
rename from rocketpy/sensors/sensors.py
rename to rocketpy/sensors/sensor.py

From 642e1b3cd8adff40219bf2b41eaf548f4cf1d027 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:52:16 +0200
Subject: [PATCH 102/120] DOC: improve inertialsensor and scalar sensor doc

---
 rocketpy/sensors/sensor.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index f8c185a13..f49450d4d 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -205,7 +205,9 @@ def export_measured_data(self, filename, file_format="csv"):
 
 
 class InertialSensor(Sensor):
-    """Abstract class for sensors
+    """Model of an inertial sensor (accelerometer, gyroscope, magnetometer).
+    Inertial sensors measurements are handled as vectors. The measurements are
+    affected by the sensor's orientation in the rocket.
 
     Attributes
     ----------
@@ -503,12 +505,12 @@ def apply_temperature_drift(self, value):
 
 
 class ScalarSensor(Sensor):
-    """Abstract class for sensors
+    """Model of a scalar sensor (barometer, GPS, etc.). Scalar sensors are used
+    to measure a single scalar value. The measurements are not affected by the
+    sensor's orientation in the rocket.
 
     Attributes
     ----------
-    type : str
-        Type of the sensor (e.g. Barometer, GPS).
     sampling_rate : float
         Sample rate of the sensor in Hz.
     measurement_range : float, tuple

From 773ec595d85993c369d77795449b18d48f5f4df0 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 22:52:30 +0200
Subject: [PATCH 103/120] MNT: sensors to sensor rename imports

---
 rocketpy/sensors/__init__.py      | 2 +-
 rocketpy/sensors/accelerometer.py | 2 +-
 rocketpy/sensors/barometer.py     | 5 +----
 rocketpy/sensors/gyroscope.py     | 2 +-
 4 files changed, 4 insertions(+), 7 deletions(-)

diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 28d9273ec..40bac14cc 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1,4 +1,4 @@
 from .accelerometer import Accelerometer
 from .barometer import Barometer
 from .gyroscope import Gyroscope
-from .sensors import InertialSensor, ScalarSensor, Sensor
+from .sensor import InertialSensor, ScalarSensor, Sensor
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index ea58d65da..45f9edc13 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -4,7 +4,7 @@
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _InertialSensorPrints
-from ..sensors.sensors import InertialSensor
+from ..sensors.sensor import InertialSensor
 
 
 class Accelerometer(InertialSensor):
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 615c8bacc..695f32b1b 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -4,7 +4,7 @@
 
 from ..mathutils.vector_matrix import Matrix
 from ..prints.sensors_prints import _SensorPrints
-from ..sensors.sensors import ScalarSensor
+from ..sensors.sensor import ScalarSensor
 
 
 class Barometer(ScalarSensor):
@@ -12,8 +12,6 @@ class Barometer(ScalarSensor):
 
     Attributes
     ----------
-    type : str
-        Type of the sensor, in this case "Barometer".
     prints : _SensorPrints
         Object that contains the print functions for the sensor.
     sampling_rate : float
@@ -136,7 +134,6 @@ def __init__(
             temperature_scale_factor=temperature_scale_factor,
             name=name,
         )
-        self.type = "Barometer"
         self.prints = _SensorPrints(self)
 
     def measure(self, time, **kwargs):
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 09d35ccab..8655851e7 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -4,7 +4,7 @@
 
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
-from ..sensors.sensors import InertialSensor
+from ..sensors.sensor import InertialSensor
 
 
 class Gyroscope(InertialSensor):

From df02bb43df855168f183b0acb8c64ecf89f8b962 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 3 Jun 2024 23:01:32 +0200
Subject: [PATCH 104/120] TST: format argument

---
 tests/unit/test_sensors.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensors.py
index 8bb506d40..186466ccb 100644
--- a/tests/unit/test_sensors.py
+++ b/tests/unit/test_sensors.py
@@ -368,7 +368,7 @@ def test_noisy_barometer(noisy_barometer, example_plain_env):
 
 
 @pytest.mark.parametrize(
-    "sensor, format, expected_header, expected_keys",
+    "sensor, file_format, expected_header, expected_keys",
     [
         ("ideal_accelerometer", "csv", "t,ax,ay,az\n", ("ax", "ay", "az")),
         ("ideal_gyroscope", "csv", "t,wx,wy,wz\n", ("wx", "wy", "wz")),
@@ -379,10 +379,10 @@ def test_noisy_barometer(noisy_barometer, example_plain_env):
     ],
 )
 def test_export_data(
-    sensor, format, expected_header, expected_keys, request, example_plain_env
+    sensor, file_format, expected_header, expected_keys, request, example_plain_env
 ):
     """Test the export_data method of the sensors. Checks if the data is
-    exported correctly in the specified format.
+    exported correctly in the specified file_format.
     """
     sensor = request.getfixturevalue(sensor)
 
@@ -403,11 +403,11 @@ def test_export_data(
         pressure=example_plain_env.pressure,
     )
 
-    file_name = f"sensors.{format}"
+    file_name = f"sensors.{file_format}"
 
-    sensor.export_measured_data(file_name, format=format)
+    sensor.export_measured_data(file_name, file_format=file_format)
 
-    if format == "csv":
+    if file_format == "csv":
         with open(file_name, "r") as file:
             contents = file.read()
 
@@ -417,7 +417,7 @@ def test_export_data(
 
         assert contents == expected_data
 
-    elif format == "json":
+    elif file_format == "json":
         with open(file_name, "r") as file:
             contents = json.load(file)
 
@@ -437,9 +437,9 @@ def test_export_data(
         sensor.measured_data[:],
         sensor.measured_data[:],
     ]
-    sensor.export_measured_data(file_name, format=format)
+    sensor.export_measured_data(file_name, file_format=file_format)
 
-    if format == "csv":
+    if file_format == "csv":
         with open(f"{file_name}_1", "r") as file:
             contents = file.read()
         assert contents == expected_data
@@ -448,7 +448,7 @@ def test_export_data(
             contents = file.read()
         assert contents == expected_data
 
-    elif format == "json":
+    elif file_format == "json":
         with open(f"{file_name}_1", "r") as file:
             contents = json.load(file)
         assert contents == expected_data

From 332b47711c3314b8d69a6fc38ab6bf01c915ab20 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 6 Jun 2024 19:37:18 +0200
Subject: [PATCH 105/120] ENH: move generic_export_data back to Sensor class

---
 rocketpy/sensors/accelerometer.py |  5 +--
 rocketpy/sensors/barometer.py     |  5 +--
 rocketpy/sensors/gyroscope.py     |  5 +--
 rocketpy/sensors/sensor.py        | 63 ++++++++++++++++++++++++++++++
 rocketpy/tools.py                 | 64 -------------------------------
 5 files changed, 66 insertions(+), 76 deletions(-)

diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index 45f9edc13..ccb9073f4 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -1,7 +1,5 @@
 import numpy as np
 
-from rocketpy.tools import export_sensors_measured_data
-
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _InertialSensorPrints
 from ..sensors.sensor import InertialSensor
@@ -267,8 +265,7 @@ def export_measured_data(self, filename, file_format="csv"):
         -------
         None
         """
-        export_sensors_measured_data(
-            sensor=self,
+        self._generic_export_measured_data(
             filename=filename,
             file_format=file_format,
             data_labels=("t", "ax", "ay", "az"),
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 695f32b1b..0439f3f70 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -1,7 +1,5 @@
 import numpy as np
 
-from rocketpy.tools import export_sensors_measured_data
-
 from ..mathutils.vector_matrix import Matrix
 from ..prints.sensors_prints import _SensorPrints
 from ..sensors.sensor import ScalarSensor
@@ -189,8 +187,7 @@ def export_measured_data(self, filename, file_format="csv"):
         -------
         None
         """
-        export_sensors_measured_data(
-            sensor=self,
+        self._generic_export_measured_data(
             filename=filename,
             file_format=file_format,
             data_labels=("t", "pressure"),
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 8655851e7..6bf6945d4 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -1,7 +1,5 @@
 import numpy as np
 
-from rocketpy.tools import export_sensors_measured_data
-
 from ..mathutils.vector_matrix import Matrix, Vector
 from ..prints.sensors_prints import _GyroscopePrints
 from ..sensors.sensor import InertialSensor
@@ -299,8 +297,7 @@ def export_measured_data(self, filename, file_format="csv"):
         -------
         None
         """
-        export_sensors_measured_data(
-            sensor=self,
+        self._generic_export_measured_data(
             filename=filename,
             file_format=file_format,
             data_labels=("t", "wx", "wy", "wz"),
diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index f49450d4d..b9277dfc4 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -1,3 +1,4 @@
+import json
 from abc import ABC, abstractmethod
 
 import numpy as np
@@ -203,6 +204,68 @@ def export_measured_data(self, filename, file_format="csv"):
         """Export the measured values to a file"""
         pass
 
+    def _generic_export_measured_data(self, filename, file_format, data_labels):
+        """Export the measured values to a file given the data labels of each
+        sensor.
+
+        Parameters
+        ----------
+        sensor : Sensor
+            Sensor object to export the measured values from.
+        filename : str
+            Name of the file to export the values to
+        file_format : str
+            file_format of the file to export the values to. Options are "csv"
+            and "json". Default is "csv".
+        data_labels : tuple
+            Tuple of strings representing the labels for the data columns
+
+        Returns
+        -------
+        None
+        """
+        if file_format.lower() not in ["json", "csv"]:
+            raise ValueError("Invalid file_format")
+
+        if file_format.lower() == "csv":
+            # if sensor has been added multiple times to the simulated rocket
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    with open(filename + f"_{i+1}", "w") as f:
+                        f.write(",".join(data_labels) + "\n")
+                        for entry in data:
+                            f.write(",".join(map(str, entry)) + "\n")
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                with open(filename, "w") as f:
+                    f.write(",".join(data_labels) + "\n")
+                    for entry in self.measured_data:
+                        f.write(",".join(map(str, entry)) + "\n")
+                print(f"Data saved to {filename}")
+            return
+
+        if file_format.lower() == "json":
+            if isinstance(self.measured_data[0], list):
+                print("Data saved to", end=" ")
+                for i, data in enumerate(self.measured_data):
+                    data_dict = {label: [] for label in data_labels}
+                    for entry in data:
+                        for label, value in zip(data_labels, entry):
+                            data_dict[label].append(value)
+                    with open(filename + f"_{i+1}", "w") as f:
+                        json.dump(data_dict, f)
+                    print(filename + f"_{i+1},", end=" ")
+            else:
+                data_dict = {label: [] for label in data_labels}
+                for entry in self.measured_data:
+                    for label, value in zip(data_labels, entry):
+                        data_dict[label].append(value)
+                with open(filename, "w") as f:
+                    json.dump(data_dict, f)
+                print(f"Data saved to {filename}")
+            return
+
 
 class InertialSensor(Sensor):
     """Model of an inertial sensor (accelerometer, gyroscope, magnetometer).
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index e540e3fd4..0cbd16628 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -1,7 +1,6 @@
 import functools
 import importlib
 import importlib.metadata
-import json
 import math
 import re
 import time
@@ -523,69 +522,6 @@ def normalize_quaternions(quaternions):
     return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
 
 
-def export_sensors_measured_data(sensor, filename, file_format, data_labels):
-    """
-    Export the measured values to a file
-
-    Parameters
-    ----------
-    sensor : Sensor
-        Sensor object to export the measured values from.
-    filename : str
-        Name of the file to export the values to
-    file_format : str
-        file_format of the file to export the values to. Options are "csv" and
-        "json". Default is "csv".
-    data_labels : tuple
-        Tuple of strings representing the labels for the data columns
-
-    Returns
-    -------
-    None
-    """
-    if file_format.lower() not in ["json", "csv"]:
-        raise ValueError("Invalid file_format")
-
-    if file_format.lower() == "csv":
-        # if sensor has been added multiple times to the simulated rocket
-        if isinstance(sensor.measured_data[0], list):
-            print("Data saved to", end=" ")
-            for i, data in enumerate(sensor.measured_data):
-                with open(filename + f"_{i+1}", "w") as f:
-                    f.write(",".join(data_labels) + "\n")
-                    for entry in data:
-                        f.write(",".join(map(str, entry)) + "\n")
-                print(filename + f"_{i+1},", end=" ")
-        else:
-            with open(filename, "w") as f:
-                f.write(",".join(data_labels) + "\n")
-                for entry in sensor.measured_data:
-                    f.write(",".join(map(str, entry)) + "\n")
-            print(f"Data saved to {filename}")
-        return
-
-    if file_format.lower() == "json":
-        if isinstance(sensor.measured_data[0], list):
-            print("Data saved to", end=" ")
-            for i, data in enumerate(sensor.measured_data):
-                data_dict = {label: [] for label in data_labels}
-                for entry in data:
-                    for label, value in zip(data_labels, entry):
-                        data_dict[label].append(value)
-                with open(filename + f"_{i+1}", "w") as f:
-                    json.dump(data_dict, f)
-                print(filename + f"_{i+1},", end=" ")
-        else:
-            data_dict = {label: [] for label in data_labels}
-            for entry in sensor.measured_data:
-                for label, value in zip(data_labels, entry):
-                    data_dict[label].append(value)
-            with open(filename, "w") as f:
-                json.dump(data_dict, f)
-            print(f"Data saved to {filename}")
-        return
-
-
 if __name__ == "__main__":
     import doctest
 

From 1d5e76952fa3386b99987d093708e4579affc2e9 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 6 Jun 2024 19:38:34 +0200
Subject: [PATCH 106/120] ENH: rename test files

---
 tests/{test_sensors.py => test_sensor.py}      | 0
 tests/unit/{test_sensors.py => test_sensor.py} | 0
 2 files changed, 0 insertions(+), 0 deletions(-)
 rename tests/{test_sensors.py => test_sensor.py} (100%)
 rename tests/unit/{test_sensors.py => test_sensor.py} (100%)

diff --git a/tests/test_sensors.py b/tests/test_sensor.py
similarity index 100%
rename from tests/test_sensors.py
rename to tests/test_sensor.py
diff --git a/tests/unit/test_sensors.py b/tests/unit/test_sensor.py
similarity index 100%
rename from tests/unit/test_sensors.py
rename to tests/unit/test_sensor.py

From 7f0fe70cea1e28c8f8d79f178d05f7b38451a71b Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 13 Jun 2024 15:26:57 +0200
Subject: [PATCH 107/120] ENH: change from celsius to kelvin

---
 rocketpy/prints/sensors_prints.py |  6 ++--
 rocketpy/sensors/accelerometer.py | 15 +++++----
 rocketpy/sensors/barometer.py     | 15 +++++----
 rocketpy/sensors/gyroscope.py     | 15 +++++----
 rocketpy/sensors/sensor.py        | 53 +++++++++++++++++--------------
 5 files changed, 56 insertions(+), 48 deletions(-)

diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index ad9c693e9..a454aa0fa 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -62,13 +62,13 @@ def _general_noise(self):
             "Constant Bias:", f"{self.sensor.constant_bias} {self.units}"
         )
         self._print_aligned(
-            "Operating Temperature:", f"{self.sensor.operating_temperature} °C"
+            "Operating Temperature:", f"{self.sensor.operating_temperature} K"
         )
         self._print_aligned(
-            "Temperature Bias:", f"{self.sensor.temperature_bias} {self.units}/°C"
+            "Temperature Bias:", f"{self.sensor.temperature_bias} {self.units}/K"
         )
         self._print_aligned(
-            "Temperature Scale Factor:", f"{self.sensor.temperature_scale_factor} %/°C"
+            "Temperature Scale Factor:", f"{self.sensor.temperature_scale_factor} %/K"
         )
 
     def all(self):
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index ccb9073f4..bf67c88c1 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -33,11 +33,11 @@ class Accelerometer(InertialSensor):
     constant_bias : float, list
         The constant bias of the sensor in m/s^2.
     operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
+        The operating temperature of the sensor in Kelvin.
     temperature_bias : float, list
-        The temperature bias of the sensor in m/s^2/°C.
+        The temperature bias of the sensor in m/s^2/K.
     temperature_scale_factor : float, list
-        The temperature scale factor of the sensor in %/°C.
+        The temperature scale factor of the sensor in %/K.
     cross_axis_sensitivity : float
         The cross axis sensitivity of the sensor in percentage.
     name : str
@@ -143,15 +143,16 @@ def __init__(
             is applied to all axes. The values of each axis can be set
             individually by passing a list of length 3.
         operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
+            The operating temperature of the sensor in Kelvin.
+            At 298.15 K (25 °C), the sensor is assumed to operate ideally, no
+            temperature related noise is applied. Default is 298.15.
         temperature_bias : float, list, optional
-            The temperature bias of the sensor in m/s^2/°C. Default is 0,
+            The temperature bias of the sensor in m/s^2/K. Default is 0,
             meaning no temperature bias is applied. If a float or int is given,
             the same temperature bias is applied to all axes. The values of each
             axis can be set individually by passing a list of length 3.
         temperature_scale_factor : float, list, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
+            The temperature scale factor of the sensor in %/K. Default is 0,
             meaning no temperature scale factor is applied. If a float or int is
             given, the same temperature scale factor is applied to all axes. The
             values of each axis can be set individually by passing a list of
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 0439f3f70..fbed17f56 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -31,11 +31,11 @@ class Barometer(ScalarSensor):
     constant_bias : float
         The constant bias of the sensor in Pa.
     operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
+        The operating temperature of the sensor in Kelvin.
     temperature_bias : float
-        The temperature bias of the sensor in Pa/°C.
+        The temperature bias of the sensor in Pa/K.
     temperature_scale_factor : float
-        The temperature scale factor of the sensor in %/°C.
+        The temperature scale factor of the sensor in %/K.
     name : str
         The name of the sensor.
     measurement : float
@@ -99,13 +99,14 @@ def __init__(
             The constant bias of the sensor in Pa. Default is 0, meaning no
             constant bias is applied.
         operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
+            The operating temperature of the sensor in Kelvin.
+            At 298.15 K (25 °C), the sensor is assumed to operate ideally, no
+            temperature related noise is applied. Default is 298.15.
         temperature_bias : float, optional
-            The temperature bias of the sensor in Pa/°C. Default is 0, meaning no
+            The temperature bias of the sensor in Pa/K. Default is 0, meaning no
             temperature bias is applied.
         temperature_scale_factor : float, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
+            The temperature scale factor of the sensor in %/K. Default is 0,
             meaning no temperature scale factor is applied.
         name : str, optional
             The name of the sensor. Default is "Barometer".
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 6bf6945d4..049cde52d 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -33,11 +33,11 @@ class Gyroscope(InertialSensor):
     constant_bias : float, list
         The constant bias of the sensor in rad/s.
     operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
+        The operating temperature of the sensor in Kelvin.
     temperature_bias : float, list
-        The temperature bias of the sensor in rad/s/°C.
+        The temperature bias of the sensor in rad/s/K.
     temperature_scale_factor : float, list
-        The temperature scale factor of the sensor in %/°C.
+        The temperature scale factor of the sensor in %/K.
     cross_axis_sensitivity : float
         The cross axis sensitivity of the sensor in percentage.
     name : str
@@ -141,15 +141,16 @@ def __init__(
             is applied to all axes. The values of each axis can be set
             individually by passing a list of length 3.
         operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
+            The operating temperature of the sensor in Kelvin.
+            At 298.15 K (25 °C), the sensor is assumed to operate ideally, no
+            temperature related noise is applied. Default is 298.15.
         temperature_sensitivity : float, list, optional
-            The temperature bias of the sensor in rad/s/°C. Default is 0,
+            The temperature bias of the sensor in rad/s/K. Default is 0,
             meaning no temperature bias is applied. If a float or int is given,
             the same temperature bias is applied to all axes. The values of each
             axis can be set individually by passing a list of length 3.
         temperature_scale_factor : float, list, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
+            The temperature scale factor of the sensor in %/K. Default is 0,
             meaning no temperature scale factor is applied. If a float or int is
             given, the same temperature scale factor is applied to all axes. The
             values of each axis can be set individually by passing a list of
diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index b9277dfc4..11147f7bc 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -28,11 +28,11 @@ class Sensor(ABC):
     constant_bias : float, list
         The constant bias of the sensor in sensor units.
     operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
+        The operating temperature of the sensor in Kelvin.
     temperature_bias : float, list
-        The temperature bias of the sensor in sensor units/°C.
+        The temperature bias of the sensor in sensor units/K.
     temperature_scale_factor : float, list
-        The temperature scale factor of the sensor in %/°C.
+        The temperature scale factor of the sensor in %/K.
     name : str
         The name of the sensor.
     measurement : float
@@ -95,13 +95,14 @@ def __init__(
             The constant bias of the sensor in sensor units. Default is 0,
             meaning no constant bias is applied.
         operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
+            The operating temperature of the sensor in Kelvin.
+            At 298.15 K (25 °C), the sensor is assumed to operate ideally, no
+            temperature related noise is applied. Default is 298.15.
         temperature_bias : float, list, optional
-            The temperature bias of the sensor in sensor units/°C. Default is 0,
+            The temperature bias of the sensor in sensor units/K. Default is 0,
             meaning no temperature bias is applied.
         temperature_scale_factor : float, list, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
+            The temperature scale factor of the sensor in %/K. Default is 0,
             meaning no temperature scale factor is applied.
         name : str, optional
             The name of the sensor. Default is "Sensor".
@@ -293,11 +294,11 @@ class InertialSensor(Sensor):
     constant_bias : float, list
         The constant bias of the sensor in sensor units.
     operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
+        The operating temperature of the sensor in Kelvin.
     temperature_bias : float, list
-        The temperature bias of the sensor in sensor units/°C.
+        The temperature bias of the sensor in sensor units/K.
     temperature_scale_factor : float, list
-        The temperature scale factor of the sensor in %/°C.
+        The temperature scale factor of the sensor in %/K.
     cross_axis_sensitivity : float
         The cross axis sensitivity of the sensor in percentage.
     name : str
@@ -326,7 +327,7 @@ def __init__(
         random_walk_density=0,
         random_walk_variance=1,
         constant_bias=0,
-        operating_temperature=25,
+        operating_temperature=298.15,
         temperature_bias=0,
         temperature_scale_factor=0,
         cross_axis_sensitivity=0,
@@ -400,15 +401,16 @@ def __init__(
             same constant bias is applied to all axes. The values of each axis
             can be set individually by passing a list of length 3.
         operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
+            The operating temperature of the sensor in Kelvin.
+            At 298.15 K (25 °C), the sensor is assumed to operate ideally, no
+            temperature related noise is applied. Default is 298.15.
         temperature_bias : float, list, optional
-            The temperature bias of the sensor in sensor units/°C. Default is 0,
+            The temperature bias of the sensor in sensor units/K. Default is 0,
             meaning no temperature bias is applied. If a float or int is given,
             the same temperature bias is applied to all axes. The values of each
             axis can be set individually by passing a list of length 3.
         temperature_scale_factor : float, list, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
+            The temperature scale factor of the sensor in %/K. Default is 0,
             meaning no temperature scale factor is applied. If a float or int is
             given, the same temperature scale factor is applied to all axes. The
             values of each axis can be set individually by passing a list of
@@ -558,11 +560,13 @@ def apply_temperature_drift(self, value):
             The value with applied temperature drift
         """
         # temperature drift
-        value += (self.operating_temperature - 25) * self.temperature_bias
+        value += (self.operating_temperature - 298.15) * self.temperature_bias
         # temperature scale factor
         scale_factor = (
             Vector([1, 1, 1])
-            + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
+            + (self.operating_temperature - 298.15)
+            / 100
+            * self.temperature_scale_factor
         )
         return value & scale_factor
 
@@ -591,11 +595,11 @@ class ScalarSensor(Sensor):
     constant_bias : float
         The constant bias of the sensor in sensor units.
     operating_temperature : float
-        The operating temperature of the sensor in degrees Celsius.
+        The operating temperature of the sensor in Kelvin.
     temperature_bias : float
-        The temperature bias of the sensor in sensor units/°C.
+        The temperature bias of the sensor in sensor units/K.
     temperature_scale_factor : float
-        The temperature scale factor of the sensor in %/°C.
+        The temperature scale factor of the sensor in %/K.
     name : str
         The name of the sensor.
     measurement : float
@@ -658,13 +662,14 @@ def __init__(
             The constant bias of the sensor in sensor units. Default is 0,
             meaning no constant bias is applied.
         operating_temperature : float, optional
-            The operating temperature of the sensor in degrees Celsius. At 25°C,
-            the temperature bias and scale factor are 0. Default is 25.
+            The operating temperature of the sensor in Kelvin.
+            At 298.15 K (25 °C), the sensor is assumed to operate ideally, no
+            temperature related noise is applied. Default is 298.15.
         temperature_bias : float, list, optional
-            The temperature bias of the sensor in sensor units/°C. Default is 0,
+            The temperature bias of the sensor in sensor units/K. Default is 0,
             meaning no temperature bias is applied.
         temperature_scale_factor : float, list, optional
-            The temperature scale factor of the sensor in %/°C. Default is 0,
+            The temperature scale factor of the sensor in %/K. Default is 0,
             meaning no temperature scale factor is applied.
         name : str, optional
             The name of the sensor. Default is "Sensor".

From 0b779f2e159ae5c245d61c25768c93f92c3a11ce Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Thu, 13 Jun 2024 16:50:21 +0200
Subject: [PATCH 108/120] TST: fix celsius to kelvin convertion

---
 rocketpy/sensors/sensor.py                 | 7 +++++--
 tests/fixtures/sensors/sensors_fixtures.py | 6 +++---
 2 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index 11147f7bc..8b0de3b6e 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -765,10 +765,13 @@ def apply_temperature_drift(self, value):
             The value with applied temperature drift
         """
         # temperature drift
-        value += (self.operating_temperature - 25) * self.temperature_bias
+        value += (self.operating_temperature - 298.15) * self.temperature_bias
         # temperature scale factor
         scale_factor = (
-            1 + (self.operating_temperature - 25) / 100 * self.temperature_scale_factor
+            1
+            + (self.operating_temperature - 298.15)
+            / 100
+            * self.temperature_scale_factor
         )
         value = value * scale_factor
 
diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
index 08982c9d4..5f148d00b 100644
--- a/tests/fixtures/sensors/sensors_fixtures.py
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -18,7 +18,7 @@ def noisy_rotated_accelerometer():
         random_walk_density=[0, 0.01, 0.02],
         random_walk_variance=[1, 1, 1.05],
         constant_bias=[0, 0.3, 0.5],
-        operating_temperature=25,
+        operating_temperature=25 + 273.15,
         temperature_bias=[0, 0.01, 0.02],
         temperature_scale_factor=[0, 0.01, 0.02],
         cross_axis_sensitivity=0.5,
@@ -40,7 +40,7 @@ def noisy_rotated_gyroscope():
         random_walk_density=[0, 0.01, 0.02],
         random_walk_variance=[1, 1, 1.05],
         constant_bias=[0, 0.3, 0.5],
-        operating_temperature=25,
+        operating_temperature=25 + 273.15,
         temperature_bias=[0, 0.01, 0.02],
         temperature_scale_factor=[0, 0.01, 0.02],
         cross_axis_sensitivity=0.5,
@@ -59,7 +59,7 @@ def noisy_barometer():
         noise_variance=19,
         random_walk_density=0.01,
         constant_bias=1000,
-        operating_temperature=25,
+        operating_temperature=25 + 273.15,
         temperature_bias=0.02,
         temperature_scale_factor=0.02,
     )

From 5db0ef3c4a63d23b7148471eebf46d837a3e74d4 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 14 Jun 2024 19:19:35 +0200
Subject: [PATCH 109/120] merge develop

---
 .coveragerc                                   |    4 -
 .flake8                                       |    5 -
 .github/workflows/test_pytest.yaml            |    2 +
 .readthedocs.yaml                             |    4 +-
 CHANGELOG.md                                  |   34 +-
 data/motors/cesaroni/Cesaroni_7579M1520-P.eng |   13 +
 ...-24-serial-5115-flight-0001-TeleMetrum.csv | 7082 +++++++++++++++++
 ...06-24-serial-6583-flight-0003-TeleMega.csv | 6235 +++++++++++++++
 docs/conf.py                                  |   12 +-
 docs/examples/index.rst                       |    1 +
 .../examples/prometheus_2022_flight_sim.ipynb |  696 ++
 docs/index.rst                                |  100 +-
 .../monte_carlo_analysis.ipynb}               |   21 +-
 .../Cd_PowerOff.csv                           |    0
 .../Cd_PowerOn.csv                            |    0
 .../LASC2019_reanalysis.nc                    |  Bin
 .../Valetudo_basemap_final.jpg                |  Bin
 .../thrustCurve.csv                           |    0
 .../monte_carlo_class_example.errors.txt      |    0
 .../monte_carlo_class_example.inputs.txt      | 1000 +++
 .../monte_carlo_class_example.kml             |   86 +
 .../monte_carlo_class_example.outputs.txt     | 1000 +++
 ...chute_drop_from_helicopter.disp_errors.txt |    0
 ...chute_drop_from_helicopter.disp_inputs.txt |    0
 ...hute_drop_from_helicopter.disp_outputs.txt |    0
 .../parachute_drop_from_helicopter.svg        |    0
 .../valetudo_rocket_v0.disp_errors.txt        |    0
 .../valetudo_rocket_v0.disp_inputs.txt        |    0
 .../valetudo_rocket_v0.disp_outputs.txt       |    0
 .../valetudo_rocket_v0.svg                    |    0
 .../monte_carlo_class_usage.ipynb             | 1406 ++++
 .../parachute_drop_from_helicopter.ipynb      |   21 +-
 docs/reference/classes/monte_carlo/index.rst  |    9 +
 .../classes/monte_carlo/monte_carlo.rst       |    5 +
 .../monte_carlo/stochastic_models/index.rst   |   26 +
 .../stochastic_elliptical_fins.rst            |    5 +
 .../stochastic_environment.rst                |    5 +
 .../stochastic_models/stochastic_flight.rst   |    5 +
 .../stochastic_generic_motor.rst              |    5 +
 .../stochastic_models/stochastic_model.rst    |    7 +
 .../stochastic_motor_model.rst                |    5 +
 .../stochastic_nose_cone.rst                  |    5 +
 .../stochastic_parachute.rst                  |    5 +
 .../stochastic_rail_buttons.rst               |    5 +
 .../stochastic_models/stochastic_rocket.rst   |    5 +
 .../stochastic_solid_motor.rst                |    5 +
 .../stochastic_models/stochastic_tail.rst     |    5 +
 .../stochastic_trapezoidal_fins.rst           |    5 +
 docs/reference/index.rst                      |    1 +
 docs/requirements.in                          |    7 +
 docs/requirements.txt                         |  254 +-
 docs/static/landing_images/api.svg            |   31 +
 docs/static/landing_images/contributor.svg    |    1 +
 .../static/landing_images/getting_started.svg |   31 +
 docs/static/landing_images/user_guide.svg     |    1 +
 docs/static/notebooks.css                     |    5 -
 docs/static/rocketpy.css                      |   80 +
 docs/user/first_simulation.rst                |    2 +-
 docs/user/function.rst                        |   14 +
 docs/user/index.rst                           |    8 +-
 docs/user/installation.rst                    |    6 +-
 docs/user/rocket.rst                          |   52 +
 docs/user/stochastic.rst                      |  249 +
 pyproject.toml                                |   77 +
 requirements-optional.txt                     |    3 +-
 requirements-tests.txt                        |    3 +-
 rocketpy/__init__.py                          |   13 +-
 rocketpy/_encoders.py                         |   43 +
 rocketpy/environment/environment.py           |   63 +-
 rocketpy/mathutils/function.py                |  997 ++-
 rocketpy/motors/solid_motor.py                |    2 +-
 rocketpy/plots/environment_analysis_plots.py  |    2 +-
 rocketpy/plots/monte_carlo_plots.py           |  165 +
 rocketpy/plots/rocket_plots.py                |   20 +-
 rocketpy/prints/monte_carlo_prints.py         |   27 +
 rocketpy/rocket/aero_surface.py               |   76 +-
 rocketpy/rocket/parachute.py                  |    6 +
 rocketpy/rocket/rocket.py                     |  153 +-
 rocketpy/simulation/__init__.py               |    1 +
 rocketpy/simulation/flight.py                 | 1272 ++-
 rocketpy/simulation/monte_carlo.py            |  876 ++
 rocketpy/stochastic/__init__.py               |   21 +
 .../stochastic/stochastic_aero_surfaces.py    |  434 +
 rocketpy/stochastic/stochastic_environment.py |  188 +
 rocketpy/stochastic/stochastic_flight.py      |  131 +
 .../stochastic/stochastic_generic_motor.py    |  193 +
 rocketpy/stochastic/stochastic_model.py       |  536 ++
 rocketpy/stochastic/stochastic_motor_model.py |   19 +
 rocketpy/stochastic/stochastic_parachute.py   |  121 +
 rocketpy/stochastic/stochastic_rocket.py      |  586 ++
 rocketpy/stochastic/stochastic_solid_motor.py |  222 +
 rocketpy/tools.py                             |  459 ++
 setup.py                                      |   46 -
 tests/acceptance/test_bella_lui_rocket.py     |   12 +-
 tests/acceptance/test_prometheus_rocket.py    |   70 +
 tests/conftest.py                             |    4 +
 .../environment/environment_fixtures.py       |   27 +
 .../Valetudo_inputs.csv                       |    0
 tests/fixtures/monte_carlo/__init__.py        |    0
 tests/fixtures/monte_carlo/example.inputs.txt |   10 +
 .../fixtures/monte_carlo/example.outputs.txt  |   10 +
 .../monte_carlo/monte_carlo_fixtures.py       |   34 +
 .../monte_carlo/stochastic_fixtures.py        |  236 +
 .../monte_carlo/stochastic_motors_fixtures.py |   78 +
 .../fixtures/motor/generic_motor_fixtures.py  |   24 +
 tests/fixtures/rockets/rocket_fixtures.py     |   79 +
 tests/test_flight.py                          |   24 +-
 tests/test_function.py                        |   30 +-
 tests/test_monte_carlo.py                     |  171 +
 tests/unit/__init__.py                        |    0
 tests/unit/stochastic/__init__.py             |    0
 .../test_stochastic_aero_surfaces.py          |   92 +
 .../stochastic/test_stochastic_environment.py |   43 +
 .../unit/stochastic/test_stochastic_flight.py |    6 +
 .../unit/stochastic/test_stochastic_motors.py |    6 +
 .../stochastic/test_stochastic_parachute.py   |   21 +
 .../unit/stochastic/test_stochastic_rocket.py |   25 +
 tests/unit/test_flight_time_nodes.py          |  103 +
 tests/unit/test_function.py                   |   59 +
 tests/unit/test_rocket.py                     |   83 +
 tests/unit/test_stochastic_model.py           |   20 +
 tests/unit/test_tools.py                      |   48 +
 tests/unit/test_utilities.py                  |    8 +-
 123 files changed, 25137 insertions(+), 1512 deletions(-)
 delete mode 100644 .coveragerc
 delete mode 100644 .flake8
 create mode 100644 data/motors/cesaroni/Cesaroni_7579M1520-P.eng
 create mode 100644 data/prometheus/2022-06-24-serial-5115-flight-0001-TeleMetrum.csv
 create mode 100644 data/prometheus/2022-06-24-serial-6583-flight-0003-TeleMega.csv
 create mode 100644 docs/examples/prometheus_2022_flight_sim.ipynb
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis.ipynb => monte_carlo_analysis/monte_carlo_analysis.ipynb} (99%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_inputs => monte_carlo_analysis/monte_carlo_analysis_inputs}/Cd_PowerOff.csv (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_inputs => monte_carlo_analysis/monte_carlo_analysis_inputs}/Cd_PowerOn.csv (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_inputs => monte_carlo_analysis/monte_carlo_analysis_inputs}/LASC2019_reanalysis.nc (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_inputs => monte_carlo_analysis/monte_carlo_analysis_inputs}/Valetudo_basemap_final.jpg (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_inputs => monte_carlo_analysis/monte_carlo_analysis_inputs}/thrustCurve.csv (100%)
 create mode 100644 docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.errors.txt
 create mode 100644 docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.inputs.txt
 create mode 100644 docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.kml
 create mode 100644 docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.outputs.txt
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/parachute_drop_from_helicopter.disp_errors.txt (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/parachute_drop_from_helicopter.disp_inputs.txt (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/parachute_drop_from_helicopter.disp_outputs.txt (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/parachute_drop_from_helicopter.svg (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/valetudo_rocket_v0.disp_errors.txt (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/valetudo_rocket_v0.disp_inputs.txt (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/valetudo_rocket_v0.disp_outputs.txt (100%)
 rename docs/notebooks/{dispersion_analysis/dispersion_analysis_outputs => monte_carlo_analysis/monte_carlo_analysis_outputs}/valetudo_rocket_v0.svg (100%)
 create mode 100644 docs/notebooks/monte_carlo_analysis/monte_carlo_class_usage.ipynb
 rename docs/notebooks/{dispersion_analysis => monte_carlo_analysis}/parachute_drop_from_helicopter.ipynb (98%)
 create mode 100644 docs/reference/classes/monte_carlo/index.rst
 create mode 100644 docs/reference/classes/monte_carlo/monte_carlo.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/index.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_elliptical_fins.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_environment.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_flight.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_generic_motor.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_model.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_motor_model.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_nose_cone.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_parachute.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_rail_buttons.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_rocket.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_solid_motor.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_tail.rst
 create mode 100644 docs/reference/classes/monte_carlo/stochastic_models/stochastic_trapezoidal_fins.rst
 create mode 100644 docs/requirements.in
 create mode 100644 docs/static/landing_images/api.svg
 create mode 100644 docs/static/landing_images/contributor.svg
 create mode 100644 docs/static/landing_images/getting_started.svg
 create mode 100644 docs/static/landing_images/user_guide.svg
 delete mode 100644 docs/static/notebooks.css
 create mode 100644 docs/static/rocketpy.css
 create mode 100644 docs/user/stochastic.rst
 create mode 100644 pyproject.toml
 create mode 100644 rocketpy/_encoders.py
 create mode 100644 rocketpy/plots/monte_carlo_plots.py
 create mode 100644 rocketpy/prints/monte_carlo_prints.py
 create mode 100644 rocketpy/simulation/monte_carlo.py
 create mode 100644 rocketpy/stochastic/__init__.py
 create mode 100644 rocketpy/stochastic/stochastic_aero_surfaces.py
 create mode 100644 rocketpy/stochastic/stochastic_environment.py
 create mode 100644 rocketpy/stochastic/stochastic_flight.py
 create mode 100644 rocketpy/stochastic/stochastic_generic_motor.py
 create mode 100644 rocketpy/stochastic/stochastic_model.py
 create mode 100644 rocketpy/stochastic/stochastic_motor_model.py
 create mode 100644 rocketpy/stochastic/stochastic_parachute.py
 create mode 100644 rocketpy/stochastic/stochastic_rocket.py
 create mode 100644 rocketpy/stochastic/stochastic_solid_motor.py
 delete mode 100644 setup.py
 create mode 100644 tests/acceptance/test_prometheus_rocket.py
 rename tests/fixtures/{dispersion => monte_carlo}/Valetudo_inputs.csv (100%)
 create mode 100644 tests/fixtures/monte_carlo/__init__.py
 create mode 100644 tests/fixtures/monte_carlo/example.inputs.txt
 create mode 100644 tests/fixtures/monte_carlo/example.outputs.txt
 create mode 100644 tests/fixtures/monte_carlo/monte_carlo_fixtures.py
 create mode 100644 tests/fixtures/monte_carlo/stochastic_fixtures.py
 create mode 100644 tests/fixtures/monte_carlo/stochastic_motors_fixtures.py
 create mode 100644 tests/test_monte_carlo.py
 create mode 100644 tests/unit/__init__.py
 create mode 100644 tests/unit/stochastic/__init__.py
 create mode 100644 tests/unit/stochastic/test_stochastic_aero_surfaces.py
 create mode 100644 tests/unit/stochastic/test_stochastic_environment.py
 create mode 100644 tests/unit/stochastic/test_stochastic_flight.py
 create mode 100644 tests/unit/stochastic/test_stochastic_motors.py
 create mode 100644 tests/unit/stochastic/test_stochastic_parachute.py
 create mode 100644 tests/unit/stochastic/test_stochastic_rocket.py
 create mode 100644 tests/unit/test_flight_time_nodes.py
 create mode 100644 tests/unit/test_stochastic_model.py

diff --git a/.coveragerc b/.coveragerc
deleted file mode 100644
index e4405ddbc..000000000
--- a/.coveragerc
+++ /dev/null
@@ -1,4 +0,0 @@
-[report]
-exclude_also=
-    ; Don't complain about exceptions or warnings not being covered by tests
-    warnings.warn*
\ No newline at end of file
diff --git a/.flake8 b/.flake8
deleted file mode 100644
index 01efeb095..000000000
--- a/.flake8
+++ /dev/null
@@ -1,5 +0,0 @@
-[flake8]
-max-line-length = 88
-max-module-lines= 3000
-exclude = .git,__pycache__
-ignore = E203, W503
diff --git a/.github/workflows/test_pytest.yaml b/.github/workflows/test_pytest.yaml
index bb0b65055..c3e06afe9 100644
--- a/.github/workflows/test_pytest.yaml
+++ b/.github/workflows/test_pytest.yaml
@@ -6,6 +6,8 @@ on:
     paths:
       - "**.py"
       - ".github/**"
+      - "pyproject.toml"
+      - "requirements*"
 
 defaults:
   run:
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index d2023dd4c..7e2375a2c 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -7,9 +7,9 @@ version: 2
 
 # Set the version of Python and other tools
 build:
-  os: ubuntu-20.04
+  os: ubuntu-22.04
   tools:
-    python: "3.9"
+    python: "3.12"
 
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 4d2509adf..42dd2d1e3 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -28,17 +28,41 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
 ## [Unreleased] - yyyy-mm-dd
 
 <!-- These are the changes that were not release yet, please add them correctly.
-  Attention: The newest changes should be on top -->
+Attention: The newest changes should be on top -->
+
+## [1.3.0.post1] - 2024-06-02
+
+You can install this version by running `pip install rocketpy==1.3.0.post1`
+
+### Fixed
+
+- BUG: pyproject.toml Main Module Finding. [#616](https://github.com/RocketPy-Team/RocketPy/pull/616)
+
+## [1.3.0] - 2024-06-01
+
+You can install this version by running `pip install rocketpy==1.3.0`
 
 ### Added
 
+- ENH: Add Prandtl-Gauss transformation to NoseCone and Tail [#609](https://github.com/RocketPy-Team/RocketPy/pull/609)
+- DOC: Adds prometheus data, Spaceport America 2022 [#601](https://github.com/RocketPy-Team/RocketPy/pull/601)
+- ENH: Pre-calculate attributes in Rocket class [#595](https://github.com/RocketPy-Team/RocketPy/pull/595)
+- ENH: Complex step differentiation [#594](https://github.com/RocketPy-Team/RocketPy/pull/594)
 - ENH: Exponential backoff decorator (fix #449) [#588](https://github.com/RocketPy-Team/RocketPy/pull/588)
+- ENH: Function Validation Rework & Swap `np.searchsorted` to `bisect_left` [#582](https://github.com/RocketPy-Team/RocketPy/pull/582)
 - ENH: Add new stability margin properties to Flight class [#572](https://github.com/RocketPy-Team/RocketPy/pull/572)
 - ENH: adds `Function.remove_outliers` method [#554](https://github.com/RocketPy-Team/RocketPy/pull/554)
 
 ### Changed
 
-- DEP: delete deprecated rocketpy.tools.cached_property [#587](https://github.com/RocketPy-Team/RocketPy/pull/587) 
+- REL: Bump versioning to RocketPy v1.3.0 [#614](https://github.com/RocketPy-Team/RocketPy/pull/614)
+- ENH: Adds StochasticModel.visualize_attributes() method [#612](https://github.com/RocketPy-Team/RocketPy/pull/612)
+- DOC: Monte carlo documentation updates [#607](https://github.com/RocketPy-Team/RocketPy/pull/607)
+- MNT: refactor u_dot parachute method [#596](https://github.com/RocketPy-Team/RocketPy/pull/596)
+- BLD: Change setup.py to pyproject.toml [#589](https://github.com/RocketPy-Team/RocketPy/pull/589)
+- DEP: delete deprecated rocketpy.tools.cached_property [#587](https://github.com/RocketPy-Team/RocketPy/pull/587)
+- DOC: Change rocketpy Landing Page to Standard Code docs [#584](https://github.com/RocketPy-Team/RocketPy/pull/584)
+- ENH: Flight simulation speed up [#581] (https://github.com/RocketPy-Team/RocketPy/pull/581) 
 - MNT: Modularize Rocket Draw [#580](https://github.com/RocketPy-Team/RocketPy/pull/580)
 - DOC: Improvements of Environment docstring phrasing [#565](https://github.com/RocketPy-Team/RocketPy/pull/565)
 - MNT: Refactor flight prints module [#579](https://github.com/RocketPy-Team/RocketPy/pull/579)
@@ -48,6 +72,12 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
 
 ### Fixed
 
+- MNT: Alter PYPI classifier naming. [#615](https://github.com/RocketPy-Team/RocketPy/pull/615)
+- DOC: Solve Dependencies Conflicts and pyproject build [#613](https://github.com/RocketPy-Team/RocketPy/pull/613)
+- BUG: Fixes nose cone bluffness issue #610 [#611](https://github.com/RocketPy-Team/RocketPy/pull/611)
+- BUG: plot drag curves when function source is callable [#599](https://github.com/RocketPy-Team/RocketPy/pull/599)
+- BUG: Fix minor type hinting problems [#598](https://github.com/RocketPy-Team/RocketPy/pull/598)
+- BUG: Optional Dependencies Naming in pyproject.toml. [#592](https://github.com/RocketPy-Team/RocketPy/pull/592)
 - BUG: Swap rocket.total_mass.differentiate for motor.total_mass_flow rate [#585](https://github.com/RocketPy-Team/RocketPy/pull/585)
 - BUG: export_eng 'Motor' method would not work for liquid motors. [#559](https://github.com/RocketPy-Team/RocketPy/pull/559) 
 
diff --git a/data/motors/cesaroni/Cesaroni_7579M1520-P.eng b/data/motors/cesaroni/Cesaroni_7579M1520-P.eng
new file mode 100644
index 000000000..6b1ff8ef2
--- /dev/null
+++ b/data/motors/cesaroni/Cesaroni_7579M1520-P.eng
@@ -0,0 +1,13 @@
+; Pro98-3G 7579M1520-BS P
+M1520-BS 98 548 P 3.737 6.718 CTI
+   0.04 1427.795
+   0.082 1706.389
+   0.176 1620.489
+   0.748 1734.249
+   1.652 1827.113
+   2.676 1715.676
+   3.89 1423.152
+   4.399 1404.579
+   4.616 661.661
+   4.877 69.649
+   4.897 0.0
\ No newline at end of file
diff --git a/data/prometheus/2022-06-24-serial-5115-flight-0001-TeleMetrum.csv b/data/prometheus/2022-06-24-serial-5115-flight-0001-TeleMetrum.csv
new file mode 100644
index 000000000..ee7dd05b4
--- /dev/null
+++ b/data/prometheus/2022-06-24-serial-5115-flight-0001-TeleMetrum.csv
@@ -0,0 +1,7082 @@
+#version,serial,flight,call,time,state,state_name,acceleration,pressure,altitude,height,speed,temperature,drogue_voltage,main_voltage,battery_voltage,connected,locked,nsat,latitude,longitude,altitude,year,month,day,hour,minute,second,pad_dist,pad_range,pad_az,pad_el,pdop,hdop,vdop,sat01,sat02,sat03,sat04,sat05,sat06,sat07,sat08,sat09,sat10,sat11,sat12,sat13,sat14,sat15,sat16,sat17,sat18,sat19,sat20,sat21,sat22,sat23,sat24,sat25,sat26,sat27,sat28,sat29,sat30,sat31,sat32
+6, 5115, 1,VA3NPN,    -0.30, 3,   boost,   -0.00,  86444.00, 1319.67,   -0.19,    0.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.29, 3,   boost,   -0.00,  86438.00, 1320.23,    0.38,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.28, 3,   boost,   -0.00,  86440.00, 1320.05,    0.19,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.27, 3,   boost,   -0.00,  86449.00, 1319.19,   -0.66,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.26, 3,   boost,   -0.00,  86443.00, 1319.76,   -0.09,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.25, 3,   boost,   -0.00,  86459.00, 1318.25,   -1.61,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.24, 3,   boost,   -0.00,  86424.00, 1321.56,    1.70,    0.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.23, 3,   boost,   -0.00,  86442.00, 1319.86,    0.00,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.22, 3,   boost,   -0.00,  86457.00, 1318.44,   -1.42,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.21, 3,   boost,   -0.00,  86436.00, 1320.42,    0.57,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.20, 3,   boost,   -0.00,  86441.00, 1319.95,    0.09,    0.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.19, 3,   boost,   -0.00,  86453.00, 1318.81,   -1.04,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.18, 3,   boost,   -0.00,  86443.00, 1319.76,   -0.09,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.17, 3,   boost,   -0.00,  86436.00, 1320.42,    0.57,    0.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.16, 3,   boost,   -0.00,  86430.00, 1320.99,    1.14,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.15, 3,   boost,   -0.00,  86449.00, 1319.19,   -0.66,    0.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.14, 3,   boost,   -0.00,  86437.00, 1320.33,    0.47,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.13, 3,   boost,   -0.00,  86450.00, 1319.10,   -0.76,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
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+6, 5115, 1,VA3NPN,    -0.11, 3,   boost,   -0.00,  86440.00, 1320.05,    0.19,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.10, 3,   boost,   -0.00,  86428.00, 1321.18,    1.33,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.09, 3,   boost,   -0.00,  86435.00, 1320.52,    0.66,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.08, 3,   boost,   -0.00,  86438.00, 1320.23,    0.38,    0.00, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.07, 3,   boost,   -0.00,  86450.00, 1319.10,   -0.76,    0.01, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.06, 3,   boost,    0.53,  86422.00, 1321.75,    1.89,    0.03, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,    -0.05, 3,   boost,    0.53,  86434.00, 1320.61,    0.76,    0.11, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
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+6, 5115, 1,VA3NPN,     0.00, 3,   boost,   89.59,  86434.00, 1320.61,    0.76,    2.43, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.00, 3,   boost,   89.59,  86434.00, 1320.61,    0.76,    2.43, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.00, 3,   boost,   89.59,  86434.00, 1320.61,    0.76,    2.43, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.00, 3,   boost,   89.59,  86434.00, 1320.61,    0.76,    2.43, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.00, 3,   boost,   89.59,  86434.00, 1320.61,    0.76,    2.43, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.00, 3,   boost,   89.59,  86434.00, 1320.61,    0.76,    2.43, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.01, 3,   boost,   87.46,  86398.00, 1324.02,    4.17,    3.25, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.01, 3,   boost,   87.46,  86398.00, 1324.02,    4.17,    3.25, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.02, 3,   boost,   86.93,  86399.00, 1323.93,    4.07,    4.08, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.02, 3,   boost,   86.93,  86399.00, 1323.93,    4.07,    4.08, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.03, 3,   boost,   79.51,  86428.00, 1321.18,    1.33,    4.91, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.04, 3,   boost,   78.98,  86435.00, 1320.52,    0.66,    5.73, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.05, 3,   boost,   78.98,  86411.00, 1322.79,    2.94,    6.53, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.06, 3,   boost,   77.92,  86431.00, 1320.90,    1.04,    7.31, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.07, 3,   boost,   76.86,  86450.00, 1319.10,   -0.76,    8.10, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.08, 3,   boost,   75.80,  86427.00, 1321.28,    1.42,    8.88, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.09, 3,   boost,   85.34,  86437.00, 1320.33,    0.47,    9.67, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.10, 3,   boost,   77.39,  86413.00, 1322.60,    2.75,   10.45, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.11, 3,   boost,   76.33,  86447.00, 1319.38,   -0.47,   11.23, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.12, 3,   boost,   76.33,  86440.00, 1320.05,    0.19,   12.01, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.13, 3,   boost,   76.33,  86422.00, 1321.75,    1.89,   12.77, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.14, 3,   boost,   76.33,  86422.00, 1321.75,    1.89,   13.54, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.15, 3,   boost,   76.33,  86432.00, 1320.80,    0.95,   14.30, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.16, 3,   boost,   76.33,  86413.00, 1322.60,    2.75,   15.06, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.17, 3,   boost,   75.80,  86440.00, 1320.05,    0.19,   15.82, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.18, 3,   boost,   74.74,  86405.00, 1323.36,    3.50,   16.57, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.19, 3,   boost,   75.27,  86413.00, 1322.60,    2.75,   17.33, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.20, 3,   boost,   75.27,  86426.00, 1321.37,    1.51,   18.08, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.21, 3,   boost,   74.74,  86429.00, 1321.09,    1.23,   18.83, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.22, 3,   boost,   74.74,  86460.00, 1318.15,   -1.70,   19.58, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.23, 3,   boost,   75.27,  86443.00, 1319.76,   -0.09,   20.33, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.24, 3,   boost,   74.74,  86396.00, 1324.21,    4.36,   21.08, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.25, 3,   boost,   75.27,  86404.00, 1323.45,    3.60,   21.84, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.26, 3,   boost,   76.86,  86469.00, 1317.30,   -2.56,   22.60, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.27, 3,   boost,   76.33,  86405.00, 1323.36,    3.50,   23.36, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.28, 3,   boost,   76.86,  86413.00, 1322.60,    2.75,   24.13, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.29, 3,   boost,   77.39,  86422.00, 1321.75,    1.89,   24.90, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.30, 3,   boost,   77.39,  86411.00, 1322.79,    2.94,   25.67, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.31, 3,   boost,   77.39,  86395.00, 1324.31,    4.45,   26.44, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.32, 3,   boost,   77.39,  86410.00, 1322.89,    3.03,   27.21, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.33, 3,   boost,   76.86,  86424.00, 1321.56,    1.70,   27.98, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.34, 3,   boost,   76.33,  86419.00, 1322.03,    2.18,   28.75, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.34, 3,   boost,   76.33,  86419.00, 1322.03,    2.18,   28.75, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.35, 3,   boost,   76.33,  86408.00, 1323.08,    3.22,   29.51, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.36, 3,   boost,   76.33,  86407.00, 1323.17,    3.31,   30.28, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.37, 3,   boost,   76.33,  86387.00, 1325.06,    5.21,   31.04, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.38, 3,   boost,   76.33,  86393.00, 1324.50,    4.64,   31.81, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.39, 3,   boost,   76.33,  86402.00, 1323.64,    3.79,   32.57, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.40, 3,   boost,   76.33,  86396.00, 1324.21,    4.36,   33.33, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.41, 3,   boost,   76.33,  86405.00, 1323.36,    3.50,   34.10, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.42, 3,   boost,   76.33,  86372.00, 1326.48,    6.63,   34.86, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.43, 3,   boost,   76.33,  86363.00, 1327.34,    7.48,   35.62, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.44, 3,   boost,   76.33,  86370.00, 1326.67,    6.82,   36.39, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.45, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   37.15, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.45, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   37.15, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.45, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   37.15, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.45, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   37.15, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.45, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   37.15, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.45, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   37.15, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395046,-106.9114515,  1390.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 25,  0,  0, 27,  0,  0,  0,  0, 33, 36, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.46, 3,   boost,   76.33,  86382.00, 1325.54,    5.68,   37.91, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.47, 3,   boost,   76.33,  86369.00, 1326.77,    6.91,   38.68, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.48, 3,   boost,   76.33,  86386.00, 1325.16,    5.30,   39.44, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.49, 3,   boost,   76.33,  86358.00, 1327.81,    7.96,   40.20, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.50, 3,   boost,   76.86,  86343.00, 1329.23,    9.38,   40.97, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.51, 3,   boost,   76.33,  86343.00, 1329.23,    9.38,   41.73, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.52, 3,   boost,   76.33,  86331.00, 1330.37,   10.51,   42.50, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.53, 3,   boost,   76.33,  86341.00, 1329.42,    9.57,   43.26, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.54, 3,   boost,   76.86,  86341.00, 1329.42,    9.57,   44.03, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.55, 3,   boost,   76.86,  86331.00, 1330.37,   10.51,   44.80, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.56, 3,   boost,   76.86,  86345.00, 1329.04,    9.19,   45.56, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.57, 3,   boost,   76.86,  86325.00, 1330.94,   11.08,   46.33, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.58, 3,   boost,   76.86,  86343.00, 1329.23,    9.38,   47.10, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.59, 3,   boost,   76.86,  86345.00, 1329.04,    9.19,   47.87, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.60, 3,   boost,   76.86,  86325.00, 1330.94,   11.08,   48.64, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.61, 3,   boost,   76.86,  86321.00, 1331.32,   11.46,   49.41, 33.9, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.62, 3,   boost,   76.86,  86331.00, 1330.37,   10.51,   50.18, 34.0, 0.00, 0.01, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
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+6, 5115, 1,VA3NPN,     0.70, 3,   boost,   77.39,  86296.00, 1333.69,   13.83,   56.35, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.71, 3,   boost,   77.39,  86278.00, 1335.39,   15.54,   57.12, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.72, 3,   boost,   77.39,  86283.00, 1334.92,   15.06,   57.90, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.73, 3,   boost,   77.39,  86278.00, 1335.39,   15.54,   58.67, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.74, 3,   boost,   77.39,  86279.00, 1335.30,   15.44,   59.44, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.75, 3,   boost,   77.39,  86269.00, 1336.25,   16.39,   60.22, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.76, 3,   boost,   77.39,  86273.00, 1335.87,   16.01,   60.99, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.77, 3,   boost,   77.39,  86286.00, 1334.63,   14.78,   61.77, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.78, 3,   boost,   77.92,  86278.00, 1335.39,   15.54,   62.55, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.79, 3,   boost,   77.92,  86260.00, 1337.10,   17.24,   63.32, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.80, 3,   boost,   77.92,  86261.00, 1337.01,   17.15,   64.10, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.81, 3,   boost,   77.92,  86237.00, 1339.28,   19.43,   64.88, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.82, 3,   boost,   77.92,  86255.00, 1337.57,   17.72,   65.66, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
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+6, 5115, 1,VA3NPN,     0.84, 3,   boost,   77.92,  86222.00, 1340.70,   20.85,   67.22, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.85, 3,   boost,   77.92,  86246.00, 1338.43,   18.57,   68.00, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.86, 3,   boost,   77.92,  86227.00, 1340.23,   20.37,   68.78, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.87, 3,   boost,   77.92,  86208.00, 1342.03,   22.18,   69.56, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.88, 3,   boost,   77.92,  86201.00, 1342.70,   22.84,   70.33, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.89, 3,   boost,   77.92,  86215.00, 1341.37,   21.51,   71.11, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.90, 3,   boost,   77.92,  86197.00, 1343.08,   23.22,   71.89, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.91, 3,   boost,   77.92,  86195.00, 1343.27,   23.41,   72.68, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.92, 3,   boost,   78.45,  86201.00, 1342.70,   22.84,   73.46, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.93, 3,   boost,   78.45,  86204.00, 1342.41,   22.56,   74.24, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.94, 3,   boost,   77.92,  86157.00, 1346.87,   27.02,   75.02, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.95, 3,   boost,   78.45,  86201.00, 1342.70,   22.84,   75.80, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.96, 3,   boost,   78.45,  86186.00, 1344.12,   24.26,   76.59, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.97, 3,   boost,   78.45,  86200.00, 1342.79,   22.94,   77.37, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.98, 3,   boost,   78.45,  86193.00, 1343.46,   23.60,   78.16, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.98, 3,   boost,   78.45,  86193.00, 1343.46,   23.60,   78.16, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     0.99, 3,   boost,   78.45,  86173.00, 1345.35,   25.50,   78.94, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.00, 3,   boost,   78.45,  86178.00, 1344.88,   25.02,   79.73, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.01, 3,   boost,   78.45,  86171.00, 1345.54,   25.69,   80.51, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.02, 3,   boost,   78.45,  86155.00, 1347.06,   27.21,   81.30, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.03, 3,   boost,   78.98,  86163.00, 1346.30,   26.45,   82.08, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.04, 3,   boost,   78.45,  86147.00, 1347.82,   27.97,   82.87, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.05, 3,   boost,   78.45,  86129.00, 1349.53,   29.67,   83.66, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.06, 3,   boost,   78.98,  86125.00, 1349.91,   30.05,   84.44, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.07, 3,   boost,   78.98,  86118.00, 1350.58,   30.72,   85.23, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.08, 3,   boost,   78.98,  86130.00, 1349.44,   29.58,   86.02, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.09, 3,   boost,   78.45,  86135.00, 1348.96,   29.11,   86.81, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.10, 3,   boost,   78.98,  86139.00, 1348.58,   28.73,   87.60, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.11, 3,   boost,   78.98,  86102.00, 1352.09,   32.24,   88.39, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.12, 3,   boost,   78.98,  86119.00, 1350.48,   30.62,   89.17, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.13, 3,   boost,   78.98,  86113.00, 1351.05,   31.19,   89.96, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.14, 3,   boost,   78.98,  86094.00, 1352.85,   33.00,   90.75, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.15, 3,   boost,   78.98,  86109.00, 1351.43,   31.57,   91.54, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.16, 3,   boost,   78.98,  86101.00, 1352.19,   32.33,   92.33, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.17, 3,   boost,   78.98,  86090.00, 1353.23,   33.38,   93.12, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.18, 3,   boost,   78.98,  86086.00, 1353.61,   33.76,   93.91, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.19, 3,   boost,   78.98,  86096.00, 1352.66,   32.81,   94.70, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.20, 3,   boost,   78.98,  86080.00, 1354.18,   34.33,   95.49, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.21, 3,   boost,   78.98,  86053.00, 1356.75,   36.89,   96.28, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.22, 3,   boost,   78.98,  86053.00, 1356.75,   36.89,   97.07, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.23, 3,   boost,   78.98,  86049.00, 1357.13,   37.27,   97.86, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.24, 3,   boost,   78.98,  86057.00, 1356.37,   36.51,   98.65, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.25, 3,   boost,   78.98,  86052.00, 1356.84,   36.99,   99.44, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.26, 3,   boost,   79.51,  86040.00, 1357.98,   38.13,  100.24, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.27, 3,   boost,   78.98,  86043.00, 1357.70,   37.84,  101.03, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.28, 3,   boost,   79.51,  86038.00, 1358.17,   38.32,  101.82, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.29, 3,   boost,   79.51,  86005.00, 1361.31,   41.46,  102.61, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.30, 3,   boost,   79.51,  86012.00, 1360.65,   40.79,  103.41, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.30, 3,   boost,   79.51,  86012.00, 1360.65,   40.79,  103.41, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.31, 3,   boost,   78.98,  86025.00, 1359.41,   39.55,  104.20, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.32, 3,   boost,   78.98,  86010.00, 1360.84,   40.98,  104.99, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.33, 3,   boost,   78.98,  86007.00, 1361.12,   41.27,  105.78, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.34, 3,   boost,   79.51,  86013.00, 1360.55,   40.69,  106.58, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.35, 3,   boost,   79.51,  86000.00, 1361.79,   41.93,  107.37, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.36, 3,   boost,   79.51,  85997.00, 1362.07,   42.22,  108.17, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.37, 3,   boost,   79.51,  85996.00, 1362.17,   42.31,  108.96, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.38, 3,   boost,   79.51,  85975.00, 1364.16,   44.31,  109.75, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.39, 3,   boost,   79.51,  85988.00, 1362.93,   43.07,  110.55, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.40, 3,   boost,   79.51,  85973.00, 1364.35,   44.50,  111.35, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.41, 3,   boost,   79.51,  85948.00, 1366.73,   46.88,  112.14, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.42, 3,   boost,   79.51,  85957.00, 1365.87,   46.02,  112.94, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.43, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  113.73, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.44, 3,   boost,   79.51,  85939.00, 1367.59,   47.73,  114.53, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395050,-106.9114519,  1390.0, 2022,  6, 24, 15, 17, 17,        0,        0, 320,   0,   1.4,2147483647.0,2147483647.0,  0, 36, 24,  0,  0, 27,  0,  0,  0,  0, 34, 37, 25, 21,  0,  0, 33,  0, 25, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,     1.45, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  115.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.45, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  115.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.45, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  115.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.45, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  115.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.45, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  115.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.45, 3,   boost,   79.51,  85952.00, 1366.35,   46.49,  115.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.46, 3,   boost,   79.51,  85935.00, 1367.97,   48.11,  116.12, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.47, 3,   boost,   79.51,  85928.00, 1368.63,   48.78,  116.91, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.48, 3,   boost,   79.51,  85929.00, 1368.54,   48.68,  117.71, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.49, 3,   boost,   79.51,  85909.00, 1370.44,   50.59,  118.50, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.50, 3,   boost,   80.04,  85929.00, 1368.54,   48.68,  119.30, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.51, 3,   boost,   79.51,  85927.00, 1368.73,   48.87,  120.10, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.52, 3,   boost,   79.51,  85900.00, 1371.30,   51.44,  120.89, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.53, 3,   boost,   79.51,  85901.00, 1371.20,   51.35,  121.69, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.54, 3,   boost,   79.51,  85890.00, 1372.25,   52.39,  122.48, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.55, 3,   boost,   79.51,  85848.00, 1376.25,   56.39,  123.28, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.56, 3,   boost,   79.51,  85864.00, 1374.72,   54.87,  124.07, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.57, 3,   boost,   79.51,  85860.00, 1375.10,   55.25,  124.87, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.58, 3,   boost,   79.51,  85840.00, 1377.01,   57.15,  125.66, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.59, 3,   boost,   79.51,  85827.00, 1378.25,   58.39,  126.46, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.60, 3,   boost,   79.51,  85839.00, 1377.10,   57.25,  127.25, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.61, 3,   boost,   79.51,  85810.00, 1379.86,   60.01,  128.05, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.62, 3,   boost,   79.51,  85808.00, 1380.06,   60.20,  128.84, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.62, 3,   boost,   79.51,  85808.00, 1380.06,   60.20,  128.84, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.63, 3,   boost,   79.51,  85796.00, 1381.20,   61.34,  129.64, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.64, 3,   boost,   78.98,  85821.00, 1378.82,   58.96,  130.43, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.65, 3,   boost,   79.51,  85814.00, 1379.48,   59.63,  131.22, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.66, 3,   boost,   78.98,  85779.00, 1382.82,   62.96,  132.01, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.67, 3,   boost,   78.98,  85781.00, 1382.63,   62.77,  132.81, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.68, 3,   boost,   78.98,  85782.00, 1382.53,   62.68,  133.60, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.69, 3,   boost,   78.98,  85771.00, 1383.58,   63.72,  134.39, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.70, 3,   boost,   78.98,  85778.00, 1382.91,   63.06,  135.18, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.71, 3,   boost,   78.98,  85776.00, 1383.10,   63.25,  135.96, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.72, 3,   boost,   78.98,  85766.00, 1384.06,   64.20,  136.75, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.73, 3,   boost,   78.98,  85748.00, 1385.77,   65.92,  137.54, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.74, 3,   boost,   78.45,  85761.00, 1384.53,   64.68,  138.33, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.75, 3,   boost,   78.45,  85724.00, 1388.06,   68.20,  139.12, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.76, 3,   boost,   78.45,  85734.00, 1387.10,   67.25,  139.90, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.77, 3,   boost,   78.45,  85727.00, 1387.77,   67.92,  140.69, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.78, 3,   boost,   78.45,  85717.00, 1388.73,   68.87,  141.47, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.79, 3,   boost,   78.45,  85738.00, 1386.72,   66.87,  142.25, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.80, 3,   boost,   78.45,  85721.00, 1388.34,   68.49,  143.04, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.81, 3,   boost,   77.92,  85727.00, 1387.77,   67.92,  143.82, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.82, 3,   boost,   78.45,  85701.00, 1390.25,   70.39,  144.60, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.83, 3,   boost,   77.92,  85709.00, 1389.49,   69.63,  145.38, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.84, 3,   boost,   77.92,  85707.00, 1389.68,   69.82,  146.16, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.85, 3,   boost,   77.92,  85684.00, 1391.87,   72.02,  146.94, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.86, 3,   boost,   77.92,  85673.00, 1392.92,   73.06,  147.72, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.87, 3,   boost,   77.92,  85684.00, 1391.87,   72.02,  148.50, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.88, 3,   boost,   77.92,  85689.00, 1391.39,   71.54,  149.28, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.89, 3,   boost,   77.39,  85665.00, 1393.68,   73.83,  150.06, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.90, 3,   boost,   77.92,  85649.00, 1395.21,   75.35,  150.83, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.91, 3,   boost,   77.39,  85654.00, 1394.73,   74.88,  151.61, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.92, 3,   boost,   77.39,  85654.00, 1394.73,   74.88,  152.38, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.93, 3,   boost,   77.39,  85648.00, 1395.30,   75.45,  153.16, 33.9, 0.00, 0.00, 3.86, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.94, 3,   boost,   76.86,  85660.00, 1394.16,   74.30,  153.93, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.94, 3,   boost,   76.86,  85660.00, 1394.16,   74.30,  153.93, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.95, 3,   boost,   77.39,  85650.00, 1395.11,   75.26,  154.70, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.96, 3,   boost,   76.86,  85638.00, 1396.26,   76.40,  155.47, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.97, 3,   boost,   76.86,  85623.00, 1397.69,   77.83,  156.24, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.98, 3,   boost,   76.86,  85639.00, 1396.16,   76.31,  157.01, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     1.99, 3,   boost,   76.86,  85612.00, 1398.74,   78.88,  157.78, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.00, 3,   boost,   76.86,  85646.00, 1395.49,   75.64,  158.54, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.01, 3,   boost,   76.33,  85633.00, 1396.73,   76.88,  159.31, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.02, 3,   boost,   76.33,  85622.00, 1397.78,   77.93,  160.08, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.03, 3,   boost,   76.33,  85613.00, 1398.64,   78.79,  160.84, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.04, 3,   boost,   76.33,  85591.00, 1400.74,   80.89,  161.60, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.05, 3,   boost,   76.33,  85595.00, 1400.36,   80.50,  162.37, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.06, 3,   boost,   76.33,  85579.00, 1401.89,   82.03,  163.13, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.07, 3,   boost,   75.80,  85569.00, 1402.84,   82.99,  163.89, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.08, 3,   boost,   75.80,  85587.00, 1401.12,   81.27,  164.65, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.09, 3,   boost,   75.80,  85566.00, 1403.13,   83.27,  165.40, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.10, 3,   boost,   75.80,  85551.00, 1404.56,   84.70,  166.16, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.11, 3,   boost,   75.27,  85540.00, 1405.61,   85.75,  166.92, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.12, 3,   boost,   75.27,  85526.00, 1406.95,   87.09,  167.67, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.13, 3,   boost,   75.27,  85528.00, 1406.76,   86.90,  168.42, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.14, 3,   boost,   75.27,  85524.00, 1407.14,   87.28,  169.18, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.15, 3,   boost,   74.74,  85496.00, 1409.81,   89.96,  169.93, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.16, 3,   boost,   74.74,  85490.00, 1410.39,   90.53,  170.67, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.17, 3,   boost,   74.74,  85477.00, 1411.63,   91.77,  171.42, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.18, 3,   boost,   74.74,  85459.00, 1413.35,   93.49,  172.17, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.19, 3,   boost,   74.74,  85454.00, 1413.82,   93.97,  172.92, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.20, 3,   boost,   74.21,  85436.00, 1415.54,   95.69,  173.66, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.21, 3,   boost,   74.21,  85439.00, 1415.26,   95.40,  174.40, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.22, 3,   boost,   74.21,  85410.00, 1418.03,   98.17,  175.15, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.23, 3,   boost,   74.21,  85398.00, 1419.18,   99.32,  175.89, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.24, 3,   boost,   74.21,  85407.00, 1418.32,   98.46,  176.63, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.25, 3,   boost,   74.21,  85396.00, 1419.37,   99.51,  177.37, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.26, 3,   boost,   74.21,  85386.00, 1420.32,  100.47,  178.11, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.26, 3,   boost,   74.21,  85386.00, 1420.32,  100.47,  178.11, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.27, 3,   boost,   74.21,  85382.00, 1420.71,  100.85,  178.85, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.28, 3,   boost,   73.68,  85376.00, 1421.28,  101.42,  179.59, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.29, 3,   boost,   73.68,  85359.00, 1422.91,  103.05,  180.33, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.30, 3,   boost,   73.68,  85336.00, 1425.11,  105.25,  181.07, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.31, 3,   boost,   73.68,  85354.00, 1423.38,  103.53,  181.80, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.32, 3,   boost,   73.15,  85321.00, 1426.54,  106.69,  182.54, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.33, 3,   boost,   73.15,  85312.00, 1427.40,  107.55,  183.27, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.34, 3,   boost,   73.15,  85304.00, 1428.17,  108.31,  184.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.35, 3,   boost,   73.15,  85319.00, 1426.73,  106.88,  184.74, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.36, 3,   boost,   73.15,  85293.00, 1429.22,  109.37,  185.47, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.37, 3,   boost,   73.15,  85289.00, 1429.60,  109.75,  186.20, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.38, 3,   boost,   72.62,  85283.00, 1430.18,  110.32,  186.93, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.39, 3,   boost,   72.62,  85275.00, 1430.94,  111.09,  187.65, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.40, 3,   boost,   72.62,  85267.00, 1431.71,  111.85,  188.38, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.41, 3,   boost,   72.62,  85256.00, 1432.76,  112.91,  189.11, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.42, 3,   boost,   72.62,  85252.00, 1433.15,  113.29,  189.83, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.43, 3,   boost,   72.62,  85237.00, 1434.58,  114.73,  190.56, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.44, 3,   boost,   72.09,  85233.00, 1434.96,  115.11,  191.28, 33.9, 0.00, 0.00, 3.87, 1, 1, 11,  32.9395428,-106.9114309,  1400.0, 2022,  6, 24, 15, 17, 18,        5,       11,  24,  65,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 25,  0,  0,  0,  0, 18, 29, 24, 29,  0,  0, 16,  0, 21, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.45, 3,   boost,   72.09,  85226.00, 1435.63,  115.78,  192.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.45, 3,   boost,   72.09,  85226.00, 1435.63,  115.78,  192.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.45, 3,   boost,   72.09,  85226.00, 1435.63,  115.78,  192.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.45, 3,   boost,   72.09,  85226.00, 1435.63,  115.78,  192.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.45, 3,   boost,   72.09,  85226.00, 1435.63,  115.78,  192.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.45, 3,   boost,   72.09,  85226.00, 1435.63,  115.78,  192.00, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.46, 3,   boost,   72.09,  85233.00, 1434.96,  115.11,  192.72, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.47, 3,   boost,   71.56,  85226.00, 1435.63,  115.78,  193.44, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.48, 3,   boost,   72.09,  85227.00, 1435.54,  115.68,  194.16, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.49, 3,   boost,   72.09,  85192.00, 1438.89,  119.04,  194.88, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.50, 3,   boost,   72.09,  85218.00, 1436.40,  116.55,  195.60, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.51, 3,   boost,   71.56,  85197.00, 1438.41,  118.56,  196.32, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.52, 3,   boost,   71.56,  85170.00, 1441.00,  121.14,  197.04, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.53, 3,   boost,   71.56,  85180.00, 1440.04,  120.18,  197.75, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.54, 3,   boost,   71.56,  85146.00, 1443.30,  123.44,  198.47, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.55, 3,   boost,   71.03,  85130.00, 1444.83,  124.98,  199.18, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.56, 3,   boost,   71.03,  85144.00, 1443.49,  123.63,  199.89, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.57, 3,   boost,   71.03,  85109.00, 1446.85,  126.99,  200.60, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.58, 3,   boost,   71.03,  85094.00, 1448.28,  128.43,  201.31, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.58, 3,   boost,   71.03,  85094.00, 1448.28,  128.43,  201.31, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.59, 3,   boost,   71.03,  85108.00, 1446.94,  127.09,  202.02, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.60, 3,   boost,   70.50,  85089.00, 1448.76,  128.91,  202.73, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.61, 3,   boost,   70.50,  85081.00, 1449.53,  129.67,  203.43, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.62, 3,   boost,   70.50,  85063.00, 1451.26,  131.40,  204.14, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.63, 3,   boost,   70.50,  85061.00, 1451.45,  131.59,  204.84, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.64, 3,   boost,   70.50,  85050.00, 1452.50,  132.65,  205.55, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.65, 3,   boost,   70.50,  85007.00, 1456.63,  136.77,  206.25, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.66, 3,   boost,   69.97,  84992.00, 1458.07,  138.21,  206.95, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.67, 3,   boost,   69.97,  85010.00, 1456.34,  136.48,  207.66, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.68, 3,   boost,   69.97,  84990.00, 1458.26,  138.40,  208.36, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.69, 3,   boost,   69.97,  84991.00, 1458.16,  138.31,  209.06, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.70, 3,   boost,   69.97,  84979.00, 1459.32,  139.46,  209.75, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.71, 3,   boost,   69.44,  84969.00, 1460.28,  140.42,  210.45, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.72, 3,   boost,   69.44,  84926.00, 1464.40,  144.55,  211.15, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.73, 3,   boost,   69.44,  84916.00, 1465.36,  145.51,  211.84, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.74, 3,   boost,   68.91,  84946.00, 1462.48,  142.63,  212.53, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.75, 3,   boost,   68.91,  84871.00, 1469.69,  149.83,  213.22, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.76, 3,   boost,   68.91,  84899.00, 1467.00,  147.14,  213.91, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.77, 3,   boost,   68.91,  84899.00, 1467.00,  147.14,  214.60, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.78, 3,   boost,   68.91,  84897.00, 1467.19,  147.33,  215.29, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.79, 3,   boost,   68.91,  84875.00, 1469.30,  149.45,  215.98, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.80, 3,   boost,   68.91,  84872.00, 1469.59,  149.74,  216.67, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.81, 3,   boost,   68.38,  84867.00, 1470.07,  150.22,  217.35, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.82, 3,   boost,   68.38,  84861.00, 1470.65,  150.79,  218.04, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.83, 3,   boost,   68.38,  84840.00, 1472.67,  152.81,  218.72, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.84, 3,   boost,   67.85,  84856.00, 1471.13,  151.27,  219.40, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.85, 3,   boost,   67.85,  84863.00, 1470.46,  150.60,  220.08, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.86, 3,   boost,   67.85,  84834.00, 1473.24,  153.39,  220.76, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.87, 3,   boost,   67.85,  84811.00, 1475.45,  155.60,  221.44, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.88, 3,   boost,   67.85,  84793.00, 1477.19,  157.33,  222.12, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.89, 3,   boost,   67.32,  84810.00, 1475.55,  155.69,  222.79, 33.9, 0.00, 0.00, 3.86, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.90, 3,   boost,   67.32,  84779.00, 1478.53,  158.68,  223.47, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.90, 3,   boost,   67.32,  84779.00, 1478.53,  158.68,  223.47, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.91, 3,   boost,   67.32,  84783.00, 1478.15,  158.29,  224.14, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.92, 3,   boost,   67.32,  84768.00, 1479.59,  159.73,  224.81, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.93, 3,   boost,   67.32,  84745.00, 1481.80,  161.95,  225.49, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.94, 3,   boost,   67.32,  84756.00, 1480.74,  160.89,  226.16, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.95, 3,   boost,   66.79,  84690.00, 1487.09,  167.24,  226.83, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.96, 3,   boost,   66.79,  84754.00, 1480.94,  161.08,  227.50, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.97, 3,   boost,   66.79,  84714.00, 1484.78,  164.93,  228.17, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.98, 3,   boost,   66.79,  84683.00, 1487.77,  167.91,  228.83, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     2.99, 3,   boost,   66.79,  84654.00, 1490.56,  170.70,  229.50, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.00, 3,   boost,   66.26,  84671.00, 1488.92,  169.07,  230.16, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.01, 3,   boost,   66.26,  84649.00, 1491.04,  171.19,  230.83, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.02, 3,   boost,   66.26,  84637.00, 1492.20,  172.34,  231.49, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.03, 3,   boost,   65.73,  84629.00, 1492.97,  173.11,  232.15, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.04, 3,   boost,   65.73,  84608.00, 1494.99,  175.13,  232.81, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.05, 3,   boost,   65.73,  84595.00, 1496.24,  176.39,  233.47, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.06, 3,   boost,   65.73,  84595.00, 1496.24,  176.39,  234.12, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.07, 3,   boost,   65.20,  84583.00, 1497.40,  177.54,  234.78, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.08, 3,   boost,   65.20,  84556.00, 1500.00,  180.14,  235.43, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.09, 3,   boost,   65.20,  84538.00, 1501.74,  181.88,  236.08, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.10, 3,   boost,   65.20,  84535.00, 1502.02,  182.17,  236.73, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.11, 3,   boost,   64.67,  84517.00, 1503.76,  183.90,  237.38, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.12, 3,   boost,   65.20,  84500.00, 1505.40,  185.54,  238.03, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.13, 3,   boost,   64.67,  84471.00, 1508.20,  188.34,  238.68, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.14, 3,   boost,   64.67,  84448.00, 1510.41,  190.56,  239.33, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.15, 3,   boost,   64.14,  84478.00, 1507.52,  187.66,  239.97, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.16, 3,   boost,   64.67,  84438.00, 1511.38,  191.52,  240.62, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.17, 3,   boost,   64.14,  84436.00, 1511.57,  191.72,  241.26, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.18, 3,   boost,   64.67,  84439.00, 1511.28,  191.43,  241.91, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.19, 3,   boost,   64.14,  84439.00, 1511.28,  191.43,  242.55, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.20, 3,   boost,   64.14,  84421.00, 1513.02,  193.16,  243.19, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.21, 3,   boost,   64.14,  84421.00, 1513.02,  193.16,  243.83, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.22, 3,   boost,   63.61,  84418.00, 1513.31,  193.45,  244.47, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.22, 3,   boost,   63.61,  84418.00, 1513.31,  193.45,  244.47, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.23, 3,   boost,   63.61,  84416.00, 1513.50,  193.65,  245.11, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.24, 3,   boost,   63.61,  84364.00, 1518.52,  198.67,  245.74, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.25, 3,   boost,   63.61,  84353.00, 1519.58,  199.73,  246.38, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.26, 3,   boost,   63.61,  84339.00, 1520.94,  201.08,  247.01, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.27, 3,   boost,   63.08,  84333.00, 1521.51,  201.66,  247.65, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.28, 3,   boost,   63.08,  84349.00, 1519.97,  200.11,  248.28, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.29, 3,   boost,   62.55,  84304.00, 1524.32,  204.46,  248.91, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.30, 3,   boost,   62.55,  84326.00, 1522.19,  202.34,  249.53, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.31, 3,   boost,   62.55,  84268.00, 1527.79,  207.94,  250.16, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.32, 3,   boost,   62.55,  84248.00, 1529.73,  209.87,  250.79, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.33, 3,   boost,   62.55,  84222.00, 1532.24,  212.39,  251.41, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.34, 3,   boost,   62.55,  84227.00, 1531.76,  211.90,  252.04, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.35, 3,   boost,   62.55,  84224.00, 1532.05,  212.19,  252.66, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.36, 3,   boost,   62.02,  84202.00, 1534.17,  214.32,  253.28, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.37, 3,   boost,   62.02,  84202.00, 1534.17,  214.32,  253.90, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.38, 3,   boost,   62.02,  84180.00, 1536.30,  216.45,  254.52, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.39, 3,   boost,   61.49,  84138.00, 1540.37,  220.51,  255.14, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.40, 3,   boost,   61.49,  84145.00, 1539.69,  219.83,  255.76, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.41, 3,   boost,   61.49,  84136.00, 1540.56,  220.70,  256.37, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.42, 3,   boost,   61.49,  84127.00, 1541.43,  221.57,  256.99, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.43, 3,   boost,   61.49,  84106.00, 1543.46,  223.61,  257.60, 33.9, 0.00, 0.00, 3.87, 1, 1, 10,  32.9395582,-106.9113928,  1447.0, 2022,  6, 24, 15, 17, 19,        8,       58,  43,  82,   1.4,2147483647.0,2147483647.0,  0, 21, 27,  0,  0, 20,  0,  0,  0,  0, 13, 24, 30, 24,  0,  0, 13,  0, 18, 29,  0,  0,  0, 20,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.44, 3,   boost,   60.96,  84089.00, 1545.11,  225.25,  258.21, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.44, 3,   boost,   60.96,  84089.00, 1545.11,  225.25,  258.21, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.44, 3,   boost,   60.96,  84089.00, 1545.11,  225.25,  258.21, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.44, 3,   boost,   60.96,  84089.00, 1545.11,  225.25,  258.21, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.44, 3,   boost,   60.96,  84089.00, 1545.11,  225.25,  258.21, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.44, 3,   boost,   60.96,  84089.00, 1545.11,  225.25,  258.21, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.45, 3,   boost,   60.96,  84048.00, 1549.08,  229.22,  258.82, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.46, 3,   boost,   60.96,  84084.00, 1545.59,  225.74,  259.43, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.47, 3,   boost,   60.96,  84034.00, 1550.43,  230.58,  260.04, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.48, 3,   boost,   60.43,  84044.00, 1549.47,  229.61,  260.65, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.49, 3,   boost,   60.43,  83997.00, 1554.02,  234.16,  261.25, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.50, 3,   boost,   60.43,  84001.00, 1553.63,  233.78,  261.86, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.51, 3,   boost,   60.43,  83977.00, 1555.96,  236.10,  262.46, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.52, 3,   boost,   59.90,  83977.00, 1555.96,  236.10,  263.06, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.53, 3,   boost,   59.90,  83966.00, 1557.02,  237.17,  263.66, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.54, 3,   boost,   59.90,  83960.00, 1557.60,  237.75,  264.26, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.54, 3,   boost,   59.90,  83960.00, 1557.60,  237.75,  264.26, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.55, 3,   boost,   59.37,  83937.00, 1559.83,  239.98,  264.86, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.56, 3,   boost,   59.37,  83897.00, 1563.71,  243.86,  265.45, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.57, 3,   boost,   59.37,  83874.00, 1565.94,  246.09,  266.05, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.58, 3,   boost,   59.37,  83898.00, 1563.62,  243.76,  266.64, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.59, 3,   boost,   58.84,  83880.00, 1565.36,  245.51,  267.23, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.60, 3,   boost,   58.84,  83840.00, 1569.24,  249.39,  267.82, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.61, 3,   boost,   58.84,  83792.00, 1573.90,  254.05,  268.41, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.62, 3,   boost,   58.84,  83810.00, 1572.15,  252.30,  268.99, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.63, 3,   boost,   58.31,  83792.00, 1573.90,  254.05,  269.58, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.64, 3,   boost,   58.31,  83730.00, 1579.92,  260.07,  270.16, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.65, 3,   boost,   57.78,  83727.00, 1580.21,  260.36,  270.74, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.66, 3,   boost,   57.78,  83706.00, 1582.25,  262.40,  271.32, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.67, 3,   boost,   57.78,  83701.00, 1582.74,  262.88,  271.90, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.68, 3,   boost,   57.78,  83700.00, 1582.84,  262.98,  272.48, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.69, 3,   boost,   57.78,  83660.00, 1586.73,  266.87,  273.06, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.70, 3,   boost,   57.78,  83695.00, 1583.32,  263.47,  273.63, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.71, 3,   boost,   57.78,  83624.00, 1590.23,  270.37,  274.21, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.72, 3,   boost,   57.25,  83628.00, 1589.84,  269.98,  274.78, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.73, 3,   boost,   57.25,  83611.00, 1591.49,  271.63,  275.36, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.74, 3,   boost,   56.72,  83599.00, 1592.66,  272.80,  275.93, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.75, 3,   boost,   56.72,  83597.00, 1592.85,  273.00,  276.50, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.76, 3,   boost,   56.72,  83580.00, 1594.51,  274.65,  277.06, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.77, 3,   boost,   56.72,  83553.00, 1597.13,  277.28,  277.63, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.78, 3,   boost,   56.72,  83576.00, 1594.89,  275.04,  278.20, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.79, 3,   boost,   56.19,  83549.00, 1597.52,  277.67,  278.76, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.80, 3,   boost,   56.19,  83524.00, 1599.95,  280.10,  279.32, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.81, 3,   boost,   56.19,  83517.00, 1600.64,  280.78,  279.88, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.82, 3,   boost,   55.66,  83486.00, 1603.65,  283.80,  280.44, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.83, 3,   boost,   55.66,  83492.00, 1603.07,  283.21,  281.00, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.84, 3,   boost,   55.66,  83449.00, 1607.26,  287.40,  281.56, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.85, 3,   boost,   55.13,  83442.00, 1607.94,  288.08,  282.11, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.86, 3,   boost,   54.60,  83433.00, 1608.82,  288.96,  282.66, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.86, 3,   boost,   54.60,  83433.00, 1608.82,  288.96,  282.66, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.87, 3,   boost,   54.60,  83437.00, 1608.43,  288.57,  283.20, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.88, 3,   boost,   53.54,  83396.00, 1612.42,  292.57,  283.75, 34.0, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.89, 3,   boost,   54.60,  83378.00, 1614.18,  294.32,  284.29, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.90, 3,   boost,   54.60,  83344.00, 1617.49,  297.64,  284.83, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.91, 3,   boost,   54.07,  83336.00, 1618.27,  298.42,  285.37, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.92, 3,   boost,   53.54,  83303.00, 1621.49,  301.63,  285.91, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.93, 3,   boost,   53.54,  83281.00, 1623.64,  303.78,  286.45, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.94, 3,   boost,   53.01,  83270.00, 1624.71,  304.85,  286.98, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.95, 3,   boost,   53.54,  83271.00, 1624.61,  304.76,  287.52, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.96, 3,   boost,   53.54,  83225.00, 1629.10,  309.25,  288.05, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.97, 3,   boost,   53.54,  83222.00, 1629.39,  309.54,  288.59, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.98, 3,   boost,   53.54,  83193.00, 1632.23,  312.37,  289.12, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     3.99, 3,   boost,   53.54,  83204.00, 1631.15,  311.30,  289.66, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.00, 3,   boost,   53.54,  83217.00, 1629.88,  310.03,  290.19, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.01, 3,   boost,   53.01,  83188.00, 1632.71,  312.86,  290.72, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.02, 3,   boost,   53.01,  83145.00, 1636.91,  317.06,  291.26, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.03, 3,   boost,   53.01,  83161.00, 1635.35,  315.50,  291.79, 34.0, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.04, 3,   boost,   53.01,  83121.00, 1639.26,  319.40,  292.32, 34.0, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.05, 3,   boost,   53.01,  83131.00, 1638.28,  318.43,  292.85, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.06, 3,   boost,   52.48,  83107.00, 1640.63,  320.77,  293.37, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.07, 3,   boost,   52.48,  83102.00, 1641.12,  321.26,  293.90, 34.0, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.08, 3,   boost,   52.48,  83072.00, 1644.05,  324.19,  294.42, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.09, 3,   boost,   52.48,  83061.00, 1645.12,  325.27,  294.95, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.10, 3,   boost,   52.48,  83030.00, 1648.16,  328.30,  295.47, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.11, 3,   boost,   52.48,  83034.00, 1647.76,  327.91,  296.00, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.12, 3,   boost,   52.48,  82983.00, 1652.75,  332.90,  296.52, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.13, 3,   boost,   52.48,  83005.00, 1650.60,  330.75,  297.05, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.14, 3,   boost,   52.48,  82923.00, 1658.63,  338.77,  297.57, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.15, 3,   boost,   52.48,  82944.00, 1656.57,  336.71,  298.10, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.16, 3,   boost,   53.01,  82939.00, 1657.06,  337.20,  298.63, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.17, 3,   boost,   52.48,  82891.00, 1661.76,  341.90,  299.15, 33.9, 0.00, 0.00, 3.86, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.18, 3,   boost,   52.48,  82867.00, 1664.11,  344.25,  299.68, 34.0, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.18, 3,   boost,   52.48,  82867.00, 1664.11,  344.25,  299.68, 34.0, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.19, 3,   boost,   52.48,  82860.00, 1664.80,  344.94,  300.20, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.20, 3,   boost,   52.48,  82848.00, 1665.97,  346.12,  300.73, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.21, 3,   boost,   52.48,  82843.00, 1666.46,  346.61,  301.25, 34.0, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.22, 3,   boost,   52.48,  82789.00, 1671.75,  351.90,  301.78, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.23, 3,   boost,   52.48,  82764.00, 1674.21,  354.35,  302.30, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.24, 3,   boost,   52.48,  82734.00, 1677.15,  357.29,  302.83, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.25, 3,   boost,   52.48,  82760.00, 1674.60,  354.74,  303.35, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.26, 3,   boost,   52.48,  82730.00, 1677.54,  357.68,  303.88, 34.0, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.27, 3,   boost,   52.48,  82691.00, 1681.37,  361.51,  304.40, 34.0, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.28, 3,   boost,   51.95,  82682.00, 1682.25,  362.39,  304.92, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.29, 3,   boost,   52.48,  82644.00, 1685.98,  366.12,  305.45, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.30, 3,   boost,   52.48,  82621.00, 1688.24,  368.38,  305.97, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.31, 3,   boost,   52.48,  82591.00, 1691.18,  371.33,  306.50, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.32, 3,   boost,   52.48,  82584.00, 1691.87,  372.02,  307.02, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.33, 3,   boost,   53.01,  82572.00, 1693.05,  373.20,  307.55, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.34, 3,   boost,   53.01,  82588.00, 1691.48,  371.62,  308.08, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.35, 3,   boost,   53.01,  82564.00, 1693.84,  373.98,  308.60, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.36, 3,   boost,   52.48,  82494.00, 1700.72,  380.86,  309.13, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.37, 3,   boost,   52.48,  82505.00, 1699.64,  379.78,  309.65, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.38, 3,   boost,   51.95,  82488.00, 1701.31,  381.45,  310.17, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.39, 3,   boost,   50.89,  82478.00, 1702.29,  382.44,  310.68, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.40, 3,   boost,   49.30,  82451.00, 1704.95,  385.09,  311.17, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.41, 3,   boost,   47.71,  82438.00, 1706.23,  386.37,  311.65, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.42, 3,   boost,   45.59,  82376.00, 1712.33,  392.47,  312.11, 34.0, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.43, 3,   boost,   42.41,  82371.00, 1712.82,  392.96,  312.54, 33.9, 0.00, 0.00, 3.87, 1, 1,  8,  32.9395820,-106.9114157,  1548.0, 2022,  6, 24, 15, 17, 20,        9,      158,  21,  87,   1.5,2147483647.0,2147483647.0,  0, 17, 26,  0,  0, 13,  0,  0,  0,  0, 10, 31, 30, 26,  0,  0,  9,  0, 10, 28,  0,  0,  0, 17,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.44, 3,   boost,   39.23,  82345.00, 1715.38,  395.52,  312.94, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.44, 3,   boost,   39.23,  82345.00, 1715.38,  395.52,  312.94, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.44, 3,   boost,   39.23,  82345.00, 1715.38,  395.52,  312.94, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.44, 3,   boost,   39.23,  82345.00, 1715.38,  395.52,  312.94, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.44, 3,   boost,   39.23,  82345.00, 1715.38,  395.52,  312.94, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.44, 3,   boost,   39.23,  82345.00, 1715.38,  395.52,  312.94, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.45, 3,   boost,   35.52,  82355.00, 1714.39,  394.54,  313.31, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.46, 3,   boost,   31.81,  82309.00, 1718.92,  399.07,  313.65, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.47, 3,   boost,   28.09,  82307.00, 1719.12,  399.26,  313.96, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.48, 3,   boost,   25.44,  82284.00, 1721.39,  401.53,  314.23, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.49, 3,   boost,   22.79,  82282.00, 1721.58,  401.73,  314.48, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.50, 3,   boost,   20.14,  82269.00, 1722.86,  403.01,  314.70, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.50, 3,   boost,   20.14,  82269.00, 1722.86,  403.01,  314.70, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.51, 3,   boost,   18.55,  82261.00, 1723.65,  403.80,  314.90, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.52, 3,   boost,   16.96,  82183.00, 1731.34,  411.49,  315.08, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.53, 3,   boost,   15.37,  82176.00, 1732.03,  412.18,  315.25, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.54, 3,   boost,   15.37,  82163.00, 1733.32,  413.46,  315.41, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.55, 3,   boost,   15.37,  82108.00, 1738.74,  418.89,  315.56, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.56, 3,   boost,   14.31,  82107.00, 1738.84,  418.98,  315.71, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.57, 3,   boost,   13.78,  82076.00, 1741.90,  422.04,  315.85, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.58, 3,   boost,   13.78,  82046.00, 1744.86,  425.01,  315.99, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.59, 3,   boost,   13.78,  81974.00, 1751.98,  432.12,  316.13, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.60, 3,   boost,   13.25,  81964.00, 1752.96,  433.11,  316.27, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.61, 3,   boost,   13.78,  81915.00, 1757.81,  437.95,  316.40, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.62, 3,   boost,   13.25,  81879.00, 1761.37,  441.51,  316.54, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.63, 3,   boost,   13.25,  81891.00, 1760.18,  440.33,  316.67, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.64, 3,   boost,   12.72,  81850.00, 1764.24,  444.38,  316.80, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.65, 3,   boost,   12.72,  81805.00, 1768.69,  448.84,  316.93, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.66, 3,   boost,   12.72,  81797.00, 1769.48,  449.63,  317.06, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.67, 3,   boost,   12.72,  81757.00, 1773.44,  453.59,  317.18, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.68, 3,   boost,   12.19,  81723.00, 1776.81,  456.96,  317.30, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.69, 3,   boost,   11.66,  81699.00, 1779.19,  459.33,  317.42, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.70, 3,   boost,   10.60,  81679.00, 1781.17,  461.32,  317.52, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.71, 3,   boost,    9.54,  81641.00, 1784.94,  465.08,  317.62, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.72, 3,   boost,    7.95,  81659.00, 1783.15,  463.30,  317.70, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.73, 3,   boost,    6.89,  81602.00, 1788.81,  468.95,  317.78, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.74, 3,   boost,    4.77,  81571.00, 1791.88,  472.03,  317.83, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.75, 3,   boost,    2.65,  81569.00, 1792.08,  472.22,  317.87, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.76, 3,   boost,    1.06,  81522.00, 1796.75,  476.89,  317.88, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.77, 3,   boost,   -1.59,  81521.00, 1796.84,  476.99,  317.88, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.78, 3,   boost,   -3.18,  81470.00, 1801.91,  482.05,  317.85, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.79, 3,   boost,   -6.36,  81441.00, 1804.79,  484.93,  317.80, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.80, 3,   boost,   -7.95,  81391.00, 1809.76,  489.90,  317.73, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.81, 3,   boost,  -10.60,  81377.00, 1811.15,  491.29,  317.64, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.82, 3,   boost,  -12.72,  81315.00, 1817.32,  497.46,  317.53, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.82, 3,   boost,  -12.72,  81315.00, 1817.32,  497.46,  317.53, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.83, 3,   boost,  -14.84,  81246.00, 1824.18,  504.33,  317.40, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.84, 3,   boost,  -15.90,  81201.00, 1828.66,  508.81,  317.25, 33.9, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.85, 3,   boost,  -17.49,  81194.00, 1829.36,  509.50,  317.08, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.86, 3,   boost,  -18.55,  81161.00, 1832.65,  512.79,  316.90, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.87, 3,   boost,  -19.61,  81147.00, 1834.04,  514.19,  316.71, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.88, 3,   boost,  -20.67,  81113.00, 1837.43,  517.57,  316.51, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.89, 3,   boost,  -21.20,  81038.00, 1844.91,  525.05,  316.30, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.90, 3,   boost,  -22.26,  81016.00, 1847.10,  527.25,  316.08, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.91, 3,   boost,  -23.85,  80922.00, 1856.49,  536.63,  315.85, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.92, 3,   boost,  -25.44,  80846.00, 1864.08,  544.22,  315.61, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.93, 3,   boost,  -25.44,  80844.00, 1864.28,  544.42,  315.37, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.94, 3,   boost,  -25.44,  80815.00, 1867.18,  547.32,  315.12, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.95, 3,   boost,  -25.44,  80734.00, 1875.28,  555.42,  314.86, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.96, 5,   coast,  -24.91,  80701.00, 1878.58,  558.72,  314.61, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.96, 5,   coast,  -24.91,  80701.00, 1878.58,  558.72,  314.61, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.97, 5,   coast,  -25.44,  80659.00, 1882.78,  562.93,  314.36, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.98, 5,   coast,  -25.44,  80651.00, 1883.59,  563.73,  314.10, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     4.99, 5,   coast,  -25.44,  80650.00, 1883.69,  563.83,  313.85, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.00, 5,   coast,  -25.44,  80552.00, 1893.50,  573.65,  313.60, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.01, 5,   coast,  -25.44,  80556.00, 1893.10,  573.25,  313.34, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.02, 5,   coast,  -24.91,  80524.00, 1896.31,  576.46,  313.09, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.03, 5,   coast,  -24.91,  80492.00, 1899.52,  579.66,  312.84, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.04, 5,   coast,  -24.91,  80432.00, 1905.54,  585.68,  312.59, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.05, 5,   coast,  -24.91,  80433.00, 1905.44,  585.58,  312.34, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.06, 5,   coast,  -24.91,  80364.00, 1912.37,  592.51,  312.09, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.07, 5,   coast,  -24.91,  80346.00, 1914.17,  594.32,  311.84, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.08, 5,   coast,  -24.91,  80292.00, 1919.60,  599.74,  311.60, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.09, 5,   coast,  -24.91,  80262.00, 1922.62,  602.76,  311.35, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.10, 5,   coast,  -24.38,  80232.00, 1925.63,  605.78,  311.10, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.11, 5,   coast,  -24.91,  80190.00, 1929.86,  610.00,  310.85, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.12, 5,   coast,  -24.38,  80173.00, 1931.57,  611.71,  310.61, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.13, 5,   coast,  -24.38,  80156.00, 1933.28,  613.42,  310.36, 34.0, 0.00, 0.00, 3.87, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.14, 5,   coast,  -24.38,  80069.00, 1942.04,  622.18,  310.12, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.14, 5,   coast,  -24.38,  80069.00, 1942.04,  622.18,  310.12, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.15, 5,   coast,  -24.38,  80071.00, 1941.83,  621.98,  309.87, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.16, 5,   coast,  -24.38,  80046.00, 1944.35,  624.50,  309.63, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.17, 5,   coast,  -24.38,  80030.00, 1945.97,  626.11,  309.39, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.18, 5,   coast,  -23.85,  79999.00, 1949.09,  629.23,  309.15, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.19, 5,   coast,  -23.85,  79933.00, 1955.74,  635.89,  308.91, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.20, 5,   coast,  -23.85,  79893.00, 1959.78,  639.92,  308.67, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.21, 5,   coast,  -23.85,  79876.00, 1961.50,  641.64,  308.43, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.22, 5,   coast,  -23.85,  79837.00, 1965.43,  645.58,  308.19, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.23, 5,   coast,  -23.85,  79827.00, 1966.44,  646.59,  307.95, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.24, 5,   coast,  -23.85,  79764.00, 1972.81,  652.95,  307.71, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.25, 5,   coast,  -23.85,  79758.00, 1973.41,  653.56,  307.48, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.26, 5,   coast,  -23.85,  79671.00, 1982.21,  662.35,  307.24, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.27, 5,   coast,  -23.85,  79677.00, 1981.60,  661.74,  307.00, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.28, 5,   coast,  -23.85,  79636.00, 1985.75,  665.89,  306.76, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.29, 5,   coast,  -23.85,  79605.00, 1988.88,  669.03,  306.52, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.30, 5,   coast,  -23.85,  79557.00, 1993.74,  673.89,  306.29, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.31, 5,   coast,  -23.32,  79584.00, 1991.01,  671.15,  306.05, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.32, 5,   coast,  -23.32,  79510.00, 1998.50,  678.65,  305.81, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.33, 5,   coast,  -23.85,  79458.00, 2003.77,  683.91,  305.58, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.34, 5,   coast,  -23.85,  79433.00, 2006.30,  686.45,  305.34, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.35, 5,   coast,  -23.32,  79424.00, 2007.22,  687.36,  305.11, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.36, 5,   coast,  -23.32,  79353.00, 2014.42,  694.56,  304.87, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.37, 5,   coast,  -23.32,  79342.00, 2015.53,  695.68,  304.64, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.38, 5,   coast,  -23.32,  79319.00, 2017.87,  698.01,  304.40, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.39, 5,   coast,  -23.32,  79282.00, 2021.62,  701.77,  304.17, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.40, 5,   coast,  -23.32,  79223.00, 2027.62,  707.76,  303.94, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     5.41, 5,   coast,  -23.32,  79213.00, 2028.63,  708.78,  303.70, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9396675,-106.9115402,  1752.0, 2022,  6, 24, 15, 17, 21,       20,      363, 335,  87,   2.7,2147483647.0,2147483647.0,  0, 10, 29,  0,  0,  9,  0,  0,  0,  0,  0, 25, 26, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 11,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,     5.44, 5,   coast,  -23.32,  79120.00, 2038.09,  718.23,  303.00, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9397878,-106.9117614,  2046.0, 2022,  6, 24, 15, 17, 22,       43,      657, 317,  86,   2.7,2147483647.0,2147483647.0,  0,  8, 29,  0,  0,  8,  0,  0,  0,  0, 30, 31, 25, 26,  0,  0,  0,  0,  0, 13,  0,  0,  0,  0,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,     5.48, 5,   coast,  -22.79,  79014.00, 2048.87,  729.02,  302.08, 34.0, 0.01, 0.00, 3.86, 1, 1,  5,  32.9397878,-106.9117614,  2046.0, 2022,  6, 24, 15, 17, 22,       43,      657, 317,  86,   2.7,2147483647.0,2147483647.0,  0,  8, 29,  0,  0,  8,  0,  0,  0,  0, 30, 31, 25, 26,  0,  0,  0,  0,  0, 13,  0,  0,  0,  0,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,     7.09, 5,   coast,  -19.61,  74292.00, 2541.71, 1221.85,  268.17, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.10, 5,   coast,  -19.08,  74258.00, 2545.35, 1225.49,  267.97, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.11, 5,   coast,  -19.61,  74234.00, 2547.92, 1228.06,  267.78, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.12, 5,   coast,  -19.08,  74207.00, 2550.81, 1230.95,  267.58, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.13, 5,   coast,  -19.08,  74162.00, 2555.63, 1235.77,  267.39, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.14, 5,   coast,  -19.61,  74141.00, 2557.88, 1238.02,  267.20, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.15, 5,   coast,  -19.08,  74116.00, 2560.56, 1240.70,  267.01, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.16, 5,   coast,  -19.08,  74074.00, 2565.07, 1245.21,  266.81, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.17, 5,   coast,  -19.61,  74089.00, 2563.46, 1243.60,  266.62, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.18, 5,   coast,  -19.61,  74056.00, 2567.00, 1247.14,  266.43, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.19, 5,   coast,  -19.61,  74006.00, 2572.36, 1252.51,  266.23, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.20, 5,   coast,  -19.08,  73993.00, 2573.76, 1253.90,  266.04, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.21, 5,   coast,  -19.08,  73956.00, 2577.73, 1257.88,  265.85, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.22, 5,   coast,  -19.08,  73934.00, 2580.10, 1260.24,  265.65, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.23, 5,   coast,  -19.08,  73922.00, 2581.39, 1261.53,  265.46, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.24, 5,   coast,  -19.08,  73872.00, 2586.76, 1266.90,  265.27, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.25, 5,   coast,  -19.08,  73880.00, 2585.90, 1266.04,  265.08, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.26, 5,   coast,  -19.08,  73840.00, 2590.20, 1270.34,  264.89, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.27, 5,   coast,  -19.08,  73796.00, 2594.93, 1275.08,  264.70, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.28, 5,   coast,  -19.08,  73778.00, 2596.87, 1277.02,  264.51, 34.0, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.29, 5,   coast,  -19.08,  73750.00, 2599.88, 1280.03,  264.32, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.30, 5,   coast,  -19.08,  73720.00, 2603.12, 1283.26,  264.13, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.31, 5,   coast,  -19.08,  73716.00, 2603.55, 1283.69,  263.94, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.32, 5,   coast,  -19.08,  73670.00, 2608.50, 1288.65,  263.75, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.33, 5,   coast,  -19.08,  73642.00, 2611.52, 1291.66,  263.56, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.34, 5,   coast,  -19.08,  73622.00, 2613.67, 1293.82,  263.37, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.35, 5,   coast,  -18.55,  73601.00, 2615.94, 1296.08,  263.18, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.36, 5,   coast,  -18.55,  73563.00, 2620.04, 1300.18,  262.99, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.37, 5,   coast,  -19.08,  73549.00, 2621.55, 1301.69,  262.80, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.38, 5,   coast,  -19.08,  73522.00, 2624.46, 1304.61,  262.61, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     7.38, 5,   coast,  -19.08,  73522.00, 2624.46, 1304.61,  262.61, 34.1, 0.00, 0.00, 3.86, 1, 1,  5,  32.9398925,-106.9119807,  2355.0, 2022,  6, 24, 15, 17, 23,       66,      967, 311,  86,   2.7,2147483647.0,2147483647.0,  0,  0, 29,  0,  0,  7,  0,  0,  0,  0, 26, 25, 31, 32,  0,  0,  0,  0,  0, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,     8.15, 5,   coast,  -17.49,  71617.00, 2832.26, 1512.40,  248.51, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,     8.18, 5,   coast,  -17.49,  71562.00, 2838.32, 1518.47,  247.97, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.19, 5,   coast,  -17.49,  71489.00, 2846.38, 1526.52,  247.80, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.20, 5,   coast,  -18.02,  71490.00, 2846.27, 1526.41,  247.62, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.21, 5,   coast,  -17.49,  71462.00, 2849.36, 1529.51,  247.44, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.22, 5,   coast,  -17.49,  71436.00, 2852.23, 1532.38,  247.27, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.23, 5,   coast,  -17.49,  71430.00, 2852.90, 1533.04,  247.09, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.24, 5,   coast,  -17.49,  71395.00, 2856.76, 1536.91,  246.92, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.25, 5,   coast,  -17.49,  71373.00, 2859.20, 1539.34,  246.74, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.26, 5,   coast,  -17.49,  71330.00, 2863.95, 1544.10,  246.57, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.27, 5,   coast,  -17.49,  71301.00, 2867.16, 1547.30,  246.39, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.28, 5,   coast,  -17.49,  71267.00, 2870.92, 1551.07,  246.22, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,     8.29, 5,   coast,  -17.49,  71255.00, 2872.25, 1552.39,  246.04, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,     8.31, 5,   coast,  -17.49,  71256.00, 2872.14, 1552.28,  245.69, 34.1, 0.00, 0.00, 3.86, 1, 1,  7,  32.9400176,-106.9122829,  2672.0, 2022,  6, 24, 15, 17, 24,       96,     1286, 306,  86,   1.9,2147483647.0,2147483647.0,  0, 23, 29,  0,  0,  7,  0,  0,  0,  0, 31, 30, 25, 27,  0,  0, 30,  0,  0, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,     9.00, 5,   coast,  -16.43,  69664.00, 3049.99, 1730.13,  233.87, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.01, 5,   coast,  -16.96,  69644.00, 3052.25, 1732.39,  233.71, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.02, 5,   coast,  -16.43,  69623.00, 3054.61, 1734.76,  233.54, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,     9.08, 5,   coast,  -16.43,  69499.00, 3068.61, 1748.76,  232.55, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,     9.12, 5,   coast,  -16.43,  69401.00, 3079.69, 1759.83,  231.89, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.13, 5,   coast,  -16.43,  69390.00, 3080.93, 1761.08,  231.73, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.14, 5,   coast,  -16.43,  69389.00, 3081.04, 1761.19,  231.56, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,     9.18, 5,   coast,  -16.43,  69283.00, 3093.04, 1773.19,  230.90, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,     9.26, 5,   coast,  -16.43,  69127.00, 3110.72, 1790.87,  229.59, 34.1, 0.00, 0.00, 3.87, 1, 1,  8,  32.9401306,-106.9125807,  2992.0, 2022,  6, 24, 15, 17, 25,      126,     1607, 303,  85,   1.9,2147483647.0,2147483647.0,  0, 30, 27,  0,  0, 24,  0,  0,  0,  0, 30, 31, 28, 28,  0,  0, 25,  0, 25, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,     9.57, 5,   coast,  -15.90,  68475.00, 3184.98, 1865.12,  224.55, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.58, 5,   coast,  -15.90,  68466.00, 3186.01, 1866.15,  224.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.59, 5,   coast,  -15.90,  68439.00, 3189.10, 1869.24,  224.23, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.60, 5,   coast,  -15.90,  68413.00, 3192.07, 1872.21,  224.07, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.61, 5,   coast,  -15.90,  68383.00, 3195.50, 1875.65,  223.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.62, 5,   coast,  -15.90,  68383.00, 3195.50, 1875.65,  223.76, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.62, 5,   coast,  -15.90,  68383.00, 3195.50, 1875.65,  223.76, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.63, 5,   coast,  -15.90,  68351.00, 3199.17, 1879.31,  223.60, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.64, 5,   coast,  -15.90,  68327.00, 3201.91, 1882.06,  223.44, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.65, 5,   coast,  -15.90,  68308.00, 3204.09, 1884.23,  223.28, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.66, 5,   coast,  -15.90,  68293.00, 3205.81, 1885.95,  223.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.67, 5,   coast,  -15.90,  68255.00, 3210.16, 1890.31,  222.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.68, 5,   coast,  -15.90,  68237.00, 3212.23, 1892.37,  222.80, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.69, 5,   coast,  -15.90,  68239.00, 3212.00, 1892.14,  222.64, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.70, 5,   coast,  -15.90,  68217.00, 3214.52, 1894.66,  222.48, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.71, 5,   coast,  -15.90,  68186.00, 3218.08, 1898.22,  222.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.72, 5,   coast,  -15.90,  68170.00, 3219.91, 1900.06,  222.17, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.73, 5,   coast,  -15.90,  68138.00, 3223.58, 1903.73,  222.01, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.74, 5,   coast,  -15.90,  68117.00, 3225.99, 1906.14,  221.85, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.75, 5,   coast,  -15.90,  68124.00, 3225.19, 1905.34,  221.69, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.76, 5,   coast,  -15.90,  68094.00, 3228.64, 1908.78,  221.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.77, 5,   coast,  -15.90,  68051.00, 3233.58, 1913.72,  221.37, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.78, 5,   coast,  -15.90,  68059.00, 3232.66, 1912.80,  221.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.79, 5,   coast,  -15.90,  68028.00, 3236.22, 1916.36,  221.05, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.80, 5,   coast,  -15.37,  67987.00, 3240.93, 1921.08,  220.90, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.81, 5,   coast,  -15.90,  67969.00, 3243.00, 1923.15,  220.74, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.82, 5,   coast,  -15.90,  67944.00, 3245.88, 1926.02,  220.58, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.83, 5,   coast,  -15.90,  67929.00, 3247.60, 1927.75,  220.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.84, 5,   coast,  -15.37,  67925.00, 3248.06, 1928.21,  220.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.85, 5,   coast,  -15.90,  67889.00, 3252.21, 1932.35,  220.11, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.86, 5,   coast,  -15.90,  67872.00, 3254.17, 1934.31,  219.95, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.87, 5,   coast,  -15.90,  67870.00, 3254.40, 1934.54,  219.79, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.88, 5,   coast,  -15.90,  67825.00, 3259.58, 1939.72,  219.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.89, 5,   coast,  -15.90,  67809.00, 3261.42, 1941.57,  219.47, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.90, 5,   coast,  -15.37,  67808.00, 3261.54, 1941.68,  219.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.91, 5,   coast,  -15.90,  67754.00, 3267.76, 1947.91,  219.16, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.92, 5,   coast,  -15.90,  67754.00, 3267.76, 1947.91,  219.00, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.93, 5,   coast,  -15.90,  67754.00, 3267.76, 1947.91,  218.84, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.94, 5,   coast,  -15.90,  67717.00, 3272.03, 1952.17,  218.68, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.94, 5,   coast,  -15.90,  67717.00, 3272.03, 1952.17,  218.68, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.95, 5,   coast,  -15.90,  67705.00, 3273.41, 1953.56,  218.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.96, 5,   coast,  -15.37,  67677.00, 3276.65, 1956.79,  218.37, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.97, 5,   coast,  -15.90,  67660.00, 3278.61, 1958.75,  218.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.98, 5,   coast,  -15.37,  67646.00, 3280.22, 1960.37,  218.05, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,     9.99, 5,   coast,  -15.90,  67613.00, 3284.03, 1964.18,  217.90, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.00, 5,   coast,  -15.37,  67638.00, 3281.15, 1961.29,  217.74, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.01, 5,   coast,  -15.90,  67617.00, 3283.57, 1963.72,  217.58, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.02, 5,   coast,  -15.90,  67592.00, 3286.46, 1966.60,  217.43, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.03, 5,   coast,  -15.37,  67580.00, 3287.85, 1967.99,  217.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.04, 5,   coast,  -15.90,  67547.00, 3291.66, 1971.81,  217.11, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.05, 5,   coast,  -15.37,  67525.00, 3294.20, 1974.35,  216.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.06, 5,   coast,  -15.37,  67500.00, 3297.10, 1977.24,  216.80, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.07, 5,   coast,  -15.37,  67480.00, 3299.41, 1979.55,  216.65, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.08, 5,   coast,  -15.37,  67476.00, 3299.87, 1980.02,  216.50, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.09, 5,   coast,  -15.37,  67436.00, 3304.50, 1984.65,  216.34, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.10, 5,   coast,  -15.37,  67434.00, 3304.73, 1984.88,  216.19, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.11, 5,   coast,  -15.37,  67396.00, 3309.13, 1989.28,  216.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.12, 5,   coast,  -15.37,  67415.00, 3306.93, 1987.08,  215.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.13, 5,   coast,  -15.37,  67386.00, 3310.29, 1990.43,  215.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.14, 5,   coast,  -15.37,  67386.00, 3310.29, 1990.43,  215.57, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.15, 5,   coast,  -15.37,  67338.00, 3315.85, 1996.00,  215.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.16, 5,   coast,  -15.37,  67347.00, 3314.81, 1994.95,  215.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.17, 5,   coast,  -15.37,  67298.00, 3320.49, 2000.63,  215.11, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.18, 5,   coast,  -15.37,  67314.00, 3318.63, 1998.78,  214.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.19, 5,   coast,  -15.37,  67254.00, 3325.59, 2005.74,  214.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.20, 5,   coast,  -15.37,  67237.00, 3327.56, 2007.71,  214.65, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.21, 5,   coast,  -15.37,  67227.00, 3328.72, 2008.87,  214.50, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.22, 5,   coast,  -15.37,  67200.00, 3331.86, 2012.00,  214.34, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.23, 5,   coast,  -15.37,  67202.00, 3331.62, 2011.77,  214.19, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.24, 5,   coast,  -15.37,  67157.00, 3336.85, 2016.99,  214.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.25, 5,   coast,  -15.37,  67116.00, 3341.61, 2021.76,  213.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.26, 5,   coast,  -15.37,  67126.00, 3340.45, 2020.60,  213.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.26, 5,   coast,  -15.37,  67126.00, 3340.45, 2020.60,  213.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.27, 5,   coast,  -15.37,  67125.00, 3340.57, 2020.71,  213.58, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.28, 5,   coast,  -15.37,  67066.00, 3347.42, 2027.57,  213.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.29, 5,   coast,  -15.37,  67050.00, 3349.28, 2029.43,  213.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.30, 5,   coast,  -15.37,  67043.00, 3350.10, 2030.24,  213.11, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.31, 5,   coast,  -15.37,  67006.00, 3354.40, 2034.55,  212.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.32, 5,   coast,  -15.37,  66973.00, 3358.24, 2038.39,  212.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.33, 5,   coast,  -15.37,  66968.00, 3358.83, 2038.97,  212.65, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.34, 5,   coast,  -15.37,  66966.00, 3359.06, 2039.20,  212.50, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.35, 5,   coast,  -15.37,  66939.00, 3362.20, 2042.35,  212.35, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.36, 5,   coast,  -15.37,  66896.00, 3367.21, 2047.35,  212.19, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.37, 5,   coast,  -15.37,  66886.00, 3368.38, 2048.52,  212.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.38, 5,   coast,  -15.37,  66880.00, 3369.07, 2049.22,  211.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.39, 5,   coast,  -15.37,  66870.00, 3370.24, 2050.38,  211.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.40, 5,   coast,  -15.37,  66839.00, 3373.85, 2054.00,  211.58, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.41, 5,   coast,  -15.37,  66815.00, 3376.65, 2056.80,  211.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.42, 5,   coast,  -15.37,  66831.00, 3374.79, 2054.93,  211.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.43, 5,   coast,  -15.37,  66800.00, 3378.40, 2058.55,  211.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.44, 5,   coast,  -15.37,  66775.00, 3381.32, 2061.46,  210.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9402495,-106.9128292,  3282.0, 2022,  6, 24, 15, 17, 26,      153,     1898, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 26,  0,  0,  0,  0, 31, 24, 28, 32,  0,  0, 30,  0, 26, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    10.45, 5,   coast,  -15.37,  66765.00, 3382.48, 2062.63,  210.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    10.45, 5,   coast,  -15.37,  66765.00, 3382.48, 2062.63,  210.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    10.46, 5,   coast,  -15.37,  66725.00, 3387.15, 2067.30,  210.66, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    10.47, 5,   coast,  -14.84,  66734.00, 3386.10, 2066.25,  210.50, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    10.48, 5,   coast,  -15.37,  66701.00, 3389.96, 2070.10,  210.35, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    11.00, 5,   coast,  -14.84,  65749.00, 3501.78, 2181.93,  202.60, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.01, 5,   coast,  -14.84,  65754.00, 3501.19, 2181.33,  202.45, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.02, 5,   coast,  -14.84,  65715.00, 3505.80, 2185.94,  202.30, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    11.04, 5,   coast,  -14.84,  65681.00, 3509.82, 2189.96,  202.01, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.05, 5,   coast,  -14.84,  65657.00, 3512.66, 2192.80,  201.86, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.06, 5,   coast,  -14.84,  65640.00, 3514.67, 2194.81,  201.71, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    11.08, 5,   coast,  -14.84,  65608.00, 3518.45, 2198.60,  201.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.09, 5,   coast,  -14.31,  65596.00, 3519.88, 2200.02,  201.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.10, 5,   coast,  -14.84,  65584.00, 3521.30, 2201.44,  201.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.11, 5,   coast,  -14.84,  65551.00, 3525.20, 2205.35,  200.97, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.12, 5,   coast,  -14.84,  65543.00, 3526.15, 2206.30,  200.82, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.13, 5,   coast,  -14.84,  65505.00, 3530.65, 2210.80,  200.68, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.14, 5,   coast,  -14.31,  65532.00, 3527.45, 2207.60,  200.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    11.16, 5,   coast,  -14.84,  65479.00, 3533.73, 2213.88,  200.24, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.17, 5,   coast,  -14.84,  65467.00, 3535.16, 2215.30,  200.09, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.18, 5,   coast,  -14.84,  65429.00, 3539.66, 2219.81,  199.94, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.19, 5,   coast,  -14.84,  65414.00, 3541.44, 2221.59,  199.79, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.20, 5,   coast,  -14.84,  65375.00, 3546.07, 2226.22,  199.64, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.21, 5,   coast,  -14.84,  65399.00, 3543.22, 2223.37,  199.50, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.22, 5,   coast,  -14.31,  65360.00, 3547.85, 2228.00,  199.35, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.22, 5,   coast,  -14.31,  65360.00, 3547.85, 2228.00,  199.35, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.23, 5,   coast,  -14.31,  65359.00, 3547.97, 2228.12,  199.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.24, 5,   coast,  -14.31,  65340.00, 3550.23, 2230.37,  199.06, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.25, 5,   coast,  -14.31,  65317.00, 3552.96, 2233.10,  198.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.26, 5,   coast,  -14.31,  65295.00, 3555.57, 2235.72,  198.78, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.27, 5,   coast,  -14.31,  65297.00, 3555.33, 2235.48,  198.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    11.29, 5,   coast,  -14.31,  65266.00, 3559.02, 2239.16,  198.35, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.30, 5,   coast,  -14.31,  65242.00, 3561.87, 2242.02,  198.20, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.31, 5,   coast,  -14.31,  65227.00, 3563.65, 2243.80,  198.06, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.32, 5,   coast,  -14.31,  65187.00, 3568.41, 2248.56,  197.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.33, 5,   coast,  -14.31,  65167.00, 3570.79, 2250.94,  197.77, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.34, 5,   coast,  -14.31,  65172.00, 3570.20, 2250.34,  197.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.35, 5,   coast,  -14.31,  65158.00, 3571.86, 2252.01,  197.49, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.36, 5,   coast,  -14.31,  65123.00, 3576.03, 2256.17,  197.34, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.37, 5,   coast,  -14.31,  65125.00, 3575.79, 2255.94,  197.20, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.38, 5,   coast,  -14.31,  65100.00, 3578.77, 2258.91,  197.06, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.39, 5,   coast,  -14.31,  65093.00, 3579.60, 2259.75,  196.91, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.40, 5,   coast,  -14.31,  65082.00, 3580.91, 2261.06,  196.77, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.41, 5,   coast,  -14.31,  65036.00, 3586.39, 2266.54,  196.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.42, 5,   coast,  -14.31,  65050.00, 3584.73, 2264.87,  196.49, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.43, 5,   coast,  -14.31,  65017.00, 3588.66, 2268.80,  196.34, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9403811,-106.9130665,  3527.0, 2022,  6, 24, 15, 17, 27,      179,     2145, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 27, 29,  0,  0, 31,  0, 26, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    11.44, 5,   coast,  -14.31,  65002.00, 3590.45, 2270.59,  196.20, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    12.11, 5,   coast,  -13.78,  63901.00, 3722.65, 2402.79,  186.74, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.12, 5,   coast,  -13.78,  63881.00, 3725.07, 2405.21,  186.60, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.13, 5,   coast,  -13.78,  63863.00, 3727.25, 2407.39,  186.46, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.14, 5,   coast,  -13.78,  63862.00, 3727.37, 2407.51,  186.33, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.15, 5,   coast,  -13.78,  63834.00, 3730.75, 2410.90,  186.19, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.16, 5,   coast,  -13.78,  63836.00, 3730.51, 2410.66,  186.05, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.17, 5,   coast,  -13.78,  63795.00, 3735.48, 2415.62,  185.91, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.18, 5,   coast,  -13.78,  63782.00, 3737.05, 2417.19,  185.78, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.18, 5,   coast,  -13.78,  63782.00, 3737.05, 2417.19,  185.78, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.19, 5,   coast,  -13.78,  63759.00, 3739.83, 2419.98,  185.64, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.20, 5,   coast,  -13.78,  63763.00, 3739.35, 2419.49,  185.50, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.21, 5,   coast,  -13.78,  63727.00, 3743.71, 2423.86,  185.36, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.22, 5,   coast,  -13.78,  63729.00, 3743.47, 2423.61,  185.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.23, 5,   coast,  -13.78,  63726.00, 3743.83, 2423.98,  185.09, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.24, 5,   coast,  -13.78,  63672.00, 3750.38, 2430.52,  184.95, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.25, 5,   coast,  -13.78,  63668.00, 3750.86, 2431.01,  184.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.26, 5,   coast,  -13.78,  63652.00, 3752.80, 2432.95,  184.67, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.27, 5,   coast,  -13.78,  63653.00, 3752.68, 2432.83,  184.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.28, 5,   coast,  -13.78,  63651.00, 3752.93, 2433.07,  184.40, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.29, 5,   coast,  -13.78,  63619.00, 3756.81, 2436.95,  184.26, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.30, 5,   coast,  -13.78,  63585.00, 3760.93, 2441.08,  184.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.31, 5,   coast,  -13.78,  63575.00, 3762.15, 2442.29,  183.98, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.32, 5,   coast,  -13.78,  63560.00, 3763.97, 2444.11,  183.85, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.33, 5,   coast,  -13.78,  63544.00, 3765.91, 2446.06,  183.71, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.34, 5,   coast,  -13.78,  63519.00, 3768.95, 2449.09,  183.57, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.35, 5,   coast,  -13.78,  63499.00, 3771.38, 2451.52,  183.43, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.36, 5,   coast,  -13.78,  63510.00, 3770.04, 2450.19,  183.29, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.37, 5,   coast,  -13.78,  63498.00, 3771.50, 2451.65,  183.16, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.38, 5,   coast,  -13.78,  63469.00, 3775.03, 2455.17,  183.02, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.39, 5,   coast,  -13.78,  63475.00, 3774.30, 2454.44,  182.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.40, 5,   coast,  -13.78,  63454.00, 3776.85, 2456.99,  182.74, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    12.41, 5,   coast,  -13.78,  63432.00, 3779.53, 2459.67,  182.61, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9404925,-106.9132855,  3755.0, 2022,  6, 24, 15, 17, 28,      203,     2374, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 31, 27,  0,  0, 32,  0,  0,  0,  0, 30, 31, 29, 29,  0,  0, 25,  0, 26, 25,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    13.05, 5,   coast,  -13.25,  62462.00, 3898.25, 2578.39,  174.03, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.06, 5,   coast,  -13.25,  62471.00, 3897.14, 2577.28,  173.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.07, 5,   coast,  -13.25,  62441.00, 3900.83, 2580.98,  173.76, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.08, 5,   coast,  -13.25,  62441.00, 3900.83, 2580.98,  173.63, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.09, 5,   coast,  -13.25,  62425.00, 3902.81, 2582.95,  173.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.10, 5,   coast,  -13.25,  62400.00, 3905.89, 2586.03,  173.36, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.11, 5,   coast,  -13.25,  62380.00, 3908.35, 2588.50,  173.23, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.12, 5,   coast,  -13.25,  62371.00, 3909.46, 2589.61,  173.10, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.13, 5,   coast,  -13.25,  62369.00, 3909.71, 2589.85,  172.97, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.14, 5,   coast,  -13.25,  62366.00, 3910.08, 2590.22,  172.83, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.14, 5,   coast,  -13.25,  62366.00, 3910.08, 2590.22,  172.83, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.15, 5,   coast,  -13.25,  62332.00, 3914.27, 2594.42,  172.70, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.16, 5,   coast,  -13.25,  62328.00, 3914.76, 2594.91,  172.57, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.17, 5,   coast,  -13.25,  62312.00, 3916.74, 2596.88,  172.44, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.18, 5,   coast,  -13.25,  62298.00, 3918.47, 2598.61,  172.30, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.19, 5,   coast,  -13.25,  62268.00, 3922.17, 2602.31,  172.17, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.20, 5,   coast,  -13.25,  62250.00, 3924.39, 2604.54,  172.04, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.21, 5,   coast,  -13.25,  62266.00, 3922.42, 2602.56,  171.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.22, 5,   coast,  -13.25,  62213.00, 3928.96, 2609.11,  171.77, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.23, 5,   coast,  -13.25,  62198.00, 3930.82, 2610.96,  171.64, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.24, 5,   coast,  -13.25,  62201.00, 3930.45, 2610.59,  171.51, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.25, 5,   coast,  -13.25,  62160.00, 3935.51, 2615.66,  171.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.26, 5,   coast,  -13.25,  62181.00, 3932.92, 2613.06,  171.24, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.27, 5,   coast,  -13.25,  62146.00, 3937.25, 2617.39,  171.11, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.28, 5,   coast,  -13.25,  62152.00, 3936.50, 2616.65,  170.98, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.29, 5,   coast,  -12.72,  62143.00, 3937.62, 2617.76,  170.85, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.30, 5,   coast,  -13.25,  62107.00, 3942.07, 2622.21,  170.72, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.31, 5,   coast,  -13.25,  62110.00, 3941.70, 2621.84,  170.59, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.32, 5,   coast,  -12.72,  62095.00, 3943.55, 2623.70,  170.46, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.33, 5,   coast,  -13.25,  62041.00, 3950.24, 2630.38,  170.32, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.34, 5,   coast,  -13.25,  62060.00, 3947.89, 2628.03,  170.19, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    13.35, 5,   coast,  -12.72,  62031.00, 3951.48, 2631.62,  170.06, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9406101,-106.9134959,  3964.0, 2022,  6, 24, 15, 17, 29,      227,     2584, 303,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 23, 29, 30,  0,  0, 30,  0, 31, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    14.00, 5,   coast,  -12.72,  61145.00, 4061.85, 2742.00,  161.75, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    14.03, 5,   coast,  -12.72,  61125.00, 4064.36, 2744.50,  161.36, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    14.05, 5,   coast,  -12.72,  61097.00, 4067.87, 2748.01,  161.11, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.06, 5,   coast,  -12.19,  61094.00, 4068.24, 2748.39,  160.99, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.07, 5,   coast,  -12.72,  61073.00, 4070.88, 2751.02,  160.86, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.08, 5,   coast,  -12.19,  61056.00, 4073.01, 2753.15,  160.74, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    14.12, 5,   coast,  -12.19,  61005.00, 4079.41, 2759.55,  160.24, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    14.15, 5,   coast,  -12.19,  60998.00, 4080.29, 2760.43,  159.87, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.16, 5,   coast,  -11.66,  60982.00, 4082.30, 2762.44,  159.75, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.17, 5,   coast,  -12.19,  60949.00, 4086.44, 2766.59,  159.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.18, 5,   coast,  -11.66,  60949.00, 4086.44, 2766.59,  159.52, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    14.20, 5,   coast,  -12.19,  60923.00, 4089.71, 2769.85,  159.28, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.21, 5,   coast,  -12.19,  60903.00, 4092.22, 2772.37,  159.16, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.22, 5,   coast,  -12.19,  60894.00, 4093.35, 2773.50,  159.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.23, 5,   coast,  -11.66,  60886.00, 4094.36, 2774.51,  158.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.24, 5,   coast,  -11.66,  60884.00, 4094.61, 2774.76,  158.80, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.25, 5,   coast,  -11.66,  60878.00, 4095.37, 2775.51,  158.68, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.26, 5,   coast,  -12.19,  60849.00, 4099.01, 2779.16,  158.56, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.27, 5,   coast,  -12.19,  60826.00, 4101.91, 2782.05,  158.44, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.28, 5,   coast,  -11.66,  60810.00, 4103.92, 2784.07,  158.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    14.29, 5,   coast,  -12.19,  60782.00, 4107.45, 2787.59,  158.20, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407079,-106.9137082,  4157.0, 2022,  6, 24, 15, 17, 30,      250,     2778, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 27,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 29,  0,  0, 29,  0, 26, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    14.93, 5,   coast,  -12.19,  60018.00, 4204.13, 2884.28,  150.43, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    14.94, 5,   coast,  -12.19,  60022.00, 4203.63, 2883.77,  150.30, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    14.95, 5,   coast,  -12.19,  60002.00, 4206.17, 2886.31,  150.18, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    14.96, 5,   coast,  -12.19,  59987.00, 4208.08, 2888.22,  150.06, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    14.97, 5,   coast,  -12.19,  59974.00, 4209.73, 2889.88,  149.94, 34.0, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    14.98, 5,   coast,  -12.19,  59974.00, 4209.73, 2889.88,  149.82, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    14.99, 5,   coast,  -12.19,  59942.00, 4213.81, 2893.95,  149.69, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.00, 5,   coast,  -12.19,  59934.00, 4214.83, 2894.97,  149.57, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.01, 5,   coast,  -12.19,  59924.00, 4216.10, 2896.24,  149.45, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.02, 5,   coast,  -12.19,  59899.00, 4219.28, 2899.43,  149.33, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.03, 5,   coast,  -12.19,  59894.00, 4219.92, 2900.07,  149.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.04, 5,   coast,  -12.19,  59904.00, 4218.65, 2898.79,  149.08, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.05, 5,   coast,  -12.19,  59902.00, 4218.90, 2899.05,  148.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.06, 5,   coast,  -12.19,  59863.00, 4223.87, 2904.02,  148.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.06, 5,   coast,  -12.19,  59863.00, 4223.87, 2904.02,  148.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.07, 5,   coast,  -12.19,  59849.00, 4225.66, 2905.80,  148.72, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.08, 5,   coast,  -12.19,  59844.00, 4226.29, 2906.44,  148.60, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.09, 5,   coast,  -12.19,  59822.00, 4229.10, 2909.24,  148.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.10, 5,   coast,  -12.19,  59801.00, 4231.78, 2911.92,  148.35, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.11, 5,   coast,  -12.19,  59789.00, 4233.31, 2913.45,  148.23, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.12, 5,   coast,  -12.19,  59801.00, 4231.78, 2911.92,  148.11, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.13, 5,   coast,  -12.19,  59792.00, 4232.93, 2913.07,  147.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.14, 5,   coast,  -12.19,  59762.00, 4236.76, 2916.90,  147.87, 34.0, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.15, 5,   coast,  -12.19,  59726.00, 4241.35, 2921.50,  147.74, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.16, 5,   coast,  -12.19,  59750.00, 4238.29, 2918.43,  147.62, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.17, 5,   coast,  -12.19,  59737.00, 4239.95, 2920.09,  147.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.18, 5,   coast,  -12.19,  59685.00, 4246.59, 2926.73,  147.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.19, 5,   coast,  -12.19,  59708.00, 4243.65, 2923.79,  147.26, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.20, 5,   coast,  -12.19,  59689.00, 4246.08, 2926.22,  147.13, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.21, 5,   coast,  -12.19,  59671.00, 4248.38, 2928.52,  147.01, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.22, 5,   coast,  -12.19,  59666.00, 4249.02, 2929.16,  146.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.23, 5,   coast,  -12.19,  59656.00, 4250.30, 2930.44,  146.77, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    15.25, 5,   coast,  -12.19,  59616.00, 4255.41, 2935.55,  146.52, 34.1, 0.00, 0.00, 3.86, 1, 1, 11,  32.9407978,-106.9139161,  4339.0, 2022,  6, 24, 15, 17, 31,      271,     2961, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 28,  0,  0,  0,  0, 29, 23, 28, 30,  0,  0, 30,  0, 32, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    15.93, 5,   coast,  -11.66,  58895.00, 4348.08, 3028.22,  138.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    15.94, 5,   coast,  -11.66,  58860.00, 4352.60, 3032.75,  138.20, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    16.04, 5,   coast,  -11.66,  58749.00, 4366.96, 3047.10,  137.03, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    16.07, 5,   coast,  -11.66,  58715.00, 4371.36, 3051.50,  136.68, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    16.09, 5,   coast,  -11.66,  58700.00, 4373.30, 3053.45,  136.45, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    16.14, 5,   coast,  -11.66,  58634.00, 4381.85, 3062.00,  135.87, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    16.15, 5,   coast,  -11.66,  58659.00, 4378.61, 3058.76,  135.75, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    16.16, 5,   coast,  -11.66,  58643.00, 4380.69, 3060.83,  135.63, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    16.17, 5,   coast,  -11.66,  58633.00, 4381.98, 3062.13,  135.52, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    16.37, 5,   coast,  -11.66,  58388.00, 4413.80, 3093.94,  133.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9408958,-106.9141167,  4500.0, 2022,  6, 24, 15, 17, 32,      293,     3124, 302,  85,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 27,  0,  0,  0,  0, 30, 30, 30, 22,  0,  0, 29,  0, 26, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    16.98, 5,   coast,  -11.13,  57789.00, 4492.04, 3172.18,  126.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    16.98, 5,   coast,  -11.13,  57789.00, 4492.04, 3172.18,  126.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    16.99, 5,   coast,  -11.13,  57817.00, 4488.37, 3168.51,  125.97, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.00, 5,   coast,  -11.66,  57807.00, 4489.68, 3169.82,  125.86, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.01, 5,   coast,  -11.66,  57767.00, 4494.92, 3175.07,  125.74, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    17.03, 5,   coast,  -11.66,  57754.00, 4496.63, 3176.77,  125.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.04, 5,   coast,  -11.66,  57752.00, 4496.89, 3177.04,  125.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.05, 5,   coast,  -11.66,  57739.00, 4498.60, 3178.74,  125.28, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.06, 5,   coast,  -11.13,  57760.00, 4495.84, 3175.99,  125.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.07, 5,   coast,  -11.66,  57736.00, 4498.99, 3179.14,  125.05, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.08, 5,   coast,  -11.66,  57721.00, 4500.96, 3181.10,  124.93, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.09, 5,   coast,  -11.66,  57697.00, 4504.11, 3184.26,  124.81, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.10, 5,   coast,  -11.66,  57699.00, 4503.85, 3183.99,  124.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.11, 5,   coast,  -11.66,  57707.00, 4502.80, 3182.94,  124.58, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.12, 5,   coast,  -11.66,  57672.00, 4507.40, 3187.54,  124.47, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.13, 5,   coast,  -11.66,  57656.00, 4509.50, 3189.64,  124.35, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.14, 5,   coast,  -11.13,  57657.00, 4509.37, 3189.51,  124.23, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.15, 5,   coast,  -11.66,  57638.00, 4511.86, 3192.01,  124.12, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.16, 5,   coast,  -11.66,  57631.00, 4512.78, 3192.93,  124.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.17, 5,   coast,  -11.66,  57613.00, 4515.15, 3195.29,  123.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.18, 5,   coast,  -11.66,  57623.00, 4513.84, 3193.98,  123.77, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.19, 5,   coast,  -11.66,  57605.00, 4516.20, 3196.35,  123.66, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.20, 5,   coast,  -11.13,  57618.00, 4514.49, 3194.64,  123.54, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.21, 5,   coast,  -11.66,  57596.00, 4517.39, 3197.53,  123.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.22, 5,   coast,  -11.13,  57577.00, 4519.89, 3200.03,  123.31, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.23, 5,   coast,  -11.13,  57585.00, 4518.83, 3198.98,  123.20, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.24, 5,   coast,  -11.13,  57567.00, 4521.20, 3201.34,  123.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.25, 5,   coast,  -11.13,  57569.00, 4520.94, 3201.08,  122.98, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.26, 5,   coast,  -11.66,  57511.00, 4528.57, 3208.72,  122.86, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.27, 5,   coast,  -11.66,  57528.00, 4526.33, 3206.48,  122.75, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.28, 5,   coast,  -11.13,  57519.00, 4527.52, 3207.66,  122.64, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.29, 5,   coast,  -11.13,  57543.00, 4524.36, 3204.50,  122.52, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.30, 5,   coast,  -11.66,  57512.00, 4528.44, 3208.58,  122.41, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.30, 5,   coast,  -11.66,  57512.00, 4528.44, 3208.58,  122.41, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.31, 5,   coast,  -11.13,  57492.00, 4531.07, 3211.22,  122.30, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.32, 5,   coast,  -11.13,  57486.00, 4531.86, 3212.01,  122.18, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.33, 5,   coast,  -11.13,  57469.00, 4534.10, 3214.25,  122.07, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.34, 5,   coast,  -11.66,  57483.00, 4532.26, 3212.40,  121.95, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.35, 5,   coast,  -11.66,  57466.00, 4534.50, 3214.64,  121.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.36, 5,   coast,  -11.66,  57462.00, 4535.03, 3215.17,  121.73, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.37, 5,   coast,  -11.66,  57436.00, 4538.45, 3218.60,  121.61, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.38, 5,   coast,  -11.13,  57437.00, 4538.32, 3218.47,  121.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.39, 5,   coast,  -11.13,  57430.00, 4539.24, 3219.39,  121.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.40, 5,   coast,  -11.13,  57428.00, 4539.51, 3219.65,  121.27, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.41, 5,   coast,  -11.13,  57419.00, 4540.69, 3220.84,  121.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.42, 5,   coast,  -11.13,  57405.00, 4542.54, 3222.68,  121.05, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.43, 5,   coast,  -11.13,  57390.00, 4544.52, 3224.66,  120.94, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.44, 5,   coast,  -11.13,  57377.00, 4546.23, 3226.38,  120.83, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9409998,-106.9142986,  4645.0, 2022,  6, 24, 15, 17, 33,      313,     3270, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 28,  0,  0,  0,  0, 29, 30, 20, 31,  0,  0, 27,  0, 18, 31,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.45, 5,   coast,  -11.13,  57386.00, 4545.05, 3225.19,  120.71, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    17.45, 5,   coast,  -11.13,  57386.00, 4545.05, 3225.19,  120.71, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    18.08, 5,   coast,  -11.13,  56818.00, 4620.27, 3300.42,  113.70, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.09, 5,   coast,  -11.13,  56805.00, 4622.00, 3302.15,  113.59, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.10, 5,   coast,  -11.13,  56795.00, 4623.33, 3303.48,  113.48, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.11, 5,   coast,  -11.13,  56789.00, 4624.13, 3304.27,  113.37, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.12, 5,   coast,  -11.13,  56771.00, 4626.52, 3306.67,  113.26, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.13, 5,   coast,  -11.13,  56787.00, 4624.40, 3304.54,  113.14, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.14, 5,   coast,  -11.13,  56763.00, 4627.59, 3307.73,  113.03, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.15, 5,   coast,  -11.13,  56762.00, 4627.72, 3307.87,  112.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.16, 5,   coast,  -11.13,  56756.00, 4628.52, 3308.66,  112.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.17, 5,   coast,  -11.13,  56741.00, 4630.52, 3310.66,  112.70, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.18, 5,   coast,  -11.13,  56740.00, 4630.65, 3310.79,  112.59, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.19, 5,   coast,  -11.13,  56729.00, 4632.11, 3312.26,  112.48, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.20, 5,   coast,  -11.13,  56724.00, 4632.78, 3312.92,  112.37, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.21, 5,   coast,  -11.13,  56698.00, 4636.24, 3316.39,  112.25, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.22, 5,   coast,  -11.13,  56692.00, 4637.04, 3317.19,  112.14, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.23, 5,   coast,  -11.13,  56682.00, 4638.37, 3318.52,  112.03, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.24, 5,   coast,  -11.13,  56677.00, 4639.04, 3319.19,  111.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.25, 5,   coast,  -11.13,  56682.00, 4638.37, 3318.52,  111.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.26, 5,   coast,  -11.13,  56677.00, 4639.04, 3319.19,  111.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.26, 5,   coast,  -11.13,  56677.00, 4639.04, 3319.19,  111.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.27, 5,   coast,  -11.13,  56669.00, 4640.11, 3320.25,  111.59, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.28, 5,   coast,  -11.13,  56662.00, 4641.04, 3321.18,  111.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.29, 5,   coast,  -11.13,  56652.00, 4642.37, 3322.52,  111.36, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.30, 5,   coast,  -11.13,  56622.00, 4646.37, 3326.52,  111.25, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.31, 5,   coast,  -11.13,  56618.00, 4646.91, 3327.05,  111.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.32, 5,   coast,  -11.13,  56593.00, 4650.24, 3330.38,  111.03, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.33, 5,   coast,  -11.13,  56604.00, 4648.77, 3328.92,  110.92, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.34, 5,   coast,  -11.13,  56598.00, 4649.57, 3329.72,  110.81, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.35, 5,   coast,  -11.13,  56609.00, 4648.11, 3328.25,  110.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.36, 5,   coast,  -11.13,  56594.00, 4650.11, 3330.25,  110.58, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.37, 5,   coast,  -11.13,  56565.00, 4653.98, 3334.12,  110.47, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    18.38, 5,   coast,  -11.13,  56569.00, 4653.44, 3333.59,  110.36, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9410988,-106.9144806,  4778.0, 2022,  6, 24, 15, 17, 34,      334,     3404, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 19,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 30,  0,  0, 28,  0, 20, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    19.01, 5,   coast,  -10.60,  56078.00, 4719.20, 3399.34,  103.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.02, 5,   coast,  -11.13,  56075.00, 4719.60, 3399.75,  103.30, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.03, 5,   coast,  -10.60,  56068.00, 4720.54, 3400.69,  103.19, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.04, 5,   coast,  -10.60,  56050.00, 4722.96, 3403.11,  103.08, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.05, 5,   coast,  -11.13,  56052.00, 4722.69, 3402.84,  102.97, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.06, 5,   coast,  -10.60,  56030.00, 4725.65, 3405.80,  102.87, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.07, 5,   coast,  -10.60,  56030.00, 4725.65, 3405.80,  102.76, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.08, 5,   coast,  -10.60,  56034.00, 4725.11, 3405.26,  102.65, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.09, 5,   coast,  -11.13,  56011.00, 4728.21, 3408.35,  102.54, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.10, 5,   coast,  -11.13,  56014.00, 4727.80, 3407.95,  102.43, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.11, 5,   coast,  -11.13,  55991.00, 4730.90, 3411.04,  102.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.12, 5,   coast,  -11.13,  55985.00, 4731.71, 3411.85,  102.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.13, 5,   coast,  -10.60,  55991.00, 4730.90, 3411.04,  102.10, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.14, 5,   coast,  -11.13,  55987.00, 4731.44, 3411.58,  101.99, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.15, 5,   coast,  -10.60,  55980.00, 4732.38, 3412.52,  101.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.16, 5,   coast,  -11.13,  55952.00, 4736.15, 3416.29,  101.77, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.17, 5,   coast,  -10.60,  55953.00, 4736.01, 3416.16,  101.67, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.18, 5,   coast,  -11.13,  55943.00, 4737.36, 3417.50,  101.56, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.19, 5,   coast,  -10.60,  55947.00, 4736.82, 3416.96,  101.45, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.20, 5,   coast,  -10.60,  55919.00, 4740.59, 3420.74,  101.34, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.21, 5,   coast,  -10.60,  55933.00, 4738.71, 3418.85,  101.24, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.22, 5,   coast,  -10.60,  55912.00, 4741.53, 3421.68,  101.13, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.22, 5,   coast,  -10.60,  55912.00, 4741.53, 3421.68,  101.13, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.23, 5,   coast,  -11.13,  55930.00, 4739.11, 3419.25,  101.02, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.24, 5,   coast,  -10.60,  55912.00, 4741.53, 3421.68,  100.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.25, 5,   coast,  -11.13,  55874.00, 4746.66, 3426.80,  100.81, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.26, 5,   coast,  -10.60,  55886.00, 4745.04, 3425.18,  100.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.27, 5,   coast,  -10.60,  55863.00, 4748.14, 3428.28,  100.59, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.28, 5,   coast,  -10.60,  55882.00, 4745.58, 3425.72,  100.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.29, 5,   coast,  -11.13,  55866.00, 4747.73, 3427.88,  100.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.30, 5,   coast,  -10.60,  55840.00, 4751.24, 3431.38,  100.27, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.31, 5,   coast,  -10.60,  55852.00, 4749.62, 3429.77,  100.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.32, 5,   coast,  -10.60,  55877.00, 4746.25, 3426.39,  100.05, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.33, 5,   coast,  -11.13,  55848.00, 4750.16, 3430.30,   99.95, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    19.34, 5,   coast,  -10.60,  55833.00, 4752.18, 3432.33,   99.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9412057,-106.9146607,  4899.0, 2022,  6, 24, 15, 17, 35,      354,     3527, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 28,  0,  0,  0,  0, 30, 31, 29, 24,  0,  0, 32,  0, 29, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    19.96, 5,   coast,  -10.60,  55392.00, 4811.85, 3492.00,   93.26, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    19.97, 5,   coast,  -10.60,  55381.00, 4813.35, 3493.49,   93.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    19.98, 5,   coast,  -10.60,  55385.00, 4812.80, 3492.95,   93.05, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    19.99, 5,   coast,  -10.60,  55377.00, 4813.89, 3494.03,   92.95, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.00, 5,   coast,  -10.60,  55361.00, 4816.06, 3496.21,   92.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.01, 5,   coast,  -10.60,  55362.00, 4815.93, 3496.07,   92.73, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.02, 5,   coast,  -10.60,  55360.00, 4816.20, 3496.34,   92.63, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.03, 5,   coast,  -10.60,  55366.00, 4815.38, 3495.53,   92.52, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.04, 5,   coast,  -10.60,  55346.00, 4818.10, 3498.24,   92.42, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.05, 5,   coast,  -10.60,  55334.00, 4819.73, 3499.87,   92.31, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.06, 5,   coast,  -10.60,  55316.00, 4822.18, 3502.32,   92.20, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.07, 5,   coast,  -10.60,  55332.00, 4820.00, 3500.15,   92.10, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.08, 5,   coast,  -10.60,  55328.00, 4820.54, 3500.69,   91.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.09, 5,   coast,  -10.60,  55311.00, 4822.85, 3503.00,   91.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.10, 5,   coast,  -10.60,  55281.00, 4826.93, 3507.08,   91.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.11, 5,   coast,  -10.60,  55283.00, 4826.66, 3506.81,   91.67, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.12, 5,   coast,  -10.60,  55283.00, 4826.66, 3506.81,   91.57, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.13, 5,   coast,  -10.60,  55278.00, 4827.34, 3507.48,   91.46, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.14, 5,   coast,  -10.60,  55261.00, 4829.65, 3509.80,   91.36, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.15, 5,   coast,  -10.60,  55272.00, 4828.16, 3508.30,   91.25, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.16, 5,   coast,  -10.60,  55273.00, 4828.02, 3508.16,   91.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.17, 5,   coast,  -10.60,  55259.00, 4829.92, 3510.07,   91.04, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.18, 5,   coast,  -10.60,  55256.00, 4830.33, 3510.48,   90.93, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.18, 5,   coast,  -10.60,  55256.00, 4830.33, 3510.48,   90.93, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.19, 5,   coast,  -10.60,  55241.00, 4832.37, 3512.52,   90.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.20, 5,   coast,  -10.60,  55251.00, 4831.01, 3511.16,   90.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.21, 5,   coast,  -10.60,  55252.00, 4830.88, 3511.02,   90.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.22, 5,   coast,  -10.60,  55229.00, 4834.01, 3514.15,   90.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.23, 5,   coast,  -10.60,  55230.00, 4833.87, 3514.01,   90.40, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.24, 5,   coast,  -10.60,  55210.00, 4836.59, 3516.74,   90.30, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.25, 5,   coast,  -10.60,  55205.00, 4837.27, 3517.42,   90.19, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.26, 5,   coast,  -10.60,  55184.00, 4840.13, 3520.27,   90.08, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.27, 5,   coast,  -10.60,  55183.00, 4840.27, 3520.41,   89.98, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.28, 5,   coast,  -10.60,  55174.00, 4841.49, 3521.64,   89.87, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.29, 5,   coast,  -10.60,  55192.00, 4839.04, 3519.19,   89.77, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.30, 5,   coast,  -10.60,  55172.00, 4841.76, 3521.91,   89.66, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.31, 5,   coast,  -10.60,  55152.00, 4844.49, 3524.63,   89.55, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.32, 5,   coast,  -10.60,  55160.00, 4843.40, 3523.54,   89.45, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.33, 5,   coast,  -10.60,  55167.00, 4842.45, 3522.59,   89.34, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.34, 5,   coast,  -10.60,  55158.00, 4843.67, 3523.82,   89.24, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.35, 5,   coast,  -10.60,  55147.00, 4845.17, 3525.31,   89.13, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.36, 5,   coast,  -10.60,  55168.00, 4842.31, 3522.45,   89.02, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.37, 5,   coast,  -10.60,  55128.00, 4847.76, 3527.90,   88.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.38, 5,   coast,  -10.60,  55110.00, 4850.21, 3530.36,   88.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.39, 5,   coast,  -10.60,  55104.00, 4851.03, 3531.17,   88.71, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.40, 5,   coast,  -10.60,  55114.00, 4849.67, 3529.81,   88.60, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.41, 5,   coast,  -10.60,  55118.00, 4849.12, 3529.27,   88.49, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.42, 5,   coast,  -10.60,  55101.00, 4851.44, 3531.58,   88.39, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.43, 5,   coast,  -10.60,  55083.00, 4853.89, 3534.04,   88.28, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.44, 5,   coast,  -10.60,  55088.00, 4853.21, 3533.35,   88.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9413034,-106.9148371,  5009.0, 2022,  6, 24, 15, 17, 36,      374,     3638, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 29,  0,  0,  0,  0, 30, 29, 29, 31,  0,  0, 31,  0, 28, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    20.45, 5,   coast,  -10.60,  55072.00, 4855.39, 3535.54,   88.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.45, 5,   coast,  -10.60,  55072.00, 4855.39, 3535.54,   88.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.45, 5,   coast,  -10.60,  55072.00, 4855.39, 3535.54,   88.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.45, 5,   coast,  -10.60,  55072.00, 4855.39, 3535.54,   88.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.45, 5,   coast,  -10.60,  55072.00, 4855.39, 3535.54,   88.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.45, 5,   coast,  -10.60,  55072.00, 4855.39, 3535.54,   88.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.46, 5,   coast,  -10.60,  55054.00, 4857.85, 3537.99,   87.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.47, 5,   coast,  -10.60,  55092.00, 4852.67, 3532.81,   87.86, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.48, 5,   coast,  -10.60,  55054.00, 4857.85, 3537.99,   87.75, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.49, 5,   coast,  -10.60,  55036.00, 4860.30, 3540.45,   87.64, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.50, 5,   coast,  -10.60,  55042.00, 4859.48, 3539.63,   87.54, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.50, 5,   coast,  -10.60,  55042.00, 4859.48, 3539.63,   87.54, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.51, 5,   coast,  -10.60,  55032.00, 4860.85, 3540.99,   87.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.52, 5,   coast,  -10.60,  55045.00, 4859.08, 3539.22,   87.33, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.53, 5,   coast,  -10.60,  55027.00, 4861.53, 3541.68,   87.22, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.54, 5,   coast,  -10.60,  55021.00, 4862.35, 3542.49,   87.11, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    20.56, 5,   coast,  -10.60,  55016.00, 4863.03, 3543.18,   86.90, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.57, 5,   coast,  -10.60,  55025.00, 4861.80, 3541.95,   86.80, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    20.61, 5,   coast,  -10.60,  54992.00, 4866.31, 3546.45,   86.37, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    20.63, 5,   coast,  -10.60,  54968.00, 4869.59, 3549.73,   86.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    20.71, 5,   coast,  -10.60,  54938.00, 4873.69, 3553.83,   85.31, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.72, 5,   coast,  -10.60,  54900.00, 4878.88, 3559.02,   85.21, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    20.74, 5,   coast,  -10.60,  54901.00, 4878.74, 3558.89,   84.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.75, 5,   coast,  -10.60,  54921.00, 4876.01, 3556.15,   84.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.76, 5,   coast,  -10.60,  54884.00, 4881.07, 3561.21,   84.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.77, 5,   coast,  -10.60,  54890.00, 4880.25, 3560.39,   84.68, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.78, 5,   coast,  -10.60,  54881.00, 4881.48, 3561.62,   84.57, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.79, 5,   coast,  -10.60,  54850.00, 4885.72, 3565.86,   84.46, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    20.83, 5,   coast,  -10.60,  54866.00, 4883.53, 3563.67,   84.05, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.84, 5,   coast,  -10.07,  54869.00, 4883.12, 3563.26,   83.94, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.85, 5,   coast,  -10.60,  54822.00, 4889.55, 3569.69,   83.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.86, 5,   coast,  -10.60,  54832.00, 4888.18, 3568.33,   83.73, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.87, 5,   coast,  -10.60,  54834.00, 4887.91, 3568.05,   83.63, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.88, 5,   coast,  -10.60,  54828.00, 4888.73, 3568.87,   83.52, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.89, 5,   coast,  -10.60,  54815.00, 4890.51, 3570.65,   83.41, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.90, 5,   coast,  -10.60,  54810.00, 4891.19, 3571.34,   83.31, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.91, 5,   coast,  -10.60,  54791.00, 4893.79, 3573.94,   83.20, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.92, 5,   coast,  -10.60,  54786.00, 4894.48, 3574.62,   83.10, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.93, 5,   coast,  -10.60,  54779.00, 4895.44, 3575.58,   82.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.94, 5,   coast,  -10.60,  54759.00, 4898.18, 3578.32,   82.88, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.95, 5,   coast,  -10.60,  54794.00, 4893.38, 3573.53,   82.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.96, 5,   coast,  -10.60,  54752.00, 4899.14, 3579.28,   82.67, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.97, 5,   coast,  -10.60,  54750.00, 4899.41, 3579.56,   82.57, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.98, 5,   coast,  -10.60,  54741.00, 4900.64, 3580.79,   82.46, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    20.99, 5,   coast,  -10.60,  54744.00, 4900.23, 3580.38,   82.35, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.00, 5,   coast,  -10.60,  54757.00, 4898.45, 3578.60,   82.25, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.01, 5,   coast,  -10.60,  54748.00, 4899.69, 3579.83,   82.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.02, 5,   coast,  -10.60,  54703.00, 4905.85, 3586.00,   82.04, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.03, 5,   coast,  -10.60,  54734.00, 4901.60, 3581.75,   81.93, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.04, 5,   coast,  -10.60,  54720.00, 4903.52, 3583.67,   81.82, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.05, 5,   coast,  -10.60,  54744.00, 4900.23, 3580.38,   81.72, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.06, 5,   coast,  -10.60,  54720.00, 4903.52, 3583.67,   81.61, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.07, 5,   coast,  -10.60,  54709.00, 4905.03, 3585.18,   81.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.08, 5,   coast,  -10.60,  54704.00, 4905.72, 3585.86,   81.40, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.09, 5,   coast,  -10.60,  54694.00, 4907.09, 3587.23,   81.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.10, 5,   coast,  -10.60,  54689.00, 4907.77, 3587.92,   81.19, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.11, 5,   coast,  -10.60,  54683.00, 4908.60, 3588.74,   81.08, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.12, 5,   coast,  -10.60,  54665.00, 4911.07, 3591.21,   80.98, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.13, 5,   coast,  -10.60,  54638.00, 4914.77, 3594.92,   80.87, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.14, 5,   coast,  -10.60,  54657.00, 4912.16, 3592.31,   80.76, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.14, 5,   coast,  -10.60,  54657.00, 4912.16, 3592.31,   80.76, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.15, 5,   coast,  -10.60,  54661.00, 4911.61, 3591.76,   80.66, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.16, 5,   coast,  -10.60,  54635.00, 4915.18, 3595.33,   80.55, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.17, 5,   coast,  -10.60,  54647.00, 4913.54, 3593.68,   80.45, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.18, 5,   coast,  -10.07,  54631.00, 4915.73, 3595.88,   80.34, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.19, 5,   coast,  -10.60,  54636.00, 4915.05, 3595.19,   80.24, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.20, 5,   coast,  -10.60,  54630.00, 4915.87, 3596.01,   80.13, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.21, 5,   coast,  -10.60,  54610.00, 4918.62, 3598.76,   80.03, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.22, 5,   coast,  -10.60,  54620.00, 4917.24, 3597.39,   79.92, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.23, 5,   coast,  -10.60,  54629.00, 4916.01, 3596.15,   79.82, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.24, 5,   coast,  -10.60,  54609.00, 4918.75, 3598.90,   79.71, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.25, 5,   coast,  -10.60,  54601.00, 4919.85, 3600.00,   79.60, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.26, 5,   coast,  -10.60,  54607.00, 4919.03, 3599.17,   79.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.27, 5,   coast,  -10.60,  54579.00, 4922.87, 3603.02,   79.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.28, 5,   coast,  -10.60,  54575.00, 4923.42, 3603.57,   79.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.29, 5,   coast,  -10.60,  54586.00, 4921.91, 3602.06,   79.18, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.30, 5,   coast,  -10.60,  54554.00, 4926.31, 3606.45,   79.07, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.31, 5,   coast,  -10.60,  54583.00, 4922.32, 3602.47,   78.97, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.32, 5,   coast,  -10.07,  54551.00, 4926.72, 3606.86,   78.87, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.33, 5,   coast,  -10.60,  54542.00, 4927.96, 3608.10,   78.76, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.34, 5,   coast,  -10.07,  54533.00, 4929.19, 3609.34,   78.66, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.35, 5,   coast,  -10.07,  54538.00, 4928.51, 3608.65,   78.55, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.36, 5,   coast,  -10.60,  54540.00, 4928.23, 3608.38,   78.45, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.37, 5,   coast,  -10.60,  54520.00, 4930.98, 3611.13,   78.35, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.38, 5,   coast,  -10.60,  54514.00, 4931.81, 3611.95,   78.24, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.39, 5,   coast,  -10.07,  54525.00, 4930.29, 3610.44,   78.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.40, 5,   coast,  -10.60,  54529.00, 4929.74, 3609.89,   78.03, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.41, 5,   coast,  -10.60,  54517.00, 4931.39, 3611.54,   77.93, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.42, 5,   coast,  -10.60,  54501.00, 4933.59, 3613.74,   77.82, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.43, 5,   coast,  -10.60,  54497.00, 4934.14, 3614.29,   77.72, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.44, 5,   coast,  -10.60,  54496.00, 4934.28, 3614.43,   77.61, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9414004,-106.9150165,  5106.0, 2022,  6, 24, 15, 17, 37,      394,     3737, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 23,  0,  0,  0,  0, 31, 23, 30, 31,  0,  0, 23,  0, 22, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    21.45, 5,   coast,  -10.07,  54488.00, 4935.38, 3615.53,   77.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.45, 5,   coast,  -10.07,  54488.00, 4935.38, 3615.53,   77.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.45, 5,   coast,  -10.07,  54488.00, 4935.38, 3615.53,   77.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.45, 5,   coast,  -10.07,  54488.00, 4935.38, 3615.53,   77.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.45, 5,   coast,  -10.07,  54488.00, 4935.38, 3615.53,   77.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.45, 5,   coast,  -10.07,  54488.00, 4935.38, 3615.53,   77.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.46, 5,   coast,  -10.07,  54481.00, 4936.35, 3616.49,   77.41, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.46, 5,   coast,  -10.07,  54481.00, 4936.35, 3616.49,   77.41, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.47, 5,   coast,  -10.07,  54458.00, 4939.51, 3619.65,   77.31, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.48, 5,   coast,  -10.07,  54486.00, 4935.66, 3615.80,   77.20, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.49, 5,   coast,  -10.07,  54487.00, 4935.52, 3615.66,   77.10, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.50, 5,   coast,  -10.60,  54461.00, 4939.10, 3619.24,   77.00, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.51, 5,   coast,  -10.07,  54464.00, 4938.68, 3618.83,   76.90, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.52, 5,   coast,  -10.07,  54464.00, 4938.68, 3618.83,   76.80, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.53, 5,   coast,  -10.60,  54444.00, 4941.44, 3621.58,   76.69, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.54, 5,   coast,  -10.07,  54435.00, 4942.68, 3622.82,   76.59, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.55, 5,   coast,  -10.60,  54432.00, 4943.09, 3623.23,   76.49, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.56, 5,   coast,  -10.60,  54421.00, 4944.60, 3624.75,   76.38, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.57, 5,   coast,  -10.07,  54436.00, 4942.54, 3622.68,   76.28, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.58, 5,   coast,  -10.07,  54408.00, 4946.39, 3626.54,   76.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.59, 5,   coast,  -10.07,  54417.00, 4945.15, 3625.30,   76.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.60, 5,   coast,  -10.60,  54411.00, 4945.98, 3626.13,   75.97, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.61, 5,   coast,  -10.60,  54400.00, 4947.50, 3627.64,   75.87, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.62, 5,   coast,  -10.60,  54398.00, 4947.77, 3627.92,   75.76, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.63, 5,   coast,  -10.60,  54399.00, 4947.63, 3627.78,   75.66, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.64, 5,   coast,  -10.07,  54388.00, 4949.15, 3629.29,   75.55, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.65, 5,   coast,  -10.07,  54367.00, 4952.04, 3632.19,   75.45, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.66, 5,   coast,  -10.07,  54380.00, 4950.25, 3630.40,   75.35, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.67, 5,   coast,  -10.60,  54379.00, 4950.39, 3630.53,   75.25, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.68, 5,   coast,  -10.07,  54373.00, 4951.22, 3631.36,   75.14, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.69, 5,   coast,  -10.60,  54371.00, 4951.49, 3631.64,   75.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.70, 5,   coast,  -10.60,  54355.00, 4953.70, 3633.84,   74.94, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.71, 5,   coast,  -10.07,  54364.00, 4952.46, 3632.60,   74.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.72, 5,   coast,  -10.07,  54350.00, 4954.39, 3634.53,   74.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.73, 5,   coast,  -10.07,  54324.00, 4957.97, 3638.11,   74.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.74, 5,   coast,  -10.07,  54348.00, 4954.66, 3634.81,   74.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.75, 5,   coast,  -10.60,  54342.00, 4955.49, 3635.63,   74.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.76, 5,   coast,  -10.07,  54335.00, 4956.45, 3636.60,   74.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.77, 5,   coast,  -10.07,  54326.00, 4957.69, 3637.84,   74.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.78, 5,   coast,  -10.07,  54309.00, 4960.04, 3640.18,   74.12, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.78, 5,   coast,  -10.07,  54309.00, 4960.04, 3640.18,   74.12, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.79, 5,   coast,  -10.07,  54304.00, 4960.73, 3640.87,   74.02, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.80, 5,   coast,  -10.60,  54298.00, 4961.56, 3641.70,   73.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.81, 5,   coast,  -10.60,  54304.00, 4960.73, 3640.87,   73.81, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    21.83, 5,   coast,  -10.07,  54298.00, 4961.56, 3641.70,   73.61, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.84, 5,   coast,  -10.07,  54283.00, 4963.63, 3643.77,   73.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.85, 5,   coast,  -10.07,  54275.00, 4964.73, 3644.87,   73.40, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.86, 5,   coast,  -10.60,  54275.00, 4964.73, 3644.87,   73.30, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.87, 5,   coast,  -10.07,  54271.00, 4965.28, 3645.43,   73.20, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.88, 5,   coast,  -10.07,  54260.00, 4966.80, 3646.94,   73.10, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.89, 5,   coast,  -10.07,  54246.00, 4968.73, 3648.88,   73.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.90, 5,   coast,  -10.07,  54255.00, 4967.49, 3647.63,   72.90, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.91, 5,   coast,  -10.07,  54268.00, 4965.70, 3645.84,   72.79, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.92, 5,   coast,  -10.07,  54231.00, 4970.80, 3650.95,   72.69, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.93, 5,   coast,  -10.07,  54254.00, 4967.63, 3647.77,   72.59, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.94, 5,   coast,  -10.07,  54241.00, 4969.42, 3649.57,   72.49, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.95, 5,   coast,  -10.07,  54217.00, 4972.74, 3652.88,   72.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.96, 5,   coast,  -10.07,  54199.00, 4975.22, 3655.37,   72.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.97, 5,   coast,  -10.07,  54216.00, 4972.88, 3653.02,   72.19, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.98, 5,   coast,  -10.07,  54218.00, 4972.60, 3652.74,   72.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    21.99, 5,   coast,  -10.07,  54199.00, 4975.22, 3655.37,   71.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.00, 5,   coast,  -10.07,  54195.00, 4975.78, 3655.92,   71.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.01, 5,   coast,  -10.07,  54199.00, 4975.22, 3655.37,   71.79, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.02, 5,   coast,  -10.07,  54198.00, 4975.36, 3655.51,   71.69, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.03, 5,   coast,  -10.07,  54205.00, 4974.39, 3654.54,   71.59, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.04, 5,   coast,  -10.07,  54185.00, 4977.16, 3657.30,   71.49, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.05, 5,   coast,  -10.07,  54178.00, 4978.13, 3658.27,   71.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.06, 5,   coast,  -10.07,  54166.00, 4979.78, 3659.93,   71.28, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.07, 5,   coast,  -10.07,  54150.00, 4982.00, 3662.14,   71.18, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.08, 5,   coast,  -10.07,  54176.00, 4978.40, 3658.55,   71.08, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.09, 5,   coast,  -10.07,  54157.00, 4981.03, 3661.17,   70.98, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.10, 5,   coast,  -10.07,  54132.00, 4984.48, 3664.63,   70.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.10, 5,   coast,  -10.07,  54132.00, 4984.48, 3664.63,   70.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.11, 5,   coast,  -10.07,  54147.00, 4982.41, 3662.55,   70.78, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.12, 5,   coast,  -10.07,  54145.00, 4982.69, 3662.83,   70.68, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.13, 5,   coast,  -10.07,  54129.00, 4984.90, 3665.04,   70.58, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.14, 5,   coast,  -10.07,  54125.00, 4985.45, 3665.60,   70.48, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.15, 5,   coast,  -10.07,  54123.00, 4985.73, 3665.87,   70.38, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.16, 5,   coast,  -10.07,  54123.00, 4985.73, 3665.87,   70.28, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.17, 5,   coast,  -10.07,  54119.00, 4986.28, 3666.43,   70.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.18, 5,   coast,  -10.07,  54129.00, 4984.90, 3665.04,   70.07, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.19, 5,   coast,  -10.60,  54097.00, 4989.33, 3669.47,   69.97, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.20, 5,   coast,  -10.07,  54115.00, 4986.84, 3666.98,   69.87, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.21, 5,   coast,  -10.07,  54093.00, 4989.88, 3670.02,   69.77, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.22, 5,   coast,  -10.07,  54089.00, 4990.43, 3670.58,   69.67, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.23, 5,   coast,  -10.07,  54103.00, 4988.50, 3668.64,   69.57, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.24, 5,   coast,  -10.07,  54112.00, 4987.25, 3667.40,   69.47, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.25, 5,   coast,  -10.07,  54081.00, 4991.54, 3671.68,   69.36, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.26, 5,   coast,  -10.07,  54069.00, 4993.20, 3673.35,   69.26, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.27, 5,   coast,  -10.07,  54077.00, 4992.09, 3672.24,   69.16, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.28, 5,   coast,  -10.07,  54069.00, 4993.20, 3673.35,   69.06, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.29, 5,   coast,  -10.07,  54068.00, 4993.34, 3673.48,   68.96, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.30, 5,   coast,  -10.07,  54042.00, 4996.94, 3677.08,   68.86, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.31, 5,   coast,  -10.07,  54069.00, 4993.20, 3673.35,   68.76, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.32, 5,   coast,  -10.07,  54052.00, 4995.55, 3675.70,   68.66, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.33, 5,   coast,  -10.07,  54052.00, 4995.55, 3675.70,   68.56, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.34, 5,   coast,  -10.07,  54044.00, 4996.66, 3676.81,   68.46, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.35, 5,   coast,  -10.07,  54051.00, 4995.69, 3675.84,   68.36, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.36, 5,   coast,  -10.07,  54023.00, 4999.57, 3679.72,   68.26, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.37, 5,   coast,  -10.07,  53999.00, 5002.90, 3683.04,   68.16, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.38, 5,   coast,  -10.07,  54025.00, 4999.29, 3679.44,   68.06, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.39, 5,   coast,  -10.07,  54019.00, 5000.13, 3680.27,   67.95, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.40, 5,   coast,  -10.07,  54010.00, 5001.37, 3681.52,   67.85, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.41, 5,   coast,  -10.07,  54022.00, 4999.71, 3679.85,   67.75, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.42, 5,   coast,  -10.07,  54007.00, 5001.79, 3681.93,   67.65, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.42, 5,   coast,  -10.07,  54007.00, 5001.79, 3681.93,   67.65, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.43, 5,   coast,  -10.07,  54007.00, 5001.79, 3681.93,   67.55, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.44, 5,   coast,  -10.07,  53993.00, 5003.73, 3683.87,   67.45, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.45, 5,   coast,  -10.07,  53978.00, 5005.81, 3685.95,   67.35, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.45, 5,   coast,  -10.07,  53978.00, 5005.81, 3685.95,   67.35, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    22.45, 5,   coast,  -10.07,  53978.00, 5005.81, 3685.95,   67.35, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9415047,-106.9151926,  5194.0, 2022,  6, 24, 15, 17, 38,      414,     3826, 302,  84,   1.4,2147483647.0,2147483647.0,  0, 27, 28,  0,  0, 21,  0,  0,  0,  0, 30, 31, 31, 22,  0,  0, 29,  0, 26, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    22.63, 5,   coast,  -10.07,  53920.00, 5013.85, 3693.99,   65.54, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    22.64, 5,   coast,  -10.07,  53890.00, 5018.01, 3698.16,   65.44, 34.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    22.96, 5,   coast,  -10.07,  53753.00, 5037.05, 3717.19,   62.21, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    22.97, 5,   coast,  -10.07,  53773.00, 5034.27, 3714.41,   62.11, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    23.00, 5,   coast,  -10.07,  53752.00, 5037.19, 3717.33,   61.81, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    23.06, 5,   coast,  -10.07,  53738.00, 5039.13, 3719.28,   61.20, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    23.10, 5,   coast,  -10.07,  53701.00, 5044.28, 3724.43,   60.80, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.11, 5,   coast,  -10.07,  53725.00, 5040.94, 3721.09,   60.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.12, 5,   coast,  -10.07,  53687.00, 5046.23, 3726.38,   60.60, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.13, 5,   coast,  -10.07,  53690.00, 5045.81, 3725.96,   60.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.14, 5,   coast,  -10.07,  53692.00, 5045.54, 3725.68,   60.40, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.15, 5,   coast,  -10.07,  53691.00, 5045.67, 3725.82,   60.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.16, 5,   coast,  -10.07,  53687.00, 5046.23, 3726.38,   60.19, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.17, 5,   coast,  -10.07,  53670.00, 5048.60, 3728.74,   60.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.18, 5,   coast,  -10.07,  53650.00, 5051.38, 3731.53,   59.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.19, 5,   coast,  -10.07,  53656.00, 5050.55, 3730.69,   59.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.20, 5,   coast,  -10.07,  53675.00, 5047.90, 3728.05,   59.79, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.21, 5,   coast,  -10.07,  53631.00, 5054.03, 3734.18,   59.69, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.22, 5,   coast,  -10.07,  53670.00, 5048.60, 3728.74,   59.59, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.23, 5,   coast,  -10.07,  53649.00, 5051.52, 3731.67,   59.49, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.24, 5,   coast,  -10.07,  53642.00, 5052.50, 3732.64,   59.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.25, 5,   coast,  -10.07,  53637.00, 5053.20, 3733.34,   59.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.26, 5,   coast,  -10.07,  53654.00, 5050.83, 3730.97,   59.19, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.27, 5,   coast,  -10.07,  53619.00, 5055.70, 3735.85,   59.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.28, 5,   coast,  -10.07,  53644.00, 5052.22, 3732.36,   58.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.29, 5,   coast,  -10.07,  53630.00, 5054.17, 3734.31,   58.88, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.30, 5,   coast,  -10.07,  53633.00, 5053.75, 3733.90,   58.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.31, 5,   coast,  -10.07,  53622.00, 5055.29, 3735.43,   58.68, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.32, 5,   coast,  -10.07,  53606.00, 5057.52, 3737.66,   58.58, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.33, 5,   coast,  -10.07,  53612.00, 5056.68, 3736.82,   58.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.34, 5,   coast,  -10.07,  53608.00, 5057.24, 3737.38,   58.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.35, 5,   coast,  -10.07,  53611.00, 5056.82, 3736.96,   58.28, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.36, 5,   coast,  -10.07,  53578.00, 5061.42, 3741.56,   58.18, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.37, 5,   coast,  -10.07,  53596.00, 5058.91, 3739.05,   58.08, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.38, 5,   coast,  -10.07,  53601.00, 5058.21, 3738.36,   57.98, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.38, 5,   coast,  -10.07,  53601.00, 5058.21, 3738.36,   57.98, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.39, 5,   coast,  -10.07,  53576.00, 5061.70, 3741.84,   57.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.40, 5,   coast,  -10.07,  53579.00, 5061.28, 3741.42,   57.78, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    23.41, 5,   coast,  -10.07,  53596.00, 5058.91, 3739.05,   57.68, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9416067,-106.9153625,  5271.0, 2022,  6, 24, 15, 17, 39,      433,     3905, 303,  84,   1.4,2147483647.0,2147483647.0,  0, 25, 28,  0,  0, 29,  0,  0,  0,  0, 29, 31, 20, 31,  0,  0, 31,  0, 31, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    24.05, 5,   coast,  -10.07,  53335.00, 5095.37, 3775.51,   51.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.06, 5,   coast,  -10.07,  53328.00, 5096.35, 3776.49,   51.13, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    24.08, 5,   coast,  -10.07,  53342.00, 5094.39, 3774.53,   50.93, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.09, 5,   coast,  -10.07,  53332.00, 5095.79, 3775.93,   50.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.10, 5,   coast,  -10.07,  53329.00, 5096.21, 3776.35,   50.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.11, 5,   coast,  -10.07,  53320.00, 5097.47, 3777.61,   50.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.12, 5,   coast,  -10.07,  53325.00, 5096.77, 3776.91,   50.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.13, 5,   coast,  -10.07,  53285.00, 5102.37, 3782.51,   50.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.14, 5,   coast,  -10.07,  53314.00, 5098.31, 3778.45,   50.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.15, 5,   coast,  -10.07,  53337.00, 5095.09, 3775.23,   50.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.16, 5,   coast,  -10.07,  53301.00, 5100.13, 3780.27,   50.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.17, 5,   coast,  -10.07,  53298.00, 5100.55, 3780.69,   50.02, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.18, 5,   coast,  -10.07,  53313.00, 5098.45, 3778.59,   49.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.19, 5,   coast,  -10.07,  53300.00, 5100.27, 3780.41,   49.82, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.20, 5,   coast,  -10.07,  53307.00, 5099.29, 3779.43,   49.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.21, 5,   coast,  -10.07,  53294.00, 5101.11, 3781.25,   49.62, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.22, 5,   coast,  -10.07,  53294.00, 5101.11, 3781.25,   49.52, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.23, 5,   coast,  -10.07,  53294.00, 5101.11, 3781.25,   49.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.24, 5,   coast,  -10.07,  53286.00, 5102.23, 3782.37,   49.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.25, 5,   coast,  -10.07,  53278.00, 5103.35, 3783.49,   49.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.26, 5,   coast,  -10.07,  53304.00, 5099.71, 3779.85,   49.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.27, 5,   coast,  -10.07,  53285.00, 5102.37, 3782.51,   49.01, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.28, 5,   coast,  -10.07,  53279.00, 5103.21, 3783.35,   48.91, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.29, 5,   coast,  -10.07,  53257.00, 5106.29, 3786.44,   48.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.30, 5,   coast,  -10.07,  53260.00, 5105.87, 3786.02,   48.71, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.31, 5,   coast,  -10.07,  53265.00, 5105.17, 3785.32,   48.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.32, 5,   coast,  -10.07,  53261.00, 5105.73, 3785.88,   48.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.33, 5,   coast,  -10.07,  53262.00, 5105.59, 3785.74,   48.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.34, 5,   coast,  -10.07,  53256.00, 5106.43, 3786.58,   48.31, 34.1, 0.01, 0.00, 3.86, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.34, 5,   coast,  -10.07,  53256.00, 5106.43, 3786.58,   48.31, 34.1, 0.01, 0.00, 3.86, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    24.35, 5,   coast,  -10.07,  53246.00, 5107.83, 3787.98,   48.21, 34.1, 0.01, 0.00, 3.86, 1, 1, 10,  32.9417030,-106.9155360,  5337.0, 2022,  6, 24, 15, 17, 40,      453,     3973, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 27, 29,  0,  0, 30,  0,  0,  0,  0, 28, 28, 28, 30,  0,  0, 30,  0, 22, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    24.99, 5,   coast,  -10.07,  53062.00, 5133.66, 3813.80,   41.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.00, 5,   coast,  -10.07,  53041.00, 5136.61, 3816.75,   41.71, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.01, 5,   coast,  -10.07,  53020.00, 5139.56, 3819.71,   41.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.02, 5,   coast,  -10.07,  53045.00, 5136.05, 3816.19,   41.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.03, 5,   coast,  -10.07,  53033.00, 5137.73, 3817.88,   41.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.04, 5,   coast,  -10.07,  53045.00, 5136.05, 3816.19,   41.31, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.05, 5,   coast,  -10.07,  53045.00, 5136.05, 3816.19,   41.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.06, 5,   coast,  -10.07,  53039.00, 5136.89, 3817.04,   41.11, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.07, 5,   coast,  -10.07,  53010.00, 5140.97, 3821.11,   41.01, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.08, 5,   coast,  -10.07,  53019.00, 5139.70, 3819.85,   40.91, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.09, 5,   coast,  -10.07,  53027.00, 5138.58, 3818.72,   40.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.10, 5,   coast,   -9.54,  53023.00, 5139.14, 3819.29,   40.71, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.11, 5,   coast,  -10.07,  53022.00, 5139.28, 3819.43,   40.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.12, 5,   coast,  -10.07,  53011.00, 5140.83, 3820.97,   40.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.13, 5,   coast,  -10.07,  53004.00, 5141.81, 3821.96,   40.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.14, 5,   coast,  -10.07,  52994.00, 5143.22, 3823.36,   40.31, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.15, 5,   coast,  -10.07,  53014.00, 5140.41, 3820.55,   40.20, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.16, 5,   coast,  -10.07,  53005.00, 5141.67, 3821.82,   40.10, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.17, 5,   coast,  -10.07,  53004.00, 5141.81, 3821.96,   40.01, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.18, 5,   coast,   -9.54,  52998.00, 5142.66, 3822.80,   39.91, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.19, 5,   coast,  -10.07,  52992.00, 5143.50, 3823.65,   39.81, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.20, 5,   coast,   -9.54,  52993.00, 5143.36, 3823.51,   39.71, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.21, 5,   coast,  -10.07,  53006.00, 5141.53, 3821.68,   39.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.22, 5,   coast,  -10.07,  52985.00, 5144.49, 3824.63,   39.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.23, 5,   coast,   -9.54,  52995.00, 5143.08, 3823.22,   39.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.24, 5,   coast,  -10.07,  52993.00, 5143.36, 3823.51,   39.31, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.25, 5,   coast,  -10.07,  52988.00, 5144.06, 3824.21,   39.21, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.26, 5,   coast,   -9.54,  52979.00, 5145.33, 3825.48,   39.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.27, 5,   coast,  -10.07,  52962.00, 5147.72, 3827.87,   39.02, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.28, 5,   coast,  -10.07,  52981.00, 5145.05, 3825.19,   38.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.29, 5,   coast,  -10.07,  52978.00, 5145.47, 3825.62,   38.82, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.30, 5,   coast,  -10.07,  52959.00, 5148.15, 3828.29,   38.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.30, 5,   coast,  -10.07,  52959.00, 5148.15, 3828.29,   38.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.31, 5,   coast,   -9.54,  52991.00, 5143.64, 3823.79,   38.62, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.32, 5,   coast,   -9.54,  52947.00, 5149.84, 3829.98,   38.52, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.33, 5,   coast,  -10.07,  52979.00, 5145.33, 3825.48,   38.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.34, 5,   coast,  -10.07,  52953.00, 5148.99, 3829.13,   38.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.35, 5,   coast,  -10.07,  52948.00, 5149.69, 3829.84,   38.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.36, 5,   coast,   -9.54,  52947.00, 5149.84, 3829.98,   38.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.37, 5,   coast,  -10.07,  52949.00, 5149.55, 3829.70,   38.02, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.38, 5,   coast,  -10.07,  52961.00, 5147.86, 3828.01,   37.92, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.39, 5,   coast,  -10.07,  52935.00, 5151.53, 3831.67,   37.82, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.40, 5,   coast,  -10.07,  52953.00, 5148.99, 3829.13,   37.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.41, 5,   coast,  -10.07,  52948.00, 5149.69, 3829.84,   37.62, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.42, 5,   coast,  -10.07,  52939.00, 5150.96, 3831.11,   37.52, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.43, 5,   coast,  -10.07,  52946.00, 5149.98, 3830.12,   37.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.44, 5,   coast,   -9.54,  52937.00, 5151.24, 3831.39,   37.33, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9417993,-106.9157084,  5393.0, 2022,  6, 24, 15, 17, 41,      472,     4031, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 29,  0,  0,  0,  0, 30, 27, 29, 31,  0,  0, 30,  0, 30, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.45, 5,   coast,   -9.54,  52928.00, 5152.51, 3832.66,   37.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.45, 5,   coast,   -9.54,  52928.00, 5152.51, 3832.66,   37.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.45, 5,   coast,   -9.54,  52928.00, 5152.51, 3832.66,   37.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.45, 5,   coast,   -9.54,  52928.00, 5152.51, 3832.66,   37.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.45, 5,   coast,   -9.54,  52928.00, 5152.51, 3832.66,   37.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.45, 5,   coast,   -9.54,  52928.00, 5152.51, 3832.66,   37.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.46, 5,   coast,  -10.07,  52918.00, 5153.92, 3834.06,   37.13, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.47, 5,   coast,  -10.07,  52942.00, 5150.54, 3830.68,   37.03, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.48, 5,   coast,  -10.07,  52934.00, 5151.67, 3831.81,   36.93, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.49, 5,   coast,  -10.07,  52940.00, 5150.82, 3830.97,   36.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.50, 5,   coast,  -10.07,  52936.00, 5151.38, 3831.53,   36.73, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.51, 5,   coast,  -10.07,  52919.00, 5153.78, 3833.92,   36.63, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.52, 5,   coast,   -9.54,  52926.00, 5152.79, 3832.94,   36.53, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.53, 5,   coast,   -9.54,  52909.00, 5155.19, 3835.33,   36.43, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.54, 5,   coast,  -10.07,  52916.00, 5154.20, 3834.35,   36.33, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.55, 5,   coast,  -10.07,  52917.00, 5154.06, 3834.20,   36.24, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.56, 5,   coast,   -9.54,  52929.00, 5152.37, 3832.51,   36.14, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.57, 5,   coast,   -9.54,  52912.00, 5154.76, 3834.91,   36.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.58, 5,   coast,  -10.07,  52901.00, 5156.31, 3836.46,   35.94, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    25.77, 5,   coast,   -9.54,  52846.00, 5164.07, 3844.21,   34.08, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.78, 5,   coast,   -9.54,  52879.00, 5159.41, 3839.56,   33.98, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.79, 5,   coast,   -9.54,  52859.00, 5162.23, 3842.38,   33.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.80, 5,   coast,   -9.54,  52875.00, 5159.98, 3840.12,   33.79, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    25.94, 5,   coast,   -9.54,  52845.00, 5164.21, 3844.35,   32.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.94, 5,   coast,   -9.54,  52845.00, 5164.21, 3844.35,   32.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.95, 5,   coast,  -10.07,  52829.00, 5166.46, 3846.61,   32.33, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.96, 5,   coast,   -9.54,  52825.00, 5167.03, 3847.17,   32.24, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.97, 5,   coast,   -9.54,  52809.00, 5169.29, 3849.43,   32.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.98, 5,   coast,   -9.54,  52834.00, 5165.76, 3845.90,   32.04, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    25.99, 5,   coast,   -9.54,  52806.00, 5169.71, 3849.85,   31.95, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.00, 5,   coast,  -10.07,  52817.00, 5168.16, 3848.30,   31.85, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.01, 5,   coast,  -10.07,  52831.00, 5166.18, 3846.33,   31.75, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.02, 5,   coast,   -9.54,  52818.00, 5168.02, 3848.16,   31.65, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.03, 5,   coast,  -10.07,  52803.00, 5170.13, 3850.28,   31.55, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.04, 5,   coast,   -9.54,  52809.00, 5169.29, 3849.43,   31.46, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.05, 5,   coast,   -9.54,  52798.00, 5170.84, 3850.98,   31.36, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.06, 5,   coast,  -10.07,  52804.00, 5169.99, 3850.14,   31.26, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.07, 5,   coast,  -10.07,  52807.00, 5169.57, 3849.71,   31.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.08, 5,   coast,   -9.54,  52802.00, 5170.27, 3850.42,   31.07, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.09, 5,   coast,   -9.54,  52808.00, 5169.43, 3849.57,   30.97, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.10, 5,   coast,   -9.54,  52790.00, 5171.97, 3852.11,   30.87, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.11, 5,   coast,   -9.54,  52777.00, 5173.80, 3853.95,   30.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.12, 5,   coast,   -9.54,  52778.00, 5173.66, 3853.80,   30.68, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.13, 5,   coast,  -10.07,  52783.00, 5172.95, 3853.10,   30.58, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.14, 5,   coast,   -9.54,  52770.00, 5174.79, 3854.93,   30.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.15, 5,   coast,  -10.07,  52780.00, 5173.38, 3853.52,   30.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.16, 5,   coast,  -10.07,  52785.00, 5172.67, 3852.82,   30.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.17, 5,   coast,   -9.54,  52775.00, 5174.08, 3854.23,   30.19, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.18, 5,   coast,   -9.54,  52784.00, 5172.81, 3852.96,   30.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.19, 5,   coast,   -9.54,  52786.00, 5172.53, 3852.68,   30.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.20, 5,   coast,   -9.54,  52769.00, 5174.93, 3855.08,   29.90, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.21, 5,   coast,  -10.07,  52782.00, 5173.10, 3853.24,   29.80, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.22, 5,   coast,  -10.07,  52773.00, 5174.37, 3854.51,   29.71, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.23, 5,   coast,   -9.54,  52768.00, 5175.07, 3855.22,   29.61, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.24, 5,   coast,   -9.54,  52777.00, 5173.80, 3853.95,   29.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    26.26, 5,   coast,   -9.54,  52760.00, 5176.20, 3856.35,   29.32, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.26, 5,   coast,   -9.54,  52760.00, 5176.20, 3856.35,   29.32, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.27, 5,   coast,   -9.54,  52749.00, 5177.76, 3857.90,   29.22, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.28, 5,   coast,  -10.07,  52756.00, 5176.77, 3856.91,   29.13, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    26.30, 5,   coast,   -9.54,  52755.00, 5176.91, 3857.05,   28.93, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.31, 5,   coast,   -9.54,  52732.00, 5180.16, 3860.30,   28.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    26.34, 5,   coast,  -10.07,  52754.00, 5177.05, 3857.19,   28.55, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    26.36, 5,   coast,   -9.54,  52744.00, 5178.46, 3858.61,   28.36, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    26.38, 5,   coast,   -9.54,  52747.00, 5178.04, 3858.18,   28.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.39, 5,   coast,   -9.54,  52728.00, 5180.72, 3860.87,   28.07, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.40, 5,   coast,  -10.07,  52739.00, 5179.17, 3859.31,   27.97, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    26.42, 5,   coast,   -9.54,  52731.00, 5180.30, 3860.44,   27.77, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.43, 5,   coast,   -9.54,  52741.00, 5178.89, 3859.03,   27.68, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.44, 5,   coast,   -9.54,  52729.00, 5180.58, 3860.72,   27.58, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9418966,-106.9158807,  5439.0, 2022,  6, 24, 15, 17, 42,      492,     4079, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 27,  0,  0, 28,  0,  0,  0,  0, 32, 28, 29, 31,  0,  0, 30,  0, 29, 27,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    26.45, 5,   coast,  -10.07,  52739.00, 5179.17, 3859.31,   27.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    26.47, 5,   coast,   -9.54,  52724.00, 5181.29, 3861.43,   27.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    26.91, 5,   coast,   -9.54,  52646.00, 5192.31, 3872.46,   23.06, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.92, 5,   coast,   -9.54,  52656.00, 5190.90, 3871.04,   22.97, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.93, 5,   coast,   -9.54,  52638.00, 5193.44, 3873.59,   22.87, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.94, 5,   coast,   -9.54,  52636.00, 5193.73, 3873.87,   22.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.95, 5,   coast,   -9.54,  52654.00, 5191.18, 3871.33,   22.68, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.96, 5,   coast,   -9.54,  52674.00, 5188.35, 3868.50,   22.59, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.97, 5,   coast,   -9.54,  52633.00, 5194.15, 3874.30,   22.49, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.98, 5,   coast,   -9.54,  52606.00, 5197.97, 3878.12,   22.40, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    26.99, 5,   coast,   -9.54,  52634.00, 5194.01, 3874.15,   22.30, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.00, 5,   coast,   -9.54,  52645.00, 5192.45, 3872.60,   22.21, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.01, 5,   coast,   -9.54,  52663.00, 5189.91, 3870.05,   22.11, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.02, 5,   coast,   -9.54,  52636.00, 5193.73, 3873.87,   22.01, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.03, 5,   coast,   -9.54,  52625.00, 5195.28, 3875.43,   21.92, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.04, 5,   coast,   -9.54,  52649.00, 5191.89, 3872.03,   21.82, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.05, 5,   coast,   -9.54,  52634.00, 5194.01, 3874.15,   21.73, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.06, 5,   coast,   -9.54,  52618.00, 5196.27, 3876.42,   21.63, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.07, 5,   coast,   -9.54,  52617.00, 5196.42, 3876.56,   21.54, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.08, 5,   coast,   -9.54,  52631.00, 5194.43, 3874.58,   21.44, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.09, 5,   coast,   -9.54,  52637.00, 5193.59, 3873.73,   21.35, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.10, 5,   coast,   -9.54,  52629.00, 5194.72, 3874.86,   21.25, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.11, 5,   coast,   -9.54,  52619.00, 5196.13, 3876.28,   21.16, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.12, 5,   coast,   -9.54,  52636.00, 5193.73, 3873.87,   21.06, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.13, 5,   coast,  -10.07,  52640.00, 5193.16, 3873.31,   20.96, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.14, 5,   coast,   -9.54,  52638.00, 5193.44, 3873.59,   20.87, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.15, 5,   coast,   -9.54,  52632.00, 5194.29, 3874.44,   20.77, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.16, 5,   coast,  -10.07,  52632.00, 5194.29, 3874.44,   20.67, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.17, 5,   coast,   -9.54,  52624.00, 5195.43, 3875.57,   20.57, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.18, 5,   coast,   -9.54,  52620.00, 5195.99, 3876.14,   20.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.19, 5,   coast,  -10.07,  52611.00, 5197.26, 3877.41,   20.38, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.20, 5,   coast,   -9.54,  52607.00, 5197.83, 3877.98,   20.28, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.21, 5,   coast,  -10.07,  52606.00, 5197.97, 3878.12,   20.18, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.22, 5,   coast,   -9.54,  52623.00, 5195.57, 3875.71,   20.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.22, 5,   coast,   -9.54,  52623.00, 5195.57, 3875.71,   20.09, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.23, 5,   coast,   -9.54,  52615.00, 5196.70, 3876.84,   19.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.24, 5,   coast,   -9.54,  52606.00, 5197.97, 3878.12,   19.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.25, 5,   coast,   -9.54,  52609.00, 5197.55, 3877.69,   19.80, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.26, 5,   coast,   -9.54,  52609.00, 5197.55, 3877.69,   19.70, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.27, 5,   coast,   -9.54,  52594.00, 5199.67, 3879.82,   19.61, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.28, 5,   coast,   -9.54,  52612.00, 5197.12, 3877.27,   19.51, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.29, 5,   coast,   -9.54,  52614.00, 5196.84, 3876.98,   19.42, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.30, 5,   coast,   -9.54,  52593.00, 5199.81, 3879.96,   19.32, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.31, 5,   coast,   -9.54,  52623.00, 5195.57, 3875.71,   19.23, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.32, 5,   coast,   -9.54,  52602.00, 5198.54, 3878.68,   19.13, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.33, 5,   coast,   -9.54,  52620.00, 5195.99, 3876.14,   19.04, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.34, 5,   coast,   -9.54,  52595.00, 5199.53, 3879.67,   18.94, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.35, 5,   coast,   -9.54,  52600.00, 5198.82, 3878.97,   18.84, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.36, 5,   coast,   -9.54,  52596.00, 5199.39, 3879.53,   18.75, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.37, 5,   coast,   -9.54,  52595.00, 5199.53, 3879.67,   18.65, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.38, 5,   coast,   -9.54,  52592.00, 5199.95, 3880.10,   18.56, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.39, 5,   coast,   -9.54,  52594.00, 5199.67, 3879.82,   18.46, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.40, 5,   coast,   -9.54,  52598.00, 5199.10, 3879.25,   18.37, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.41, 5,   coast,   -9.54,  52586.00, 5200.80, 3880.95,   18.27, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.42, 5,   coast,   -9.54,  52596.00, 5199.39, 3879.53,   18.18, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.43, 5,   coast,   -9.54,  52604.00, 5198.26, 3878.40,   18.08, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9419941,-106.9160507,  5475.0, 2022,  6, 24, 15, 17, 43,      511,     4117, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 28,  0,  0,  0,  0, 32, 27, 29, 30,  0,  0, 29,  0, 27, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.44, 5,   coast,   -9.54,  52590.00, 5200.24, 3880.38,   17.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.44, 5,   coast,   -9.54,  52590.00, 5200.24, 3880.38,   17.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.44, 5,   coast,   -9.54,  52590.00, 5200.24, 3880.38,   17.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.44, 5,   coast,   -9.54,  52590.00, 5200.24, 3880.38,   17.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.44, 5,   coast,   -9.54,  52590.00, 5200.24, 3880.38,   17.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.44, 5,   coast,   -9.54,  52590.00, 5200.24, 3880.38,   17.99, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.45, 5,   coast,   -9.54,  52597.00, 5199.25, 3879.39,   17.89, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.46, 5,   coast,   -9.54,  52595.00, 5199.53, 3879.67,   17.80, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    27.66, 5,   coast,   -9.54,  52591.00, 5200.10, 3880.24,   15.89, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    27.69, 5,   coast,   -9.54,  52543.00, 5206.89, 3887.04,   15.60, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    27.93, 5,   coast,   -9.54,  52547.00, 5206.33, 3886.47,   13.31, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.94, 5,   coast,   -9.54,  52566.00, 5203.64, 3883.78,   13.22, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    27.98, 5,   coast,   -9.54,  52533.00, 5208.31, 3888.45,   12.83, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    27.99, 5,   coast,   -9.54,  52549.00, 5206.04, 3886.19,   12.74, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.00, 5,   coast,   -9.54,  52567.00, 5203.49, 3883.64,   12.64, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.01, 5,   coast,   -9.54,  52525.00, 5209.44, 3889.59,   12.55, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.02, 5,   coast,   -9.54,  52540.00, 5207.32, 3887.46,   12.45, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.03, 5,   coast,   -9.54,  52541.00, 5207.18, 3887.32,   12.36, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.04, 5,   coast,   -9.54,  52554.00, 5205.34, 3885.48,   12.26, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    28.06, 5,   coast,   -9.54,  52515.00, 5210.86, 3891.01,   12.07, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.07, 5,   coast,   -9.54,  52547.00, 5206.33, 3886.47,   11.97, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.08, 5,   coast,  -10.07,  52536.00, 5207.89, 3888.03,   11.88, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.09, 5,   coast,   -9.54,  52520.00, 5210.15, 3890.30,   11.78, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.10, 5,   coast,   -9.54,  52550.00, 5205.90, 3886.05,   11.68, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.11, 5,   coast,   -9.54,  52551.00, 5205.76, 3885.90,   11.59, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.12, 5,   coast,   -9.54,  52546.00, 5206.47, 3886.61,   11.49, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.13, 5,   coast,  -10.07,  52540.00, 5207.32, 3887.46,   11.39, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.14, 5,   coast,   -9.54,  52540.00, 5207.32, 3887.46,   11.30, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.15, 5,   coast,   -9.54,  52518.00, 5210.44, 3890.58,   11.20, 34.2, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.16, 5,   coast,   -9.54,  52528.00, 5209.02, 3889.16,   11.11, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.17, 5,   coast,   -9.54,  52535.00, 5208.03, 3888.17,   11.01, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.18, 5,   coast,   -9.54,  52522.00, 5209.87, 3890.01,   10.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.18, 5,   coast,   -9.54,  52522.00, 5209.87, 3890.01,   10.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.19, 5,   coast,   -9.54,  52505.00, 5212.28, 3892.42,   10.82, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.20, 5,   coast,   -9.54,  52515.00, 5210.86, 3891.01,   10.72, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.21, 5,   coast,   -9.54,  52524.00, 5209.59, 3889.73,   10.63, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.22, 5,   coast,   -9.54,  52526.00, 5209.30, 3889.45,   10.53, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.23, 5,   coast,   -9.54,  52515.00, 5210.86, 3891.01,   10.44, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.24, 5,   coast,   -9.54,  52543.00, 5206.89, 3887.04,   10.34, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.25, 5,   coast,   -9.54,  52527.00, 5209.16, 3889.30,   10.25, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.26, 5,   coast,   -9.54,  52527.00, 5209.16, 3889.30,   10.15, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.27, 5,   coast,   -9.54,  52525.00, 5209.44, 3889.59,   10.06, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.28, 5,   coast,   -9.54,  52525.00, 5209.44, 3889.59,    9.96, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.29, 5,   coast,   -9.54,  52526.00, 5209.30, 3889.45,    9.86, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.30, 5,   coast,   -9.54,  52524.00, 5209.59, 3889.73,    9.77, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.31, 5,   coast,   -9.54,  52518.00, 5210.44, 3890.58,    9.67, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.32, 5,   coast,   -9.54,  52521.00, 5210.01, 3890.15,    9.58, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.33, 5,   coast,   -9.54,  52512.00, 5211.29, 3891.43,    9.48, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.34, 5,   coast,   -9.54,  52521.00, 5210.01, 3890.15,    9.39, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.35, 5,   coast,   -9.54,  52538.00, 5207.60, 3887.75,    9.29, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.36, 5,   coast,   -9.54,  52507.00, 5211.99, 3892.14,    9.20, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.37, 5,   coast,   -9.54,  52520.00, 5210.15, 3890.30,    9.10, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.38, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    9.01, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.39, 5,   coast,   -9.54,  52522.00, 5209.87, 3890.01,    8.91, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.40, 5,   coast,   -9.54,  52521.00, 5210.01, 3890.15,    8.82, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.41, 5,   coast,   -9.54,  52533.00, 5208.31, 3888.45,    8.72, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.42, 5,   coast,   -9.54,  52516.00, 5210.72, 3890.86,    8.62, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.43, 5,   coast,   -9.54,  52520.00, 5210.15, 3890.30,    8.53, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9420904,-106.9162182,  5501.0, 2022,  6, 24, 15, 17, 44,      530,     4145, 303,  83,   1.4,2147483647.0,2147483647.0,  0, 32, 24,  0,  0, 28,  0,  0,  0,  0, 31, 25, 29, 31,  0,  0, 29,  0, 26, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.44, 5,   coast,   -9.54,  52517.00, 5210.58, 3890.72,    8.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.44, 5,   coast,   -9.54,  52517.00, 5210.58, 3890.72,    8.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    28.44, 5,   coast,   -9.54,  52517.00, 5210.58, 3890.72,    8.43, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    28.45, 5,   coast,   -9.54,  52525.00, 5209.44, 3889.59,    8.34, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.46, 5,   coast,  -10.07,  52526.00, 5209.30, 3889.45,    8.24, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.47, 5,   coast,   -9.54,  52536.00, 5207.89, 3888.03,    8.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.48, 5,   coast,   -9.54,  52532.00, 5208.45, 3888.60,    8.05, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.49, 5,   coast,   -9.54,  52512.00, 5211.29, 3891.43,    7.95, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.50, 5,   coast,   -9.54,  52511.00, 5211.43, 3891.57,    7.86, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    28.51, 5,   coast,   -9.54,  52503.00, 5212.56, 3892.71,    7.76, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.52, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    7.67, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.53, 5,   coast,   -9.54,  52521.00, 5210.01, 3890.15,    7.57, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.54, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    7.47, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.55, 5,   coast,   -9.54,  52507.00, 5211.99, 3892.14,    7.38, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.56, 5,   coast,  -10.07,  52521.00, 5210.01, 3890.15,    7.28, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.57, 5,   coast,   -9.54,  52512.00, 5211.29, 3891.43,    7.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.58, 5,   coast,   -9.54,  52522.00, 5209.87, 3890.01,    7.09, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.59, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    6.99, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.60, 5,   coast,   -9.54,  52500.00, 5212.99, 3893.13,    6.90, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.61, 5,   coast,   -9.54,  52497.00, 5213.41, 3893.56,    6.80, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.62, 5,   coast,   -9.54,  52502.00, 5212.70, 3892.85,    6.71, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.63, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    6.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.64, 5,   coast,   -9.54,  52530.00, 5208.74, 3888.88,    6.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.65, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    6.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.66, 5,   coast,   -9.54,  52498.00, 5213.27, 3893.41,    6.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.67, 5,   coast,   -9.54,  52517.00, 5210.58, 3890.72,    6.23, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.68, 5,   coast,   -9.54,  52489.00, 5214.55, 3894.69,    6.13, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.69, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    6.04, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.70, 5,   coast,   -9.54,  52504.00, 5212.42, 3892.56,    5.94, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.71, 5,   coast,   -9.54,  52528.00, 5209.02, 3889.16,    5.85, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.72, 5,   coast,   -9.54,  52515.00, 5210.86, 3891.01,    5.75, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.73, 5,   coast,   -9.54,  52507.00, 5211.99, 3892.14,    5.66, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    28.75, 5,   coast,   -9.54,  52503.00, 5212.56, 3892.71,    5.47, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.76, 5,   coast,   -9.54,  52513.00, 5211.14, 3891.29,    5.37, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.77, 5,   coast,   -9.54,  52525.00, 5209.44, 3889.59,    5.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.78, 5,   coast,   -9.54,  52523.00, 5209.73, 3889.87,    5.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.79, 5,   coast,   -9.54,  52512.00, 5211.29, 3891.43,    5.08, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.80, 5,   coast,   -9.54,  52501.00, 5212.85, 3892.99,    4.99, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.81, 5,   coast,   -9.54,  52507.00, 5211.99, 3892.14,    4.89, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.82, 5,   coast,   -9.54,  52503.00, 5212.56, 3892.71,    4.80, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.82, 5,   coast,   -9.54,  52503.00, 5212.56, 3892.71,    4.80, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.83, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    4.70, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.84, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    4.61, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.85, 5,   coast,   -9.54,  52498.00, 5213.27, 3893.41,    4.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.86, 5,   coast,   -9.54,  52531.00, 5208.59, 3888.74,    4.42, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.87, 5,   coast,   -9.54,  52487.00, 5214.83, 3894.97,    4.32, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.88, 5,   coast,   -9.54,  52494.00, 5213.84, 3893.98,    4.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.89, 5,   coast,   -9.54,  52497.00, 5213.41, 3893.56,    4.13, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.90, 5,   coast,   -9.54,  52520.00, 5210.15, 3890.30,    4.03, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.91, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    3.94, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.92, 5,   coast,   -9.54,  52487.00, 5214.83, 3894.97,    3.84, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.93, 5,   coast,   -9.54,  52504.00, 5212.42, 3892.56,    3.75, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.94, 5,   coast,   -9.54,  52504.00, 5212.42, 3892.56,    3.65, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.95, 5,   coast,   -9.54,  52493.00, 5213.98, 3894.12,    3.56, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.96, 5,   coast,   -9.54,  52505.00, 5212.28, 3892.42,    3.46, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.97, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    3.37, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.98, 5,   coast,   -9.54,  52505.00, 5212.28, 3892.42,    3.27, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    28.99, 5,   coast,   -9.54,  52505.00, 5212.28, 3892.42,    3.18, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.00, 5,   coast,   -9.54,  52502.00, 5212.70, 3892.85,    3.08, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.01, 5,   coast,   -9.54,  52498.00, 5213.27, 3893.41,    2.98, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.02, 5,   coast,   -9.54,  52495.00, 5213.70, 3893.84,    2.89, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.03, 5,   coast,   -9.54,  52507.00, 5211.99, 3892.14,    2.79, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.04, 5,   coast,   -9.54,  52502.00, 5212.70, 3892.85,    2.70, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.05, 5,   coast,   -9.54,  52491.00, 5214.26, 3894.41,    2.60, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.06, 5,   coast,   -9.54,  52492.00, 5214.12, 3894.27,    2.51, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.07, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    2.41, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.08, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    2.31, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.09, 5,   coast,  -10.07,  52525.00, 5209.44, 3889.59,    2.22, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.10, 5,   coast,   -9.54,  52506.00, 5212.14, 3892.28,    2.12, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.11, 5,   coast,   -9.54,  52523.00, 5209.73, 3889.87,    2.03, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.12, 5,   coast,   -9.54,  52517.00, 5210.58, 3890.72,    1.93, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.13, 5,   coast,   -9.54,  52501.00, 5212.85, 3892.99,    1.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.14, 5,   coast,   -9.54,  52501.00, 5212.85, 3892.99,    1.74, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.14, 5,   coast,   -9.54,  52501.00, 5212.85, 3892.99,    1.74, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.15, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    1.64, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.16, 5,   coast,   -9.54,  52506.00, 5212.14, 3892.28,    1.55, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.17, 5,   coast,   -9.54,  52512.00, 5211.29, 3891.43,    1.45, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.18, 5,   coast,   -9.54,  52482.00, 5215.54, 3895.68,    1.36, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.19, 5,   coast,   -9.54,  52495.00, 5213.70, 3893.84,    1.26, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.20, 5,   coast,   -9.54,  52498.00, 5213.27, 3893.41,    1.17, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.21, 5,   coast,   -9.54,  52524.00, 5209.59, 3889.73,    1.07, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.22, 5,   coast,   -9.54,  52490.00, 5214.40, 3894.55,    0.98, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.23, 5,   coast,   -9.54,  52494.00, 5213.84, 3893.98,    0.88, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.24, 5,   coast,   -9.54,  52507.00, 5211.99, 3892.14,    0.78, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.25, 5,   coast,   -9.54,  52510.00, 5211.57, 3891.71,    0.69, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.26, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    0.59, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.27, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    0.50, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.28, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    0.40, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.29, 5,   coast,   -9.54,  52525.00, 5209.44, 3889.59,    0.31, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.30, 5,   coast,  -10.07,  52500.00, 5212.99, 3893.13,    0.22, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.31, 5,   coast,   -9.54,  52527.00, 5209.16, 3889.30,    0.14, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.32, 5,   coast,   -9.54,  52497.00, 5213.41, 3893.56,    0.08, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.33, 5,   coast,   -9.54,  52511.00, 5211.43, 3891.57,    0.04, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.34, 5,   coast,   -9.54,  52517.00, 5210.58, 3890.72,    0.01, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.35, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    0.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.36, 5,   coast,   -9.54,  52516.00, 5210.72, 3890.86,    0.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.37, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    0.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.38, 5,   coast,   -9.54,  52528.00, 5209.02, 3889.16,    0.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.39, 5,   coast,   -9.54,  52514.00, 5211.00, 3891.15,    0.00, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.40, 5,   coast,   -9.54,  52508.00, 5211.85, 3892.00,    0.00, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    29.41, 5,   coast,   -9.54,  52509.00, 5211.71, 3891.86,    0.00, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9421893,-106.9163832,  5517.0, 2022,  6, 24, 15, 17, 45,      549,     4163, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 24,  0,  0, 28,  0,  0,  0,  0, 31, 26, 30, 31,  0,  0, 27,  0, 26, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    30.34, 6,  drogue,  -19.08,  52557.00, 5204.91, 3885.05,   -5.55, 34.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9422903,-106.9165506,  5523.0, 2022,  6, 24, 15, 17, 46,      568,     4172, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 31, 25,  0,  0, 30,  0,  0,  0,  0, 32, 27, 30, 29,  0,  0, 26,  0, 25, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    32.44, 6,  drogue,  -13.25,  52769.00, 5174.93, 3855.08,  -18.38, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9424943,-106.9168879,  5511.0, 2022,  6, 24, 15, 17, 48,      607,     4165, 303,  82,   1.4,2147483647.0,2147483647.0,  0, 29, 31,  0,  0, 34,  0,  0,  0,  0, 32, 28, 26, 23,  0,  0, 32,  0, 30, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 31,  0,  0
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+6, 5115, 1,VA3NPN,    32.64, 6,  drogue,  -10.07,  52771.00, 5174.65, 3854.79,  -19.58, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    32.74, 6,  drogue,   -6.36,  52783.00, 5172.95, 3853.10,  -20.28, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    33.04, 6,  drogue,   -5.83,  52801.00, 5170.41, 3850.56,  -22.94, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    33.14, 6,  drogue,   -6.36,  52801.00, 5170.41, 3850.56,  -23.88, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    33.24, 6,  drogue,   -2.65,  52867.00, 5161.11, 3841.25,  -24.75, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    33.30, 6,  drogue,   -2.65,  52867.00, 5161.11, 3841.25,  -24.75, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    33.34, 6,  drogue,   -2.65,  52908.00, 5155.33, 3835.47,  -25.59, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9425842,-106.9169991,  5494.0, 2022,  6, 24, 15, 17, 49,      621,     4151, 303,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 32,  0,  0, 22,  0,  0,  0,  0, 28, 27, 28, 25,  0,  0, 37,  0, 33, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,    33.44, 6,  drogue,   -1.59,  52882.00, 5158.99, 3839.14,  -26.42, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
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+6, 5115, 1,VA3NPN,    33.54, 6,  drogue,    7.95,  52850.00, 5163.50, 3843.65,  -27.16, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    33.62, 6,  drogue,    7.95,  52850.00, 5163.50, 3843.65,  -27.16, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    33.64, 6,  drogue,   23.85,  52953.00, 5148.99, 3829.13,  -27.79, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    33.74, 6,  drogue,   21.73,  52979.00, 5145.33, 3825.48,  -28.38, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    33.84, 6,  drogue,   -4.77,  52947.00, 5149.84, 3829.98,  -28.89, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    33.94, 6,  drogue,  -13.25,  52998.00, 5142.66, 3822.80,  -29.32, 34.2, 0.01, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    33.94, 6,  drogue,  -13.25,  52998.00, 5142.66, 3822.80,  -29.32, 34.2, 0.01, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
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+6, 5115, 1,VA3NPN,    34.14, 6,  drogue,   -6.36,  53081.00, 5130.99, 3811.13,  -29.83, 34.2, 0.01, 0.00, 3.87, 1, 1, 10,  32.9426537,-106.9170665,  5469.0, 2022,  6, 24, 15, 17, 50,      630,     4127, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 34,  0,  0,  0,  0, 33, 27, 27, 29,  0,  0, 26,  0, 27, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
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+6, 5115, 1,VA3NPN,    34.94, 6,  drogue,  -15.90,  53276.00, 5103.63, 3783.77,  -29.09, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427219,-106.9171188,  5440.0, 2022,  6, 24, 15, 17, 51,      639,     4100, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 29,  0,  0,  0,  0, 27, 27, 26, 18,  0,  0, 30,  0, 31, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    35.04, 6,  drogue,  -14.31,  53282.00, 5102.79, 3782.93,  -28.94, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427219,-106.9171188,  5440.0, 2022,  6, 24, 15, 17, 51,      639,     4100, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 29,  0,  0,  0,  0, 27, 27, 26, 18,  0,  0, 30,  0, 31, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    35.14, 6,  drogue,  -12.72,  53248.00, 5107.55, 3787.70,  -28.82, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427219,-106.9171188,  5440.0, 2022,  6, 24, 15, 17, 51,      639,     4100, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 29,  0,  0,  0,  0, 27, 27, 26, 18,  0,  0, 30,  0, 31, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    35.22, 6,  drogue,  -12.72,  53248.00, 5107.55, 3787.70,  -28.82, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9427219,-106.9171188,  5440.0, 2022,  6, 24, 15, 17, 51,      639,     4100, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 29,  0,  0,  0,  0, 27, 27, 26, 18,  0,  0, 30,  0, 31, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    35.24, 6,  drogue,  -14.31,  53201.00, 5114.14, 3794.29,  -28.75, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9427219,-106.9171188,  5440.0, 2022,  6, 24, 15, 17, 51,      639,     4100, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 29,  0,  0,  0,  0, 27, 27, 26, 18,  0,  0, 30,  0, 31, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,    35.44, 6,  drogue,   -5.83,  53305.00, 5099.57, 3779.71,  -28.58, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    35.54, 6,  drogue,   -9.01,  53310.00, 5098.87, 3779.01,  -28.47, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    35.64, 6,  drogue,  -11.66,  53323.00, 5097.05, 3777.19,  -28.37, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    35.74, 6,  drogue,  -10.60,  53413.00, 5084.46, 3764.60,  -28.25, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    35.84, 6,  drogue,   -2.12,  53478.00, 5075.37, 3755.52,  -28.05, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    35.94, 6,  drogue,   -7.42,  53487.00, 5074.12, 3754.26,  -27.85, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.04, 6,  drogue,  -10.07,  53460.00, 5077.89, 3758.03,  -27.57, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.14, 6,  drogue,   -9.54,  53439.00, 5080.82, 3760.97,  -27.29, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.18, 6,  drogue,   -9.54,  53439.00, 5080.82, 3760.97,  -27.29, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.24, 6,  drogue,  -11.13,  53444.00, 5080.12, 3760.27,  -27.02, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.34, 6,  drogue,  -11.66,  53479.00, 5075.24, 3755.38,  -26.76, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.44, 6,  drogue,  -11.13,  53474.00, 5075.93, 3756.08,  -26.52, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    36.45, 6,  drogue,  -11.13,  53474.00, 5075.93, 3756.08,  -26.52, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9427713,-106.9171623,  5410.0, 2022,  6, 24, 15, 17, 52,      645,     4071, 304,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 30,  0,  0,  0,  0, 34, 28, 26, 28,  0,  0, 25,  0, 27, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    36.82, 6,  drogue,  -16.43,  53652.00, 5051.11, 3731.25,  -26.01, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    36.84, 6,  drogue,  -21.73,  53665.00, 5049.29, 3729.44,  -26.02, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    36.94, 6,  drogue,  -18.55,  53676.00, 5047.76, 3727.91,  -26.09, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.04, 6,  drogue,  -14.31,  53598.00, 5058.63, 3738.77,  -26.26, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.14, 6,  drogue,  -13.78,  53635.00, 5053.47, 3733.62,  -26.49, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.14, 6,  drogue,  -13.78,  53635.00, 5053.47, 3733.62,  -26.49, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.24, 6,  drogue,  -18.55,  53664.00, 5049.43, 3729.58,  -26.78, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.34, 6,  drogue,  -17.49,  53659.00, 5050.13, 3730.27,  -27.20, 34.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.44, 6,  drogue,  -10.60,  53702.00, 5044.14, 3724.29,  -27.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.45, 6,  drogue,  -10.60,  53702.00, 5044.14, 3724.29,  -27.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.45, 6,  drogue,  -10.60,  53702.00, 5044.14, 3724.29,  -27.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,    37.45, 6,  drogue,  -10.60,  53702.00, 5044.14, 3724.29,  -27.72, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9428197,-106.9171696,  5380.0, 2022,  6, 24, 15, 17, 53,      649,     4042, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 33, 26,  0,  0, 27,  0,  0,  0,  0, 32, 28, 26, 31,  0,  0, 31,  0, 26, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,    37.54, 6,  drogue,   -9.54,  53730.00, 5040.25, 3720.39,  -28.30, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9428850,-106.9171631,  5349.0, 2022,  6, 24, 15, 17, 54,      652,     4012, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 27,  0,  0, 26,  0,  0,  0,  0, 31, 29, 27, 26,  0,  0, 33,  0, 27, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,    37.64, 6,  drogue,   -8.48,  53695.00, 5045.12, 3725.26,  -28.92, 34.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9428850,-106.9171631,  5349.0, 2022,  6, 24, 15, 17, 54,      652,     4012, 305,  81,   1.4,2147483647.0,2147483647.0,  0, 29, 27,  0,  0, 26,  0,  0,  0,  0, 31, 29, 27, 26,  0,  0, 33,  0, 27, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
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+6, 5115, 1,VA3NPN,    40.34, 6,  drogue,  -16.43,  54363.00, 4952.59, 3632.74,  -28.65, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9430199,-106.9171386,  5285.0, 2022,  6, 24, 15, 17, 56,      659,     3950, 306,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 22,  0,  0, 35,  0,  0,  0,  0, 31, 27, 26, 32,  0,  0, 27,  0, 25, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
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+6, 5115, 1,VA3NPN,    40.64, 6,  drogue,  -14.84,  54371.00, 4951.49, 3631.64,  -28.94, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    40.66, 6,  drogue,  -14.84,  54371.00, 4951.49, 3631.64,  -28.94, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    40.74, 6,  drogue,  -15.37,  54409.00, 4946.26, 3626.40,  -28.93, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    40.84, 6,  drogue,  -13.25,  54370.00, 4951.63, 3631.77,  -29.12, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    40.94, 6,  drogue,  -11.13,  54509.00, 4932.49, 3612.64,  -29.23, 34.1, 0.01, 0.00, 3.87, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    40.98, 6,  drogue,  -11.13,  54509.00, 4932.49, 3612.64,  -29.23, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    41.04, 6,  drogue,   -9.01,  54526.00, 4930.16, 3610.30,  -29.34, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    41.14, 6,  drogue,  -11.66,  54513.00, 4931.94, 3612.09,  -29.44, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    41.24, 6,  drogue,  -13.25,  54515.00, 4931.67, 3611.81,  -29.54, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    41.30, 6,  drogue,  -13.25,  54515.00, 4931.67, 3611.81,  -29.54, 34.1, 0.00, 0.01, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    41.34, 6,  drogue,  -15.37,  54565.00, 4924.80, 3604.94,  -29.64, 34.1, 0.00, 0.01, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    41.44, 6,  drogue,  -16.43,  54576.00, 4923.28, 3603.43,  -29.76, 34.1, 0.00, 0.01, 3.86, 1, 1, 10,  32.9430994,-106.9171388,  5251.0, 2022,  6, 24, 15, 17, 57,      664,     3918, 307,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 23,  0,  0, 32,  0,  0,  0,  0, 24, 31, 31, 32,  0,  0, 30,  0, 32, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 27,  0,  0
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+6, 5115, 1,VA3NPN,    41.54, 6,  drogue,  -16.43,  54594.00, 4920.81, 3600.96,  -29.87, 34.1, 0.00, 0.01, 3.86, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    41.62, 6,  drogue,  -16.43,  54594.00, 4920.81, 3600.96,  -29.87, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    41.64, 6,  drogue,  -14.84,  54667.00, 4910.79, 3590.94,  -30.02, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    41.74, 6,  drogue,  -14.84,  54688.00, 4907.91, 3588.06,  -30.15, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    41.84, 6,  drogue,  -17.49,  54732.00, 4901.88, 3582.02,  -30.37, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    41.94, 6,  drogue,  -17.49,  54739.00, 4900.92, 3581.06,  -30.70, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    41.94, 6,  drogue,  -17.49,  54739.00, 4900.92, 3581.06,  -30.70, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.04, 6,  drogue,  -12.72,  54749.00, 4899.55, 3579.69,  -31.14, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.14, 6,  drogue,   -6.89,  54685.00, 4908.32, 3588.47,  -31.54, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.24, 6,  drogue,   -5.30,  54772.00, 4896.40, 3576.54,  -31.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.26, 6,  drogue,   -5.30,  54772.00, 4896.40, 3576.54,  -31.88, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.34, 6,  drogue,   -6.36,  54699.00, 4906.40, 3586.55,  -32.34, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.44, 6,  drogue,   -5.83,  54739.00, 4900.92, 3581.06,  -32.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.45, 6,  drogue,   -5.83,  54739.00, 4900.92, 3581.06,  -32.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.45, 6,  drogue,   -5.83,  54739.00, 4900.92, 3581.06,  -32.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.45, 6,  drogue,   -5.83,  54739.00, 4900.92, 3581.06,  -32.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.45, 6,  drogue,   -5.83,  54739.00, 4900.92, 3581.06,  -32.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.45, 6,  drogue,   -5.83,  54739.00, 4900.92, 3581.06,  -32.83, 34.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9431690,-106.9171327,  5218.0, 2022,  6, 24, 15, 17, 58,      669,     3886, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 27,  0,  0,  0,  0, 31, 22, 30, 26,  0,  0, 34,  0, 32, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,    42.54, 6,  drogue,   -6.36,  54784.00, 4894.75, 3574.90,  -33.35, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    42.58, 6,  drogue,   -6.36,  54784.00, 4894.75, 3574.90,  -33.35, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    42.64, 6,  drogue,   -7.95,  54776.00, 4895.85, 3575.99,  -33.95, 34.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    42.74, 6,  drogue,    9.54,  54779.00, 4895.44, 3575.58,  -34.59, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    42.84, 6,  drogue,   18.02,  55023.00, 4862.08, 3542.22,  -35.21, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    42.90, 6,  drogue,   18.02,  55023.00, 4862.08, 3542.22,  -35.21, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    42.94, 6,  drogue,    2.65,  54937.00, 4873.82, 3553.97,  -35.90, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.04, 6,  drogue,   -8.48,  54950.00, 4872.05, 3552.19,  -36.51, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.14, 6,  drogue,   -8.48,  54983.00, 4867.54, 3547.68,  -36.99, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.22, 6,  drogue,   -8.48,  54983.00, 4867.54, 3547.68,  -36.99, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.24, 6,  drogue,    6.89,  55023.00, 4862.08, 3542.22,  -37.36, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.34, 6,  drogue,    9.01,  55055.00, 4857.71, 3537.86,  -37.65, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.44, 6,  drogue,    7.42,  55088.00, 4853.21, 3533.35,  -37.81, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    43.45, 6,  drogue,    7.42,  55088.00, 4853.21, 3533.35,  -37.81, 34.0, 0.00, 0.00, 3.86, 1, 1, 10,  32.9432461,-106.9171166,  5186.0, 2022,  6, 24, 15, 17, 59,      673,     3855, 308,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 31,  0,  0, 28,  0,  0,  0,  0, 31, 30, 23, 32,  0,  0, 35,  0, 22, 20,  0,  0,  0, 26,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,    44.24, 6,  drogue,  -13.25,  55185.00, 4839.99, 3520.14,  -35.16, 34.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9433280,-106.9170992,  5154.0, 2022,  6, 24, 15, 18,  0,      677,     3824, 309,  80,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 32,  0,  0,  0,  0, 27, 24, 26, 30,  0,  0, 26,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,    44.64, 6,  drogue,  -12.72,  55467.00, 4801.68, 3481.82,  -32.78, 34.0, 0.00, 0.01, 3.86, 1, 1, 10,  32.9434010,-106.9170860,  5124.0, 2022,  6, 24, 15, 18,  1,      681,     3796, 309,  80,   1.4,2147483647.0,2147483647.0,  0, 32, 26,  0,  0, 33,  0,  0,  0,  0, 32, 26, 26, 30,  0,  0, 32,  0, 29, 24,  0,  0,  0, 32,  0,  0,  0,  0,  0, 23,  0,  0
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+6, 5115, 1,VA3NPN,    75.34, 6,  drogue,  -18.02,  62291.00, 3919.33, 2599.48,  -29.96, 33.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9459314,-106.9173876,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2956, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 24, 30,  0,  0, 24,  0,  0,  0,  0, 28, 33, 30, 30,  0,  0, 33,  0, 26, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    75.43, 6,  drogue,  -18.02,  62291.00, 3919.33, 2599.48,  -29.96, 33.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9459314,-106.9173876,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2956, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 24, 30,  0,  0, 24,  0,  0,  0,  0, 28, 33, 30, 30,  0,  0, 33,  0, 26, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
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+6, 5115, 1,VA3NPN,    75.44, 6,  drogue,  -16.96,  62278.00, 3920.94, 2601.08,  -29.94, 33.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
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+6, 5115, 1,VA3NPN,    75.64, 6,  drogue,  -16.43,  62358.00, 3911.06, 2591.21,  -29.83, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
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+6, 5115, 1,VA3NPN,    75.84, 6,  drogue,  -17.49,  62453.00, 3899.36, 2579.50,  -29.55, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    75.86, 6,  drogue,  -17.49,  62453.00, 3899.36, 2579.50,  -29.55, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    75.94, 6,  drogue,  -17.49,  62437.00, 3901.33, 2581.47,  -29.35, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    76.04, 6,  drogue,  -18.55,  62458.00, 3898.74, 2578.88,  -29.18, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    76.14, 6,  drogue,  -19.61,  62475.00, 3896.65, 2576.79,  -29.02, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    76.18, 6,  drogue,  -19.61,  62475.00, 3896.65, 2576.79,  -29.02, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    76.24, 6,  drogue,  -20.14,  62482.00, 3895.78, 2575.93,  -28.89, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    76.34, 6,  drogue,  -19.08,  62539.00, 3888.77, 2568.91,  -28.78, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460036,-106.9174029,  4173.0, 2022,  6, 24, 15, 18, 32,      911,     2928, 322,  72,   1.4,2147483647.0,2147483647.0,  0, 26, 29,  0,  0, 25,  0,  0,  0,  0, 28, 32, 30, 30,  0,  0, 35,  0, 27, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 22,  0,  0
+6, 5115, 1,VA3NPN,    76.44, 6,  drogue,  -19.61,  62539.00, 3888.77, 2568.91,  -28.67, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.44, 6,  drogue,  -19.61,  62539.00, 3888.77, 2568.91,  -28.67, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    76.50, 6,  drogue,  -19.61,  62539.00, 3888.77, 2568.91,  -28.67, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.54, 6,  drogue,  -18.55,  62578.00, 3883.97, 2564.12,  -28.56, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.64, 6,  drogue,  -17.49,  62599.00, 3881.39, 2561.53,  -28.41, 33.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.74, 6,  drogue,  -17.49,  62624.00, 3878.32, 2558.46,  -28.28, 33.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.82, 6,  drogue,  -17.49,  62624.00, 3878.32, 2558.46,  -28.28, 33.5, 0.00, 0.00, 3.87, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.84, 6,  drogue,  -19.61,  62687.00, 3870.58, 2550.72,  -28.21, 33.5, 0.00, 0.00, 3.87, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    76.94, 6,  drogue,  -21.73,  62675.00, 3872.05, 2552.19,  -28.18, 33.5, 0.00, 0.00, 3.87, 1, 1, 10,  32.9460726,-106.9174005,  4142.0, 2022,  6, 24, 15, 18, 33,      917,     2901, 323,  72,   1.4,2147483647.0,2147483647.0,  0, 35, 28,  0,  0, 30,  0,  0,  0,  0, 34, 31, 31, 23,  0,  0, 31,  0, 27, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    91.24, 6,  drogue,  -13.78,  65871.00, 3487.38, 2167.52,  -25.82, 33.2, 0.00, 0.01, 3.87, 1, 1, 10,  32.9469928,-106.9169800,  3726.0, 2022,  6, 24, 15, 18, 47,      980,     2533, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 34,  0,  0,  0,  0, 25, 35, 27, 31,  0,  0, 31,  0, 31, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    91.34, 6,  drogue,  -13.25,  65908.00, 3483.01, 2163.16,  -26.36, 33.2, 0.00, 0.01, 3.87, 1, 1, 10,  32.9469928,-106.9169800,  3726.0, 2022,  6, 24, 15, 18, 47,      980,     2533, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 34,  0,  0,  0,  0, 25, 35, 27, 31,  0,  0, 31,  0, 31, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    91.54, 6,  drogue,  -13.78,  65837.00, 3491.39, 2171.53,  -27.43, 33.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9470412,-106.9169863,  3699.0, 2022,  6, 24, 15, 18, 48,      984,     2510, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 26,  0,  0, 35,  0,  0,  0,  0, 23, 26, 27, 31,  0,  0, 32,  0, 35, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    91.64, 6,  drogue,  -10.07,  65897.00, 3484.31, 2164.46,  -27.95, 33.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9470412,-106.9169863,  3699.0, 2022,  6, 24, 15, 18, 48,      984,     2510, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 26,  0,  0, 35,  0,  0,  0,  0, 23, 26, 27, 31,  0,  0, 32,  0, 35, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    91.74, 6,  drogue,   -7.42,  65987.00, 3473.70, 2153.85,  -28.50, 33.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9470412,-106.9169863,  3699.0, 2022,  6, 24, 15, 18, 48,      984,     2510, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 26,  0,  0, 35,  0,  0,  0,  0, 23, 26, 27, 31,  0,  0, 32,  0, 35, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    91.84, 6,  drogue,   -7.95,  66012.00, 3470.76, 2150.90,  -29.03, 33.2, 0.00, 0.00, 3.86, 1, 1, 10,  32.9470412,-106.9169863,  3699.0, 2022,  6, 24, 15, 18, 48,      984,     2510, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 26,  0,  0, 35,  0,  0,  0,  0, 23, 26, 27, 31,  0,  0, 32,  0, 35, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,    91.86, 6,  drogue,   -7.95,  66012.00, 3470.76, 2150.90,  -29.03, 33.2, 0.00, 0.00, 3.87, 1, 1, 10,  32.9470412,-106.9169863,  3699.0, 2022,  6, 24, 15, 18, 48,      984,     2510, 328,  67,   1.4,2147483647.0,2147483647.0,  0, 25, 26,  0,  0, 35,  0,  0,  0,  0, 23, 26, 27, 31,  0,  0, 32,  0, 35, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,    97.54, 6,  drogue,  -14.31,  67277.00, 3322.92, 2003.07,  -28.35, 33.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    97.62, 6,  drogue,  -14.31,  67277.00, 3322.92, 2003.07,  -28.35, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    97.64, 6,  drogue,  -14.84,  67363.00, 3312.95, 1993.10,  -28.40, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    97.74, 6,  drogue,  -16.43,  67387.00, 3310.17, 1990.32,  -28.36, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    97.84, 6,  drogue,  -12.19,  67400.00, 3308.67, 1988.81,  -28.28, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    97.94, 6,  drogue,  -11.66,  67461.00, 3301.61, 1981.75,  -28.22, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    97.94, 6,  drogue,  -11.66,  67461.00, 3301.61, 1981.75,  -28.22, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    98.04, 6,  drogue,  -16.43,  67479.00, 3299.53, 1979.67,  -28.11, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    98.14, 6,  drogue,  -19.61,  67520.00, 3294.78, 1974.93,  -27.99, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    98.24, 6,  drogue,  -20.14,  67509.00, 3296.05, 1976.20,  -27.87, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    98.26, 6,  drogue,  -20.14,  67509.00, 3296.05, 1976.20,  -27.87, 33.1, 0.01, 0.00, 3.86, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,    98.34, 6,  drogue,  -18.02,  67533.00, 3293.28, 1973.42,  -27.72, 33.1, 0.01, 0.00, 3.86, 1, 1, 10,  32.9472657,-106.9170301,  3528.0, 2022,  6, 24, 15, 18, 54,     1008,     2364, 329,  65,   1.4,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 28,  0,  0,  0,  0, 27, 27, 30, 31,  0,  0, 35,  0, 31, 28,  0,  0,  0, 25,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,    98.54, 6,  drogue,  -19.61,  67602.00, 3285.31, 1965.45,  -27.41, 33.1, 0.01, 0.00, 3.86, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    98.58, 6,  drogue,  -19.61,  67602.00, 3285.31, 1965.45,  -27.41, 33.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    98.64, 6,  drogue,  -20.14,  67616.00, 3283.69, 1963.83,  -27.25, 33.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    98.74, 6,  drogue,  -20.14,  67634.00, 3281.61, 1961.75,  -27.06, 33.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    98.84, 6,  drogue,  -20.14,  67622.00, 3283.00, 1963.14,  -26.86, 33.1, 0.00, 0.00, 3.86, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    98.90, 6,  drogue,  -20.14,  67622.00, 3283.00, 1963.14,  -26.86, 33.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    98.94, 6,  drogue,  -20.14,  67665.00, 3278.03, 1958.17,  -26.65, 33.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    99.04, 6,  drogue,  -20.67,  67673.00, 3277.11, 1957.25,  -26.44, 33.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    99.14, 6,  drogue,  -18.55,  67724.00, 3271.22, 1951.37,  -26.15, 33.1, 0.00, 0.01, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    99.22, 6,  drogue,  -18.55,  67724.00, 3271.22, 1951.37,  -26.15, 33.1, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    99.24, 6,  drogue,  -18.02,  67723.00, 3271.34, 1951.48,  -25.83, 33.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    99.34, 6,  drogue,  -19.61,  67778.00, 3265.00, 1945.14,  -25.48, 33.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9472884,-106.9170078,  3499.0, 2022,  6, 24, 15, 18, 55,     1009,     2338, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 30, 30,  0,  0, 33,  0,  0,  0,  0, 32, 31, 29, 30,  0,  0, 27,  0, 20, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,    99.44, 6,  drogue,  -19.08,  67773.00, 3265.57, 1945.72,  -25.16, 33.0, 0.00, 0.00, 3.87, 1, 1, 10,  32.9473294,-106.9169831,  3471.0, 2022,  6, 24, 15, 18, 56,     1012,     2314, 329,  64,   1.4,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 31,  0,  0,  0,  0, 31, 30, 27, 34,  0,  0, 28,  0, 27, 26,  0,  0,  0, 21,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   116.04, 6,  drogue,  -10.07,  71648.00, 2828.84, 1508.99,  -26.36, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475420,-106.9167311,  3022.0, 2022,  6, 24, 15, 19, 12,     1021,     1925, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 29, 31,  0,  0, 28,  0,  0,  0,  0, 24, 25, 30, 35,  0,  0, 35,  0, 31, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,   116.18, 6,  drogue,  -11.66,  71646.00, 2829.06, 1509.21,  -26.74, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9475420,-106.9167311,  3022.0, 2022,  6, 24, 15, 19, 12,     1021,     1925, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 29, 31,  0,  0, 28,  0,  0,  0,  0, 24, 25, 30, 35,  0,  0, 35,  0, 31, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.24, 6,  drogue,  -14.84,  71658.00, 2827.74, 1507.88,  -27.04, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9475420,-106.9167311,  3022.0, 2022,  6, 24, 15, 19, 12,     1021,     1925, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 29, 31,  0,  0, 28,  0,  0,  0,  0, 24, 25, 30, 35,  0,  0, 35,  0, 31, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.34, 6,  drogue,  -15.90,  71659.00, 2827.63, 1507.77,  -27.32, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9475420,-106.9167311,  3022.0, 2022,  6, 24, 15, 19, 12,     1021,     1925, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 29, 31,  0,  0, 28,  0,  0,  0,  0, 24, 25, 30, 35,  0,  0, 35,  0, 31, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.44, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.44, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.44, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.44, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.44, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.44, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.01, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.50, 6,  drogue,  -17.49,  71694.00, 2823.77, 1503.92,  -27.57, 32.6, 0.00, 0.01, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.54, 6,  drogue,  -16.43,  71723.00, 2820.58, 1500.72,  -27.79, 32.6, 0.00, 0.01, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.64, 6,  drogue,  -16.43,  71758.00, 2816.73, 1496.87,  -27.94, 32.6, 0.00, 0.01, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.74, 6,  drogue,  -16.96,  71824.00, 2809.46, 1489.61,  -28.06, 32.6, 0.00, 0.01, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.82, 6,  drogue,  -16.96,  71824.00, 2809.46, 1489.61,  -28.06, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.84, 6,  drogue,  -14.84,  71845.00, 2807.15, 1487.30,  -28.10, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   116.94, 6,  drogue,   -9.54,  71879.00, 2803.42, 1483.56,  -28.13, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   117.04, 6,  drogue,   -9.01,  71855.00, 2806.05, 1486.20,  -28.12, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   117.14, 6,  drogue,  -15.37,  71868.00, 2804.63, 1484.77,  -28.15, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   117.14, 6,  drogue,  -15.37,  71868.00, 2804.63, 1484.77,  -28.15, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   117.24, 6,  drogue,  -21.20,  71890.00, 2802.21, 1482.35,  -28.18, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   117.34, 6,  drogue,  -19.61,  71876.00, 2803.75, 1483.89,  -28.21, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474979,-106.9167178,  2994.0, 2022,  6, 24, 15, 19, 13,     1016,     1899, 331,  58,   1.4,2147483647.0,2147483647.0,  0, 27, 25,  0,  0, 35,  0,  0,  0,  0, 30, 34, 24, 27,  0,  0, 28,  0, 26, 26,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   117.44, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.44, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.44, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.44, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.44, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.44, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.46, 6,  drogue,  -20.14,  71946.00, 2796.05, 1476.20,  -28.28, 32.6, 0.00, 0.01, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.54, 6,  drogue,  -21.20,  72000.00, 2790.12, 1470.27,  -28.29, 32.6, 0.00, 0.01, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.64, 6,  drogue,  -17.49,  72017.00, 2788.26, 1468.40,  -28.28, 32.6, 0.00, 0.01, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.74, 6,  drogue,  -13.25,  72002.00, 2789.91, 1470.05,  -28.34, 32.6, 0.00, 0.01, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.78, 6,  drogue,  -13.25,  72002.00, 2789.91, 1470.05,  -28.34, 32.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.84, 6,  drogue,  -13.25,  72021.00, 2787.82, 1467.96,  -28.47, 32.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   117.94, 6,  drogue,  -13.78,  72062.00, 2783.32, 1463.47,  -28.65, 32.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   118.04, 6,  drogue,  -16.43,  72158.00, 2772.80, 1452.94,  -28.90, 32.6, 0.00, 0.00, 3.86, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   118.10, 6,  drogue,  -16.43,  72158.00, 2772.80, 1452.94,  -28.90, 32.6, 0.00, 0.00, 3.87, 1, 1, 10,  32.9474632,-106.9167215,  2964.0, 2022,  6, 24, 15, 19, 14,     1012,     1872, 331,  57,   1.4,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 34,  0,  0,  0,  0, 30, 29, 30, 31,  0,  0, 29,  0, 27, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,   121.74, 6,  drogue,  -12.72,  73014.00, 2679.44, 1359.59,  -25.42, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   121.84, 6,  drogue,  -15.90,  73036.00, 2677.06, 1357.20,  -25.65, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   121.94, 6,  drogue,  -17.49,  73054.00, 2675.10, 1355.25,  -25.85, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   121.94, 6,  drogue,  -17.49,  73054.00, 2675.10, 1355.25,  -25.85, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   122.04, 6,  drogue,  -16.96,  73090.00, 2671.20, 1351.34,  -26.02, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   122.14, 6,  drogue,  -16.43,  73112.00, 2668.81, 1348.96,  -26.13, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   122.24, 6,  drogue,  -15.90,  73104.00, 2669.68, 1349.82,  -26.21, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   122.26, 6,  drogue,  -15.90,  73104.00, 2669.68, 1349.82,  -26.21, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
+6, 5115, 1,VA3NPN,   122.34, 6,  drogue,  -19.08,  73177.00, 2661.77, 1341.91,  -26.25, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475686,-106.9165540,  2853.0, 2022,  6, 24, 15, 19, 18,     1015,     1781, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 33,  0,  0,  0,  0, 29, 30, 31, 31,  0,  0, 31,  0, 35, 31,  0,  0,  0, 26,  0,  0,  0,  0,  0, 29,  0,  0
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+6, 5115, 1,VA3NPN,   122.54, 6,  drogue,  -12.19,  73206.00, 2658.63, 1338.77,  -26.25, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   122.58, 6,  drogue,  -12.19,  73206.00, 2658.63, 1338.77,  -26.25, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   122.64, 6,  drogue,  -14.84,  73200.00, 2659.28, 1339.42,  -26.26, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   122.74, 6,  drogue,  -15.37,  73240.00, 2654.95, 1335.09,  -26.24, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   122.84, 6,  drogue,  -15.90,  73258.00, 2653.00, 1333.14,  -26.17, 32.5, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   122.90, 6,  drogue,  -15.90,  73258.00, 2653.00, 1333.14,  -26.17, 32.5, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   122.94, 6,  drogue,  -15.90,  73304.00, 2648.02, 1328.16,  -26.03, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   123.04, 6,  drogue,  -15.90,  73361.00, 2641.85, 1322.00,  -25.88, 32.5, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   123.14, 6,  drogue,  -15.37,  73394.00, 2638.29, 1318.43,  -25.68, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   123.22, 6,  drogue,  -15.37,  73394.00, 2638.29, 1318.43,  -25.68, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   123.24, 6,  drogue,  -20.14,  73444.00, 2632.88, 1313.03,  -25.48, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   123.34, 6,  drogue,  -20.67,  73463.00, 2630.83, 1310.98,  -25.29, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475735,-106.9165278,  2826.0, 2022,  6, 24, 15, 19, 19,     1015,     1758, 332,  55,   1.4,2147483647.0,2147483647.0,  0, 31, 32,  0,  0, 35,  0,  0,  0,  0, 32, 25, 24, 27,  0,  0, 32,  0, 27, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   123.44, 6,  drogue,  -18.55,  73478.00, 2629.21, 1309.36,  -25.11, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.44, 6,  drogue,  -18.55,  73478.00, 2629.21, 1309.36,  -25.11, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   123.44, 6,  drogue,  -18.55,  73478.00, 2629.21, 1309.36,  -25.11, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.54, 6,  drogue,  -19.08,  73486.00, 2628.35, 1308.49,  -24.95, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.54, 6,  drogue,  -19.08,  73486.00, 2628.35, 1308.49,  -24.95, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.64, 6,  drogue,  -19.61,  73454.00, 2631.80, 1311.95,  -24.83, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.74, 6,  drogue,  -18.02,  73478.00, 2629.21, 1309.36,  -24.74, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.84, 6,  drogue,  -15.37,  73475.00, 2629.54, 1309.68,  -24.67, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.86, 6,  drogue,  -15.37,  73475.00, 2629.54, 1309.68,  -24.67, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   123.94, 6,  drogue,  -11.66,  73519.00, 2624.79, 1304.93,  -24.68, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.04, 6,  drogue,  -14.84,  73543.00, 2622.20, 1302.34,  -24.76, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.14, 6,  drogue,  -18.02,  73561.00, 2620.25, 1300.40,  -24.88, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.18, 6,  drogue,  -18.02,  73561.00, 2620.25, 1300.40,  -24.88, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.24, 6,  drogue,  -16.43,  73587.00, 2617.45, 1297.59,  -25.03, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.34, 6,  drogue,  -15.90,  73627.00, 2613.14, 1293.28,  -25.26, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9475944,-106.9165157,  2799.0, 2022,  6, 24, 15, 19, 20,     1016,     1737, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 30, 24,  0,  0, 27,  0,  0,  0,  0, 26, 31, 23, 27,  0,  0, 26,  0, 25, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.44, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.44, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.44, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.44, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.44, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.44, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.50, 6,  drogue,  -16.43,  73622.00, 2613.67, 1293.82,  -25.51, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.54, 6,  drogue,  -15.90,  73693.00, 2606.02, 1286.17,  -25.78, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.64, 6,  drogue,  -16.96,  73733.00, 2601.72, 1281.86,  -26.07, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.74, 6,  drogue,  -18.02,  73770.00, 2597.73, 1277.88,  -26.38, 32.4, 0.00, 0.00, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.82, 6,  drogue,  -18.02,  73770.00, 2597.73, 1277.88,  -26.38, 32.4, 0.00, 0.01, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.84, 6,  drogue,  -15.90,  73788.00, 2595.79, 1275.94,  -26.70, 32.4, 0.00, 0.01, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   124.94, 6,  drogue,  -19.08,  73767.00, 2598.05, 1278.20,  -27.04, 32.4, 0.00, 0.01, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.04, 6,  drogue,  -18.55,  73786.00, 2596.01, 1276.15,  -27.42, 32.4, 0.00, 0.01, 3.87, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.14, 6,  drogue,  -20.14,  73801.00, 2594.40, 1274.54,  -27.79, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.14, 6,  drogue,  -20.14,  73801.00, 2594.40, 1274.54,  -27.79, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.24, 6,  drogue,  -19.08,  73832.00, 2591.06, 1271.21,  -28.14, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.34, 6,  drogue,  -19.08,  73848.00, 2589.34, 1269.48,  -28.46, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476126,-106.9164818,  2773.0, 2022,  6, 24, 15, 19, 21,     1016,     1716, 332,  54,   1.4,2147483647.0,2147483647.0,  0, 31, 30,  0,  0, 23,  0,  0,  0,  0, 31, 30, 25, 25,  0,  0, 35,  0, 31, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.44, 6,  drogue,  -18.02,  73869.00, 2587.08, 1267.23,  -28.75, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476153,-106.9164264,  2745.0, 2022,  6, 24, 15, 19, 22,     1014,     1693, 333,  53,   1.4,2147483647.0,2147483647.0,  0, 22, 29,  0,  0, 31,  0,  0,  0,  0, 22, 32, 24, 32,  0,  0, 32,  0, 31, 23,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.44, 6,  drogue,  -18.02,  73869.00, 2587.08, 1267.23,  -28.75, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476153,-106.9164264,  2745.0, 2022,  6, 24, 15, 19, 22,     1014,     1693, 333,  53,   1.4,2147483647.0,2147483647.0,  0, 22, 29,  0,  0, 31,  0,  0,  0,  0, 22, 32, 24, 32,  0,  0, 32,  0, 31, 23,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.44, 6,  drogue,  -18.02,  73869.00, 2587.08, 1267.23,  -28.75, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476153,-106.9164264,  2745.0, 2022,  6, 24, 15, 19, 22,     1014,     1693, 333,  53,   1.4,2147483647.0,2147483647.0,  0, 22, 29,  0,  0, 31,  0,  0,  0,  0, 22, 32, 24, 32,  0,  0, 32,  0, 31, 23,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.44, 6,  drogue,  -18.02,  73869.00, 2587.08, 1267.23,  -28.75, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476153,-106.9164264,  2745.0, 2022,  6, 24, 15, 19, 22,     1014,     1693, 333,  53,   1.4,2147483647.0,2147483647.0,  0, 22, 29,  0,  0, 31,  0,  0,  0,  0, 22, 32, 24, 32,  0,  0, 32,  0, 31, 23,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   125.44, 6,  drogue,  -18.02,  73869.00, 2587.08, 1267.23,  -28.75, 32.4, 0.00, 0.00, 3.86, 1, 1, 10,  32.9476153,-106.9164264,  2745.0, 2022,  6, 24, 15, 19, 22,     1014,     1693, 333,  53,   1.4,2147483647.0,2147483647.0,  0, 22, 29,  0,  0, 31,  0,  0,  0,  0, 22, 32, 24, 32,  0,  0, 32,  0, 31, 23,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   147.64, 6,  drogue,  -18.55,  79041.00, 2046.12,  726.27,  -23.72, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   147.74, 6,  drogue,  -18.55,  79067.00, 2043.48,  723.62,  -24.17, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   147.84, 6,  drogue,  -20.14,  79159.00, 2034.12,  714.27,  -24.70, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   147.86, 6,  drogue,  -20.14,  79159.00, 2034.12,  714.27,  -24.70, 32.0, 0.00, 0.01, 3.87, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   147.94, 6,  drogue,  -16.96,  79182.00, 2031.78,  711.93,  -25.27, 32.0, 0.00, 0.01, 3.87, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.04, 6,  drogue,  -13.25,  79213.00, 2028.63,  708.78,  -25.89, 32.0, 0.00, 0.01, 3.87, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.14, 6,  drogue,  -10.60,  79195.00, 2030.46,  710.61,  -26.51, 32.0, 0.00, 0.01, 3.87, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.18, 6,  drogue,  -10.60,  79195.00, 2030.46,  710.61,  -26.51, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.24, 6,  drogue,  -10.07,  79218.00, 2028.13,  708.27,  -27.15, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.34, 6,  drogue,   -9.01,  79177.00, 2032.29,  712.44,  -27.71, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484644,-106.9156889,  2153.0, 2022,  6, 24, 15, 19, 44,     1072,     1316, 338,  35,   1.7,2147483647.0,2147483647.0,  0, 29, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 28,  0,  0, 33,  0, 31, 26,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,   148.50, 6,  drogue,   -8.48,  79268.00, 2023.05,  703.19,  -28.26, 32.0, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.54, 6,  drogue,   -8.48,  79286.00, 2021.22,  701.36,  -28.81, 32.0, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.64, 6,  drogue,   -2.65,  79289.00, 2020.91,  701.06,  -29.32, 32.0, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.74, 6,  drogue,   27.56,  79533.00, 1996.17,  676.32,  -29.72, 32.0, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.82, 6,  drogue,   27.56,  79533.00, 1996.17,  676.32,  -29.72, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.84, 6,  drogue,   29.68,  79462.00, 2003.37,  683.51,  -30.02, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   148.94, 6,  drogue,  -10.07,  79396.00, 2010.06,  690.20,  -30.20, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   149.04, 6,  drogue,   -9.54,  79435.00, 2006.10,  686.25,  -30.32, 32.0, 0.00, 0.00, 3.86, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   149.14, 6,  drogue,   -3.18,  79444.00, 2005.19,  685.33,  -30.33, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   149.14, 6,  drogue,   -3.18,  79444.00, 2005.19,  685.33,  -30.33, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   149.24, 6,  drogue,   -3.18,  79557.00, 1993.74,  673.89,  -30.25, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   149.34, 6,  drogue,   -0.00,  79674.00, 1981.90,  662.05,  -30.12, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484932,-106.9156267,  2127.0, 2022,  6, 24, 15, 19, 45,     1073,     1302, 339,  34,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 36,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 29,  0, 30, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   149.44, 6,  drogue,   -4.77,  79714.00, 1977.86,  658.00,  -29.87, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484898,-106.9155675,  2097.0, 2022,  6, 24, 15, 19, 46,     1070,     1283, 339,  33,   1.7,2147483647.0,2147483647.0,  0, 27, 26,  0,  0, 29,  0,  0,  0,  0, 27, 28, 26, 28,  0,  0, 30,  0, 29, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   149.44, 6,  drogue,   -4.77,  79714.00, 1977.86,  658.00,  -29.87, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484898,-106.9155675,  2097.0, 2022,  6, 24, 15, 19, 46,     1070,     1283, 339,  33,   1.7,2147483647.0,2147483647.0,  0, 27, 26,  0,  0, 29,  0,  0,  0,  0, 27, 28, 26, 28,  0,  0, 30,  0, 29, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   151.42, 6,  drogue,  -12.19,  80127.00, 1936.20,  616.34,  -24.90, 31.9, 0.00, 0.01, 3.86, 1, 1,  9,  32.9485085,-106.9155050,  2069.0, 2022,  6, 24, 15, 19, 47,     1070,     1268, 339,  32,   1.7,2147483647.0,2147483647.0,  0, 27, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 30,  0, 29, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   151.42, 6,  drogue,  -12.19,  80127.00, 1936.20,  616.34,  -24.90, 31.9, 0.00, 0.01, 3.86, 1, 1,  9,  32.9485085,-106.9155050,  2069.0, 2022,  6, 24, 15, 19, 47,     1070,     1268, 339,  32,   1.7,2147483647.0,2147483647.0,  0, 27, 26,  0,  0, 29,  0,  0,  0,  0, 26, 28, 26, 32,  0,  0, 30,  0, 29, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   151.44, 6,  drogue,   -8.48,  80032.00, 1945.76,  625.91,  -24.86, 31.9, 0.00, 0.01, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   151.54, 6,  drogue,  -16.96,  80109.00, 1938.01,  618.15,  -24.78, 31.9, 0.00, 0.01, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   151.64, 6,  drogue,  -15.90,  80120.00, 1936.90,  617.04,  -24.67, 31.9, 0.00, 0.01, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   151.70, 6,  drogue,  -15.90,  80120.00, 1936.90,  617.04,  -24.67, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   151.74, 6,  drogue,  -16.43,  80188.00, 1930.06,  610.20,  -24.56, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   151.84, 6,  drogue,  -13.78,  80223.00, 1926.54,  606.68,  -24.48, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   151.94, 6,  drogue,  -16.96,  80280.00, 1920.81,  600.95,  -24.42, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.02, 6,  drogue,  -16.96,  80280.00, 1920.81,  600.95,  -24.42, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.04, 6,  drogue,  -18.02,  80324.00, 1916.38,  596.53,  -24.39, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.14, 6,  drogue,  -17.49,  80369.00, 1911.86,  592.01,  -24.34, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.24, 6,  drogue,  -14.84,  80417.00, 1907.05,  587.19,  -24.26, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.34, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.34, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.43, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.43, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.43, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.43, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.43, 6,  drogue,  -19.08,  80386.00, 1910.16,  590.30,  -24.20, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485384,-106.9154554,  2043.0, 2022,  6, 24, 15, 19, 48,     1072,     1255, 340,  31,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 26, 32, 27, 31,  0,  0, 33,  0, 28, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   152.44, 6,  drogue,  -19.08,  80362.00, 1912.57,  592.71,  -24.15, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.54, 6,  drogue,  -19.61,  80335.00, 1915.28,  595.42,  -24.11, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.64, 6,  drogue,  -19.61,  80394.00, 1909.35,  589.50,  -24.09, 31.9, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.66, 6,  drogue,  -19.61,  80394.00, 1909.35,  589.50,  -24.09, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.74, 6,  drogue,  -19.08,  80424.00, 1906.34,  586.49,  -24.11, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.84, 6,  drogue,  -18.02,  80452.00, 1903.53,  583.68,  -24.16, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.94, 6,  drogue,  -18.55,  80504.00, 1898.32,  578.46,  -24.18, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   152.98, 6,  drogue,  -18.55,  80504.00, 1898.32,  578.46,  -24.18, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   153.04, 6,  drogue,  -18.02,  80539.00, 1894.81,  574.95,  -24.25, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   153.14, 6,  drogue,  -18.02,  80554.00, 1893.30,  573.45,  -24.31, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   153.24, 6,  drogue,  -18.55,  80559.00, 1892.80,  572.95,  -24.37, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   153.30, 6,  drogue,  -18.55,  80559.00, 1892.80,  572.95,  -24.37, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   153.34, 6,  drogue,  -19.61,  80604.00, 1888.29,  568.44,  -24.45, 31.9, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485575,-106.9154293,  2017.0, 2022,  6, 24, 15, 19, 49,     1073,     1243, 340,  30,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 28,  0,  0,  0,  0, 26, 31, 27, 32,  0,  0, 30,  0, 32, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   153.44, 6,  drogue,  -18.02,  80619.00, 1886.79,  566.93,  -24.47, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.44, 6,  drogue,  -18.02,  80619.00, 1886.79,  566.93,  -24.47, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.44, 6,  drogue,  -18.02,  80619.00, 1886.79,  566.93,  -24.47, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.44, 6,  drogue,  -18.02,  80619.00, 1886.79,  566.93,  -24.47, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.44, 6,  drogue,  -18.02,  80619.00, 1886.79,  566.93,  -24.47, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.44, 6,  drogue,  -18.02,  80619.00, 1886.79,  566.93,  -24.47, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.54, 6,  drogue,  -18.55,  80639.00, 1884.79,  564.93,  -24.57, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.62, 6,  drogue,  -18.55,  80639.00, 1884.79,  564.93,  -24.57, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.64, 6,  drogue,  -19.08,  80654.00, 1883.29,  563.43,  -24.68, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.74, 6,  drogue,  -18.55,  80715.00, 1877.18,  557.32,  -24.82, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.84, 6,  drogue,  -18.55,  80734.00, 1875.28,  555.42,  -24.98, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.94, 6,  drogue,  -18.55,  80729.00, 1875.78,  555.92,  -25.14, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   153.94, 6,  drogue,  -18.55,  80729.00, 1875.78,  555.92,  -25.14, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.04, 6,  drogue,  -18.55,  80763.00, 1872.38,  552.52,  -25.31, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.14, 6,  drogue,  -19.08,  80782.00, 1870.48,  550.62,  -25.46, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.24, 6,  drogue,  -18.02,  80799.00, 1868.78,  548.92,  -25.57, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.26, 6,  drogue,  -18.02,  80799.00, 1868.78,  548.92,  -25.57, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.34, 6,  drogue,  -18.02,  80827.00, 1865.98,  546.12,  -25.61, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.43, 6,  drogue,  -18.02,  80827.00, 1865.98,  546.12,  -25.61, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.43, 6,  drogue,  -18.02,  80827.00, 1865.98,  546.12,  -25.61, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.43, 6,  drogue,  -18.02,  80827.00, 1865.98,  546.12,  -25.61, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.43, 6,  drogue,  -18.02,  80827.00, 1865.98,  546.12,  -25.61, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.43, 6,  drogue,  -18.02,  80827.00, 1865.98,  546.12,  -25.61, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485534,-106.9153944,  1990.0, 2022,  6, 24, 15, 19, 50,     1071,     1228, 340,  29,   1.7,2147483647.0,2147483647.0,  0, 26, 27,  0,  0, 33,  0,  0,  0,  0, 25, 26, 30, 26,  0,  0, 30,  0, 32, 27,  0,  0,  0, 25,  0,  0,  0,  0,  0, 32,  0,  0
+6, 5115, 1,VA3NPN,   154.44, 6,  drogue,  -19.08,  80841.00, 1864.58,  544.72,  -25.60, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.54, 6,  drogue,  -19.61,  80889.00, 1859.78,  539.93,  -25.55, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.58, 6,  drogue,  -19.61,  80889.00, 1859.78,  539.93,  -25.55, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.64, 6,  drogue,  -18.55,  80910.00, 1857.68,  537.83,  -25.50, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.74, 6,  drogue,  -19.08,  80950.00, 1853.69,  533.83,  -25.44, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.84, 6,  drogue,  -19.08,  81027.00, 1846.00,  526.15,  -25.36, 31.8, 0.00, 0.00, 3.87, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.90, 6,  drogue,  -19.08,  81027.00, 1846.00,  526.15,  -25.36, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   154.94, 6,  drogue,  -19.08,  80996.00, 1849.10,  529.24,  -25.28, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   155.04, 6,  drogue,  -19.08,  81048.00, 1843.91,  524.05,  -25.17, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   155.14, 6,  drogue,  -19.61,  81029.00, 1845.81,  525.95,  -25.04, 31.8, 0.00, 0.00, 3.86, 1, 1,  9,  32.9485296,-106.9153380,  1964.0, 2022,  6, 24, 15, 19, 51,     1067,     1212, 340,  28,   1.7,2147483647.0,2147483647.0,  0, 34, 30,  0,  0, 27,  0,  0,  0,  0, 31, 27, 34, 32,  0,  0, 36,  0, 29, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,   158.04, 7,    main,  -25.44,  81764.00, 1772.75,  452.90,  -25.43, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9484059,-106.9151603,  1887.0, 2022,  6, 24, 15, 19, 54,     1049,     1160, 341,  25,   1.7,2147483647.0,2147483647.0,  0, 25, 21,  0,  0, 28,  0,  0,  0,  0, 27, 31, 28, 30,  0,  0, 30,  0, 30, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,   158.84, 7,    main,  -24.91,  81955.00, 1753.85,  434.00,  -20.25, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   158.94, 7,    main,  134.11,  81965.00, 1752.87,  433.01,  -19.37, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.04, 7,    main,   18.02,  82064.00, 1743.09,  423.23,  -18.47, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.06, 7,    main,   18.02,  82064.00, 1743.09,  423.23,  -18.47, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.14, 7,    main,  142.06,  82085.00, 1741.01,  421.16,  -17.58, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.24, 7,    main,   73.68,  82093.00, 1740.22,  420.37,  -16.70, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.34, 7,    main,  129.34,  82103.00, 1739.24,  419.38,  -15.83, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.38, 7,    main,  129.34,  82103.00, 1739.24,  419.38,  -15.83, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483549,-106.9151201,  1859.0, 2022,  6, 24, 15, 19, 55,     1042,     1143, 341,  24,   1.7,2147483647.0,2147483647.0,  0, 24, 19,  0,  0, 18,  0,  0,  0,  0, 26, 33, 34, 25,  0,  0, 32,  0, 34, 34,  0,  0,  0, 21,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.44, 7,    main,   29.68,  82076.00, 1741.90,  422.04,  -15.01, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.44, 7,    main,   29.68,  82076.00, 1741.90,  422.04,  -15.01, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.44, 7,    main,   29.68,  82076.00, 1741.90,  422.04,  -15.01, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
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+6, 5115, 1,VA3NPN,   159.44, 7,    main,   29.68,  82076.00, 1741.90,  422.04,  -15.01, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.54, 7,    main,  -14.84,  82062.00, 1743.28,  423.43,  -14.24, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.64, 7,    main,   -6.36,  82065.00, 1742.99,  423.13,  -13.53, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.70, 7,    main,   -6.36,  82065.00, 1742.99,  423.13,  -13.53, 31.7, 0.01, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.74, 7,    main,   15.37,  82093.00, 1740.22,  420.37,  -12.90, 31.7, 0.01, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.84, 7,    main,    6.36,  82127.00, 1736.87,  417.01,  -12.32, 31.7, 0.01, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   159.94, 7,    main,   -3.71,  82178.00, 1731.84,  411.98,  -11.80, 31.7, 0.01, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.02, 7,    main,   -3.71,  82178.00, 1731.84,  411.98,  -11.80, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.04, 7,    main,   14.31,  82147.00, 1734.89,  415.04,  -11.30, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.14, 7,    main,    0.53,  82173.00, 1732.33,  412.47,  -10.84, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.24, 7,    main,   -5.30,  82188.00, 1730.85,  410.99,  -10.44, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.34, 7,    main,   -6.89,  82167.00, 1732.92,  413.06,  -10.08, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.34, 7,    main,   -6.89,  82167.00, 1732.92,  413.06,  -10.08, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9483197,-106.9150608,  1835.0, 2022,  6, 24, 15, 19, 56,     1036,     1128, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 29, 23,  0,  0, 33,  0,  0,  0,  0, 31, 30, 30, 35,  0,  0, 34,  0, 31, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 5115, 1,VA3NPN,   160.44, 7,    main,  -30.22,  82210.00, 1728.68,  408.82,   -9.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9482913,-106.9150353,  1820.0, 2022,  6, 24, 15, 19, 57,     1033,     1119, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 25, 30,  0,  0, 28,  0,  0,  0,  0, 25, 30, 28, 27,  0,  0, 33,  0, 30, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   160.44, 7,    main,  -30.22,  82210.00, 1728.68,  408.82,   -9.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9482913,-106.9150353,  1820.0, 2022,  6, 24, 15, 19, 57,     1033,     1119, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 25, 30,  0,  0, 28,  0,  0,  0,  0, 25, 30, 28, 27,  0,  0, 33,  0, 30, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   160.44, 7,    main,  -30.22,  82210.00, 1728.68,  408.82,   -9.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9482913,-106.9150353,  1820.0, 2022,  6, 24, 15, 19, 57,     1033,     1119, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 25, 30,  0,  0, 28,  0,  0,  0,  0, 25, 30, 28, 27,  0,  0, 33,  0, 30, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   160.44, 7,    main,  -30.22,  82210.00, 1728.68,  408.82,   -9.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9482913,-106.9150353,  1820.0, 2022,  6, 24, 15, 19, 57,     1033,     1119, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 25, 30,  0,  0, 28,  0,  0,  0,  0, 25, 30, 28, 27,  0,  0, 33,  0, 30, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   160.44, 7,    main,  -30.22,  82210.00, 1728.68,  408.82,   -9.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9482913,-106.9150353,  1820.0, 2022,  6, 24, 15, 19, 57,     1033,     1119, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 25, 30,  0,  0, 28,  0,  0,  0,  0, 25, 30, 28, 27,  0,  0, 33,  0, 30, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   160.44, 7,    main,  -30.22,  82210.00, 1728.68,  408.82,   -9.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9482913,-106.9150353,  1820.0, 2022,  6, 24, 15, 19, 57,     1033,     1119, 341,  23,   1.7,2147483647.0,2147483647.0,  0, 25, 30,  0,  0, 28,  0,  0,  0,  0, 25, 30, 28, 27,  0,  0, 33,  0, 30, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,   179.44, 7,    main,   -5.30,  83497.00, 1602.58,  282.73,   -6.66, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9488752,-106.9152904,  1691.0, 2022,  6, 24, 15, 20, 16,     1102,     1142, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 32, 30,  0,  0, 28,  0,  0,  0,  0, 32, 18, 31, 33,  0,  0, 33,  0, 27, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 33,  0,  0
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+6, 5115, 1,VA3NPN,   180.04, 7,    main,   -1.59,  83561.00, 1596.35,  276.50,   -6.62, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9488752,-106.9152904,  1691.0, 2022,  6, 24, 15, 20, 16,     1102,     1142, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 32, 30,  0,  0, 28,  0,  0,  0,  0, 32, 18, 31, 33,  0,  0, 33,  0, 27, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,   180.14, 7,    main,   -1.06,  83531.00, 1599.27,  279.42,   -6.60, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9488752,-106.9152904,  1691.0, 2022,  6, 24, 15, 20, 16,     1102,     1142, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 32, 30,  0,  0, 28,  0,  0,  0,  0, 32, 18, 31, 33,  0,  0, 33,  0, 27, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,   180.18, 7,    main,   -1.06,  83531.00, 1599.27,  279.42,   -6.60, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9488752,-106.9152904,  1691.0, 2022,  6, 24, 15, 20, 16,     1102,     1142, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 32, 30,  0,  0, 28,  0,  0,  0,  0, 32, 18, 31, 33,  0,  0, 33,  0, 27, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,   180.24, 7,    main,    0.53,  83542.00, 1598.20,  278.35,   -6.58, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9488752,-106.9152904,  1691.0, 2022,  6, 24, 15, 20, 16,     1102,     1142, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 32, 30,  0,  0, 28,  0,  0,  0,  0, 32, 18, 31, 33,  0,  0, 33,  0, 27, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,   180.34, 7,    main,   -0.00,  83568.00, 1595.67,  275.82,   -6.55, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9488752,-106.9152904,  1691.0, 2022,  6, 24, 15, 20, 16,     1102,     1142, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 32, 30,  0,  0, 28,  0,  0,  0,  0, 32, 18, 31, 33,  0,  0, 33,  0, 27, 28,  0,  0,  0, 24,  0,  0,  0,  0,  0, 33,  0,  0
+6, 5115, 1,VA3NPN,   180.44, 7,    main,   -0.00,  83563.00, 1596.16,  276.30,   -6.52, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
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+6, 5115, 1,VA3NPN,   180.50, 7,    main,   -0.00,  83563.00, 1596.16,  276.30,   -6.52, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
+6, 5115, 1,VA3NPN,   180.54, 7,    main,   -1.06,  83562.00, 1596.26,  276.40,   -6.49, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
+6, 5115, 1,VA3NPN,   180.64, 7,    main,   -2.65,  83579.00, 1594.60,  274.75,   -6.45, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
+6, 5115, 1,VA3NPN,   180.74, 7,    main,   -3.71,  83590.00, 1593.53,  273.68,   -6.42, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
+6, 5115, 1,VA3NPN,   180.82, 7,    main,   -3.71,  83590.00, 1593.53,  273.68,   -6.42, 31.6, 0.01, 0.00, 3.87, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
+6, 5115, 1,VA3NPN,   180.84, 7,    main,   -4.24,  83585.00, 1594.02,  274.16,   -6.38, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
+6, 5115, 1,VA3NPN,   180.94, 7,    main,   -4.77,  83599.00, 1592.66,  272.80,   -6.32, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9489269,-106.9152981,  1684.0, 2022,  6, 24, 15, 20, 17,     1108,     1146, 341,  15,   1.7,2147483647.0,2147483647.0,  0, 26, 28,  0,  0, 31,  0,  0,  0,  0, 26, 29, 31, 34,  0,  0, 36,  0, 28, 32,  0,  0,  0, 24,  0,  0,  0,  0,  0, 35,  0,  0
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+6, 5115, 1,VA3NPN,   189.94, 7,    main,   -3.18,  84256.00, 1528.95,  209.10,   -6.90, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9490168,-106.9151699,  1618.0, 2022,  6, 24, 15, 20, 26,     1113,     1136, 342,  12,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 31,  0,  0,  0,  0, 31, 27, 29, 29,  0,  0, 26,  0, 26, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   190.04, 7,    main,   -4.24,  84259.00, 1528.66,  208.81,   -6.86, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9490168,-106.9151699,  1618.0, 2022,  6, 24, 15, 20, 26,     1113,     1136, 342,  12,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 31,  0,  0,  0,  0, 31, 27, 29, 29,  0,  0, 26,  0, 26, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 28,  0,  0
+6, 5115, 1,VA3NPN,   190.10, 7,    main,   -4.24,  84259.00, 1528.66,  208.81,   -6.86, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9490168,-106.9151699,  1618.0, 2022,  6, 24, 15, 20, 26,     1113,     1136, 342,  12,   1.7,2147483647.0,2147483647.0,  0, 29, 25,  0,  0, 31,  0,  0,  0,  0, 31, 27, 29, 29,  0,  0, 26,  0, 26, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 28,  0,  0
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+6, 5115, 1,VA3NPN,   198.74, 7,    main,   -1.59,  84854.00, 1471.32,  151.47,   -5.58, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9490614,-106.9155519,  1553.0, 2022,  6, 24, 15, 20, 35,     1129,     1141, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 31, 29,  0,  0, 30,  0,  0,  0,  0, 30, 27, 30, 35,  0,  0, 35,  0, 28, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 32,  0,  0
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+6, 5115, 1,VA3NPN,   199.64, 7,    main,   -2.12,  84876.00, 1469.21,  149.35,   -5.65, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   199.70, 7,    main,   -2.12,  84876.00, 1469.21,  149.35,   -5.65, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   199.74, 7,    main,   -1.06,  84907.00, 1466.23,  146.37,   -5.70, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   199.84, 7,    main,   -2.12,  84879.00, 1468.92,  149.06,   -5.76, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   199.94, 7,    main,   -2.65,  84913.00, 1465.65,  145.80,   -5.80, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.02, 7,    main,   -2.65,  84913.00, 1465.65,  145.80,   -5.80, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.04, 7,    main,   -2.65,  84917.00, 1465.27,  145.41,   -5.84, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.14, 7,    main,   -4.77,  84931.00, 1463.92,  144.07,   -5.86, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.24, 7,    main,   -4.24,  84937.00, 1463.35,  143.49,   -5.89, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.34, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.34, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.43, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.43, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.43, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.43, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.43, 7,    main,   -4.24,  84930.00, 1464.02,  144.16,   -5.90, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491081,-106.9155428,  1548.0, 2022,  6, 24, 15, 20, 36,     1134,     1145, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 32, 29,  0,  0, 31,  0,  0,  0,  0, 34, 25, 30, 31,  0,  0, 35,  0, 28, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 34,  0,  0
+6, 5115, 1,VA3NPN,   200.44, 7,    main,   -5.30,  84946.00, 1462.48,  142.63,   -5.89, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.54, 7,    main,   -4.24,  84923.00, 1464.69,  144.84,   -5.88, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.64, 7,    main,   -3.71,  84970.00, 1460.18,  140.32,   -5.86, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.66, 7,    main,   -3.71,  84970.00, 1460.18,  140.32,   -5.86, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.74, 7,    main,   -5.30,  84982.00, 1459.03,  139.17,   -5.84, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.84, 7,    main,   -3.18,  84949.00, 1462.20,  142.34,   -5.81, 31.6, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.94, 7,    main,   -0.53,  84967.00, 1460.47,  140.61,   -5.78, 31.6, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   200.98, 7,    main,   -0.53,  84967.00, 1460.47,  140.61,   -5.78, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.04, 7,    main,   -2.65,  84982.00, 1459.03,  139.17,   -5.75, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.14, 7,    main,   -1.59,  84991.00, 1458.16,  138.31,   -5.73, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.24, 7,    main,   -0.53,  84980.00, 1459.22,  139.36,   -5.71, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.30, 7,    main,   -0.53,  84980.00, 1459.22,  139.36,   -5.71, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.34, 7,    main,   -0.00,  85006.00, 1456.72,  136.87,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.43, 7,    main,   -0.00,  85006.00, 1456.72,  136.87,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.43, 7,    main,   -0.00,  85006.00, 1456.72,  136.87,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.43, 7,    main,   -0.00,  85006.00, 1456.72,  136.87,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.43, 7,    main,   -0.00,  85006.00, 1456.72,  136.87,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.43, 7,    main,   -0.00,  85006.00, 1456.72,  136.87,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491501,-106.9155338,  1542.0, 2022,  6, 24, 15, 20, 37,     1138,     1148, 340,   8,   1.7,2147483647.0,2147483647.0,  0, 25, 29,  0,  0, 30,  0,  0,  0,  0, 22, 30, 28, 26,  0,  0, 33,  0, 29, 23,  0,  0,  0, 31,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.44, 7,    main,    0.53,  84999.00, 1457.40,  137.54,   -5.67, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.54, 7,    main,   -0.53,  85002.00, 1457.11,  137.25,   -5.66, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.62, 7,    main,   -0.53,  85002.00, 1457.11,  137.25,   -5.66, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.64, 7,    main,   -0.53,  85018.00, 1455.57,  135.72,   -5.66, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.74, 7,    main,   -0.53,  85021.00, 1455.28,  135.43,   -5.68, 31.6, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.84, 7,    main,   -2.65,  85035.00, 1453.94,  134.09,   -5.68, 31.7, 0.01, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.94, 7,    main,   -4.24,  85009.00, 1456.44,  136.58,   -5.70, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   201.94, 7,    main,   -4.24,  85009.00, 1456.44,  136.58,   -5.70, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.04, 7,    main,   -4.77,  85044.00, 1453.08,  133.22,   -5.73, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.14, 7,    main,   -6.36,  85031.00, 1454.33,  134.47,   -5.77, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.24, 7,    main,   -5.30,  85046.00, 1452.89,  133.03,   -5.80, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.26, 7,    main,   -5.30,  85046.00, 1452.89,  133.03,   -5.80, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.34, 7,    main,   -4.77,  85049.00, 1452.60,  132.74,   -5.82, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.43, 7,    main,   -4.77,  85049.00, 1452.60,  132.74,   -5.82, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.43, 7,    main,   -4.77,  85049.00, 1452.60,  132.74,   -5.82, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.43, 7,    main,   -4.77,  85049.00, 1452.60,  132.74,   -5.82, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.43, 7,    main,   -4.77,  85049.00, 1452.60,  132.74,   -5.82, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.43, 7,    main,   -4.77,  85049.00, 1452.60,  132.74,   -5.82, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9491870,-106.9155208,  1536.0, 2022,  6, 24, 15, 20, 38,     1142,     1151, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 26, 33,  0,  0, 29,  0,  0,  0,  0, 24, 30, 27, 25,  0,  0, 33,  0, 30, 22,  0,  0,  0, 30,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   202.44, 7,    main,   -2.65,  85043.00, 1453.17,  133.32,   -5.83, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.54, 7,    main,   -4.77,  85081.00, 1449.53,  129.67,   -5.84, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.58, 7,    main,   -4.77,  85081.00, 1449.53,  129.67,   -5.84, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.64, 7,    main,   -2.12,  85067.00, 1450.87,  131.02,   -5.87, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.74, 7,    main,   -1.59,  85076.00, 1450.01,  130.15,   -5.89, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.84, 7,    main,   -0.53,  85085.00, 1449.15,  129.29,   -5.89, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.90, 7,    main,   -0.53,  85085.00, 1449.15,  129.29,   -5.89, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   202.94, 7,    main,   -0.00,  85102.00, 1447.52,  127.66,   -5.90, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.04, 7,    main,   -0.53,  85117.00, 1446.08,  126.22,   -5.90, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.14, 7,    main,   -1.06,  85106.00, 1447.13,  127.28,   -5.92, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.22, 7,    main,   -1.06,  85106.00, 1447.13,  127.28,   -5.92, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.24, 7,    main,   -1.06,  85111.00, 1446.65,  126.80,   -5.91, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.34, 7,    main,   -2.12,  85087.00, 1448.95,  129.10,   -5.92, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.43, 7,    main,   -2.12,  85087.00, 1448.95,  129.10,   -5.92, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.43, 7,    main,   -2.12,  85087.00, 1448.95,  129.10,   -5.92, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.43, 7,    main,   -2.12,  85087.00, 1448.95,  129.10,   -5.92, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   203.43, 7,    main,   -2.12,  85087.00, 1448.95,  129.10,   -5.92, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9492265,-106.9155191,  1530.0, 2022,  6, 24, 15, 20, 39,     1146,     1154, 341,   7,   1.7,2147483647.0,2147483647.0,  0, 25, 27,  0,  0, 29,  0,  0,  0,  0, 25, 29, 29, 35,  0,  0, 32,  0, 33, 25,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
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+6, 5115, 1,VA3NPN,   205.24, 7,    main,   -2.12,  85227.00, 1435.54,  115.68,   -5.68, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493142,-106.9155380,  1518.0, 2022,  6, 24, 15, 20, 41,     1156,     1163, 341,   6,   1.7,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 27,  0,  0,  0,  0, 30, 34, 30, 25,  0,  0, 26,  0, 30, 25,  0,  0,  0, 32,  0,  0,  0,  0,  0, 24,  0,  0
+6, 5115, 1,VA3NPN,   205.34, 7,    main,   -1.59,  85237.00, 1434.58,  114.73,   -5.64, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493142,-106.9155380,  1518.0, 2022,  6, 24, 15, 20, 41,     1156,     1163, 341,   6,   1.7,2147483647.0,2147483647.0,  0, 31, 28,  0,  0, 27,  0,  0,  0,  0, 30, 34, 30, 25,  0,  0, 26,  0, 30, 25,  0,  0,  0, 32,  0,  0,  0,  0,  0, 24,  0,  0
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+6, 5115, 1,VA3NPN,   212.04, 7,    main,   -0.00,  85650.00, 1395.11,   75.26,   -6.91, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494867,-106.9153670,  1478.0, 2022,  6, 24, 15, 20, 48,     1169,     1172, 342,   4,   1.7,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 29,  0,  0,  0,  0, 32, 35, 27, 26,  0,  0, 27,  0, 26, 24,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   212.14, 7,    main,   -0.53,  85663.00, 1393.87,   74.02,   -6.89, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494867,-106.9153670,  1478.0, 2022,  6, 24, 15, 20, 48,     1169,     1172, 342,   4,   1.7,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 29,  0,  0,  0,  0, 32, 35, 27, 26,  0,  0, 27,  0, 26, 24,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
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+6, 5115, 1,VA3NPN,   212.24, 7,    main,   -0.00,  85656.00, 1394.54,   74.69,   -6.86, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494867,-106.9153670,  1478.0, 2022,  6, 24, 15, 20, 48,     1169,     1172, 342,   4,   1.7,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 29,  0,  0,  0,  0, 32, 35, 27, 26,  0,  0, 27,  0, 26, 24,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   212.34, 7,    main,   -1.59,  85691.00, 1391.20,   71.35,   -6.84, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494867,-106.9153670,  1478.0, 2022,  6, 24, 15, 20, 48,     1169,     1172, 342,   4,   1.7,2147483647.0,2147483647.0,  0, 33, 27,  0,  0, 29,  0,  0,  0,  0, 32, 35, 27, 26,  0,  0, 27,  0, 26, 24,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
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+6, 5115, 1,VA3NPN,   218.04, 7,    main,   -2.65,  86081.00, 1354.09,   34.23,   -6.19, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   218.14, 7,    main,    1.59,  86089.00, 1353.33,   33.47,   -6.20, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   218.24, 7,    main,   -2.65,  86085.00, 1353.71,   33.85,   -6.21, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   218.26, 7,    main,   -2.65,  86085.00, 1353.71,   33.85,   -6.21, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   218.34, 7,    main,   -1.59,  86094.00, 1352.85,   33.00,   -6.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   218.42, 7,    main,   -1.59,  86094.00, 1352.85,   33.00,   -6.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   218.42, 7,    main,   -1.59,  86094.00, 1352.85,   33.00,   -6.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493131,-106.9154056,  1433.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 25, 34,  0,  0, 27,  0,  0,  0,  0, 21, 31, 25, 28,  0,  0, 26,  0, 28, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
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+6, 5115, 1,VA3NPN,   218.44, 7,    main,   -0.53,  86098.00, 1352.47,   32.62,   -6.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.54, 7,    main,   -3.71,  86108.00, 1351.52,   31.67,   -6.24, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.58, 7,    main,   -3.71,  86108.00, 1351.52,   31.67,   -6.24, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.64, 7,    main,   -2.65,  86125.00, 1349.91,   30.05,   -6.26, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.74, 7,    main,   -3.71,  86135.00, 1348.96,   29.11,   -6.26, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.84, 7,    main,   -2.12,  86131.00, 1349.34,   29.49,   -6.26, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.90, 7,    main,   -2.12,  86131.00, 1349.34,   29.49,   -6.26, 31.6, 0.00, 0.01, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   218.94, 7,    main,   -3.18,  86137.00, 1348.77,   28.92,   -6.25, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.04, 7,    main,   -3.71,  86146.00, 1347.92,   28.06,   -6.26, 31.6, 0.00, 0.01, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.14, 7,    main,   -1.59,  86139.00, 1348.58,   28.73,   -6.25, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.22, 7,    main,   -1.59,  86139.00, 1348.58,   28.73,   -6.25, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.24, 7,    main,   -2.12,  86148.00, 1347.73,   27.87,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.34, 7,    main,   -0.00,  86157.00, 1346.87,   27.02,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.43, 7,    main,   -0.00,  86157.00, 1346.87,   27.02,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.43, 7,    main,   -0.00,  86157.00, 1346.87,   27.02,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.43, 7,    main,   -0.00,  86157.00, 1346.87,   27.02,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.43, 7,    main,   -0.00,  86157.00, 1346.87,   27.02,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.43, 7,    main,   -0.00,  86157.00, 1346.87,   27.02,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493307,-106.9154612,  1424.0, 2022,  6, 24, 15, 20, 55,     1155,     1155, 341,   2,   1.7,2147483647.0,2147483647.0,  0, 31, 31,  0,  0, 27,  0,  0,  0,  0, 29, 31, 26, 26,  0,  0, 27,  0, 31, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   219.44, 7,    main,   -2.65,  86163.00, 1346.30,   26.45,   -6.26, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.54, 7,    main,   -0.53,  86181.00, 1344.59,   24.74,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.54, 7,    main,   -0.53,  86181.00, 1344.59,   24.74,   -6.27, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.64, 7,    main,   -1.59,  86175.00, 1345.16,   25.31,   -6.27, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.74, 7,    main,   -0.53,  86197.00, 1343.08,   23.22,   -6.28, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.84, 7,    main,   -3.18,  86200.00, 1342.79,   22.94,   -6.30, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.86, 7,    main,   -3.18,  86200.00, 1342.79,   22.94,   -6.30, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   219.94, 7,    main,   -1.06,  86203.00, 1342.51,   22.65,   -6.30, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.04, 7,    main,   -1.06,  86201.00, 1342.70,   22.84,   -6.31, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.14, 7,    main,   -4.24,  86236.00, 1339.38,   19.52,   -6.33, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.18, 7,    main,   -4.24,  86236.00, 1339.38,   19.52,   -6.33, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.24, 7,    main,   -4.24,  86214.00, 1341.46,   21.61,   -6.34, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.34, 7,    main,   -4.24,  86219.00, 1340.99,   21.13,   -6.35, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.43, 7,    main,   -4.24,  86219.00, 1340.99,   21.13,   -6.35, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
+6, 5115, 1,VA3NPN,   220.43, 7,    main,   -4.24,  86219.00, 1340.99,   21.13,   -6.35, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,   220.43, 7,    main,   -4.24,  86219.00, 1340.99,   21.13,   -6.35, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9493732,-106.9154970,  1418.0, 2022,  6, 24, 15, 20, 56,     1160,     1161, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 30, 26,  0,  0, 27,  0,  0,  0,  0, 29, 31, 27, 25,  0,  0, 28,  0, 32, 25,  0,  0,  0, 30,  0,  0,  0,  0,  0, 25,  0,  0
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+6, 5115, 1,VA3NPN,   220.44, 7,    main,   -3.71,  86230.00, 1339.95,   20.09,   -6.37, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.50, 7,    main,   -3.71,  86230.00, 1339.95,   20.09,   -6.37, 31.6, 0.00, 0.01, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.54, 7,    main,   -4.77,  86247.00, 1338.33,   18.48,   -6.39, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.64, 7,    main,   -5.30,  86255.00, 1337.57,   17.72,   -6.41, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.74, 7,    main,   -2.12,  86243.00, 1338.71,   18.86,   -6.44, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.82, 7,    main,   -2.12,  86243.00, 1338.71,   18.86,   -6.44, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.84, 7,    main,   -4.24,  86266.00, 1336.53,   16.68,   -6.45, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   220.94, 7,    main,   -2.65,  86253.00, 1337.76,   17.91,   -6.45, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.04, 7,    main,   -4.24,  86279.00, 1335.30,   15.44,   -6.45, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.14, 7,    main,   -1.59,  86281.00, 1335.11,   15.25,   -6.45, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.14, 7,    main,   -1.59,  86281.00, 1335.11,   15.25,   -6.45, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.24, 7,    main,   -2.65,  86291.00, 1334.16,   14.31,   -6.44, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.34, 7,    main,   -3.18,  86297.00, 1333.59,   13.74,   -6.43, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.43, 7,    main,   -3.18,  86297.00, 1333.59,   13.74,   -6.43, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.43, 7,    main,   -3.18,  86297.00, 1333.59,   13.74,   -6.43, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.43, 7,    main,   -3.18,  86297.00, 1333.59,   13.74,   -6.43, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.43, 7,    main,   -3.18,  86297.00, 1333.59,   13.74,   -6.43, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.43, 7,    main,   -3.18,  86297.00, 1333.59,   13.74,   -6.43, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494105,-106.9155182,  1410.0, 2022,  6, 24, 15, 20, 57,     1165,     1165, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 23, 26,  0,  0, 28,  0,  0,  0,  0, 18, 24, 31, 34,  0,  0, 33,  0, 29, 26,  0,  0,  0, 28,  0,  0,  0,  0,  0, 31,  0,  0
+6, 5115, 1,VA3NPN,   221.44, 7,    main,   -1.59,  86306.00, 1332.74,   12.88,   -6.41, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.46, 7,    main,   -1.59,  86306.00, 1332.74,   12.88,   -6.41, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.54, 7,    main,   -2.12,  86312.00, 1332.17,   12.31,   -6.39, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.64, 7,    main,   -0.00,  86318.00, 1331.60,   11.75,   -6.36, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.74, 7,    main,   -2.65,  86339.00, 1329.61,    9.76,   -6.32, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.78, 7,    main,   -2.65,  86339.00, 1329.61,    9.76,   -6.32, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.84, 7,    main,   -1.06,  86332.00, 1330.27,   10.42,   -6.29, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   221.94, 7,    main,   -2.65,  86330.00, 1330.46,   10.61,   -6.24, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.04, 7,    main,   -2.12,  86330.00, 1330.46,   10.61,   -6.17, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.10, 7,    main,   -2.12,  86330.00, 1330.46,   10.61,   -6.17, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.14, 7,    main,   -4.77,  86349.00, 1328.66,    8.81,   -6.09, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.24, 7,    main,   -0.53,  86363.00, 1327.34,    7.48,   -5.99, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.34, 7,    main,   -4.24,  86356.00, 1328.00,    8.14,   -5.87, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.42, 7,    main,   -4.24,  86356.00, 1328.00,    8.14,   -5.87, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.43, 7,    main,   -4.24,  86356.00, 1328.00,    8.14,   -5.87, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494454,-106.9155256,  1403.0, 2022,  6, 24, 15, 20, 58,     1169,     1169, 341,   1,   1.7,2147483647.0,2147483647.0,  0, 35, 26,  0,  0, 33,  0,  0,  0,  0, 33, 31, 26, 26,  0,  0, 28,  0, 28, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   222.44, 7,    main,   -2.65,  86377.00, 1326.01,    6.16,   -5.75, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.54, 7,    main,    7.95,  86377.00, 1326.01,    6.16,   -5.61, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.64, 7,    main,    2.65,  86393.00, 1324.50,    4.64,   -5.44, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.74, 7,    main,    1.06,  86395.00, 1324.31,    4.45,   -5.26, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.74, 7,    main,    1.06,  86395.00, 1324.31,    4.45,   -5.26, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.84, 7,    main,   -0.53,  86398.00, 1324.02,    4.17,   -5.07, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   222.94, 7,    main,    6.89,  86395.00, 1324.31,    4.45,   -4.86, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.04, 7,    main,    0.53,  86402.00, 1323.64,    3.79,   -4.64, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.06, 7,    main,    0.53,  86402.00, 1323.64,    3.79,   -4.64, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.14, 7,    main,   -1.06,  86410.00, 1322.89,    3.03,   -4.39, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.24, 7,    main,   -0.00,  86419.00, 1322.03,    2.18,   -4.15, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.34, 7,    main,    4.24,  86427.00, 1321.28,    1.42,   -3.90, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.38, 7,    main,    4.24,  86427.00, 1321.28,    1.42,   -3.90, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.43, 7,    main,    4.24,  86427.00, 1321.28,    1.42,   -3.90, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   223.43, 7,    main,    4.24,  86427.00, 1321.28,    1.42,   -3.90, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494759,-106.9155052,  1396.0, 2022,  6, 24, 15, 20, 59,     1172,     1172, 341,   0,   1.7,2147483647.0,2147483647.0,  0, 25, 35,  0,  0, 31,  0,  0,  0,  0, 27, 32, 26, 25,  0,  0, 36,  0, 30, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   223.44, 7,    main,    5.83,  86421.00, 1321.84,    1.99,   -3.63, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   223.54, 7,    main,    5.30,  86440.00, 1320.05,    0.19,   -3.35, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   223.64, 7,    main,   -3.18,  86441.00, 1319.95,    0.09,   -3.06, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   223.70, 7,    main,   -3.18,  86441.00, 1319.95,    0.09,   -3.06, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   223.74, 7,    main,  -24.91,  86439.00, 1320.14,    0.28,   -2.79, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   223.84, 7,    main,  -17.49,  86460.00, 1318.15,   -1.70,   -2.51, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   223.94, 7,    main,  -15.37,  86460.00, 1318.15,   -1.70,   -2.24, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.02, 7,    main,  -15.37,  86460.00, 1318.15,   -1.70,   -2.24, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.04, 7,    main,  -10.60,  86437.00, 1320.33,    0.47,   -1.97, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.14, 7,    main,   -5.83,  86443.00, 1319.76,   -0.09,   -1.72, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.24, 7,    main,   -7.42,  86440.00, 1320.05,    0.19,   -1.50, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.34, 7,    main,  -10.60,  86449.00, 1319.19,   -0.66,   -1.29, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.34, 7,    main,  -10.60,  86449.00, 1319.19,   -0.66,   -1.29, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494914,-106.9154735,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 31, 26,  0,  0, 26,  0,  0,  0,  0, 31, 27, 27, 31,  0,  0, 33,  0, 25, 31,  0,  0,  0, 25,  0,  0,  0,  0,  0, 27,  0,  0
+6, 5115, 1,VA3NPN,   224.44, 7,    main,  -10.60,  86461.00, 1318.06,   -1.80,   -1.10, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   224.44, 7,    main,  -10.60,  86461.00, 1318.06,   -1.80,   -1.10, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   224.44, 7,    main,  -10.60,  86461.00, 1318.06,   -1.80,   -1.10, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   224.66, 7,    main,  -10.07,  86443.00, 1319.76,   -0.09,   -0.78, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   224.74, 7,    main,  -10.60,  86454.00, 1318.72,   -1.14,   -0.64, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   224.84, 7,    main,  -10.07,  86459.00, 1318.25,   -1.61,   -0.52, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   224.94, 7,    main,  -10.60,  86470.00, 1317.21,   -2.65,   -0.42, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   224.98, 7,    main,  -10.60,  86470.00, 1317.21,   -2.65,   -0.42, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   225.04, 7,    main,  -10.07,  86456.00, 1318.53,   -1.33,   -0.34, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   225.14, 7,    main,  -10.60,  86431.00, 1320.90,    1.04,   -0.28, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   225.24, 7,    main,  -10.07,  86461.00, 1318.06,   -1.80,   -0.26, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   225.30, 7,    main,  -10.07,  86461.00, 1318.06,   -1.80,   -0.26, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   225.34, 7,    main,  -10.07,  86465.00, 1317.68,   -2.18,   -0.23, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 5115, 1,VA3NPN,   225.43, 7,    main,  -10.07,  86465.00, 1317.68,   -2.18,   -0.23, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494979,-106.9154600,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 32, 28,  0,  0, 32,  0,  0,  0,  0, 31, 35, 26, 30,  0,  0, 32,  0, 32, 22,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
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+6, 5115, 1,VA3NPN,   225.44, 7,    main,  -10.60,  86446.00, 1319.48,   -0.38,   -0.20, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494992,-106.9154636,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 32,  0,  0,  0,  0, 32, 32, 23, 22,  0,  0, 33,  0, 33, 18,  0,  0,  0, 30,  0,  0,  0,  0,  0, 21,  0,  0
+6, 5115, 1,VA3NPN,   225.54, 7,    main,  -10.60,  86438.00, 1320.23,    0.38,   -0.18, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494992,-106.9154636,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 32,  0,  0,  0,  0, 32, 32, 23, 22,  0,  0, 33,  0, 33, 18,  0,  0,  0, 30,  0,  0,  0,  0,  0, 21,  0,  0
+6, 5115, 1,VA3NPN,   225.62, 7,    main,  -10.60,  86438.00, 1320.23,    0.38,   -0.18, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494992,-106.9154636,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 32,  0,  0,  0,  0, 32, 32, 23, 22,  0,  0, 33,  0, 33, 18,  0,  0,  0, 30,  0,  0,  0,  0,  0, 21,  0,  0
+6, 5115, 1,VA3NPN,   225.64, 7,    main,  -10.07,  86445.00, 1319.57,   -0.28,   -0.17, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494992,-106.9154636,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 32,  0,  0,  0,  0, 32, 32, 23, 22,  0,  0, 33,  0, 33, 18,  0,  0,  0, 30,  0,  0,  0,  0,  0, 21,  0,  0
+6, 5115, 1,VA3NPN,   225.74, 7,    main,  -10.60,  86455.00, 1318.63,   -1.23,   -0.15, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494992,-106.9154636,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 32,  0,  0,  0,  0, 32, 32, 23, 22,  0,  0, 33,  0, 33, 18,  0,  0,  0, 30,  0,  0,  0,  0,  0, 21,  0,  0
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+6, 5115, 1,VA3NPN,   227.74, 7,    main,  -10.60,  86441.00, 1319.95,    0.09,    0.09, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494999,-106.9154598,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 18, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 13,  0,  0
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+6, 5115, 1,VA3NPN,   228.24, 7,    main,  -10.07,  86438.00, 1320.23,    0.38,   -0.07, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494999,-106.9154598,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 18, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 13,  0,  0
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+6, 5115, 1,VA3NPN,   228.64, 7,    main,  -10.60,  86448.00, 1319.29,   -0.57,   -0.09, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   228.74, 7,    main,  -10.07,  86471.00, 1317.11,   -2.75,   -0.07, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   228.82, 7,    main,  -10.07,  86471.00, 1317.11,   -2.75,   -0.07, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   228.84, 7,    main,  -10.07,  86452.00, 1318.91,   -0.95,   -0.05, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   228.94, 7,    main,  -10.60,  86465.00, 1317.68,   -2.18,   -0.03, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   229.04, 7,    main,  -10.07,  86450.00, 1319.10,   -0.76,    0.01, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   229.14, 7,    main,  -10.60,  86442.00, 1319.86,    0.00,    0.03, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
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+6, 5115, 1,VA3NPN,   229.24, 7,    main,  -10.07,  86467.00, 1317.49,   -2.37,    0.05, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   229.34, 7,    main,  -10.60,  86453.00, 1318.81,   -1.04,    0.10, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
+6, 5115, 1,VA3NPN,   229.43, 7,    main,  -10.60,  86453.00, 1318.81,   -1.04,    0.10, 31.6, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494997,-106.9154584,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 16, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0, 11,  0,  0
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+6, 5115, 1,VA3NPN,   229.78, 7,    main,  -10.60,  86444.00, 1319.67,   -0.19,    0.21, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494977,-106.9154585,  1387.0, 2022,  6, 24, 15, 21,  6,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 32,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   230.04, 7,    main,  -10.60,  86426.00, 1321.37,    1.51,    0.24, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494977,-106.9154585,  1387.0, 2022,  6, 24, 15, 21,  6,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 32,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   230.14, 7,    main,  -10.60,  86450.00, 1319.10,   -0.76,    0.23, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494977,-106.9154585,  1387.0, 2022,  6, 24, 15, 21,  6,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 32,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   230.34, 7,    main,  -10.60,  86449.00, 1319.19,   -0.66,    0.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494977,-106.9154585,  1387.0, 2022,  6, 24, 15, 21,  6,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 32,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   230.42, 7,    main,  -10.60,  86449.00, 1319.19,   -0.66,    0.22, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494977,-106.9154585,  1387.0, 2022,  6, 24, 15, 21,  6,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 32,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   230.43, 7,    main,  -10.60,  86449.00, 1319.19,   -0.66,    0.22, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494977,-106.9154585,  1387.0, 2022,  6, 24, 15, 21,  6,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 32,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   230.54, 7,    main,  -10.07,  86453.00, 1318.81,   -1.04,    0.18, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
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+6, 5115, 1,VA3NPN,   230.74, 7,    main,  -10.60,  86439.00, 1320.14,    0.28,    0.10, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
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+6, 5115, 1,VA3NPN,   231.04, 7,    main,  -10.07,  86427.00, 1321.28,    1.42,    0.00, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
+6, 5115, 1,VA3NPN,   231.06, 7,    main,  -10.07,  86427.00, 1321.28,    1.42,    0.00, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
+6, 5115, 1,VA3NPN,   231.14, 7,    main,  -10.07,  86455.00, 1318.63,   -1.23,   -0.02, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
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+6, 5115, 1,VA3NPN,   231.34, 7,    main,  -10.60,  86432.00, 1320.80,    0.95,   -0.09, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
+6, 5115, 1,VA3NPN,   231.38, 7,    main,  -10.60,  86432.00, 1320.80,    0.95,   -0.09, 31.7, 0.00, 0.01, 3.86, 1, 1,  9,  32.9494975,-106.9154591,  1387.0, 2022,  6, 24, 15, 21,  7,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  9,  0,  0
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+6, 5115, 1,VA3NPN,   233.04, 7,    main,  -10.60,  86452.00, 1318.91,   -0.95,   -0.21, 31.6, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494956,-106.9154566,  1387.0, 2022,  6, 24, 15, 21,  9,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 22,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   233.14, 7,    main,  -10.07,  86433.00, 1320.71,    0.85,   -0.23, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494956,-106.9154566,  1387.0, 2022,  6, 24, 15, 21,  9,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 22,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   233.34, 7,    main,  -10.60,  86465.00, 1317.68,   -2.18,   -0.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494956,-106.9154566,  1387.0, 2022,  6, 24, 15, 21,  9,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 22,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   233.42, 7,    main,  -10.60,  86465.00, 1317.68,   -2.18,   -0.22, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494956,-106.9154566,  1387.0, 2022,  6, 24, 15, 21,  9,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 22,  0,  0, 34,  0, 34,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   234.26, 7,    main,  -10.60,  86445.00, 1319.57,   -0.28,    0.03, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494955,-106.9154556,  1387.0, 2022,  6, 24, 15, 21, 10,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   234.34, 7,    main,  -10.60,  86464.00, 1317.77,   -2.08,    0.10, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494955,-106.9154556,  1387.0, 2022,  6, 24, 15, 21, 10,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   234.43, 7,    main,  -10.60,  86464.00, 1317.77,   -2.08,    0.10, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494955,-106.9154556,  1387.0, 2022,  6, 24, 15, 21, 10,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 31, 15, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   234.84, 7,    main,  -10.07,  86456.00, 1318.53,   -1.33,    0.49, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494951,-106.9154545,  1387.0, 2022,  6, 24, 15, 21, 11,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 15, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  8,  0,  0
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+6, 5115, 1,VA3NPN,   236.74, 7,    main,  -10.60,  86462.00, 1317.96,   -1.89,    0.31, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   236.82, 7,    main,  -10.60,  86462.00, 1317.96,   -1.89,    0.31, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   236.84, 7,    main,  -10.60,  86458.00, 1318.34,   -1.51,    0.38, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   236.94, 7,    main,  -10.07,  86457.00, 1318.44,   -1.42,    0.45, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.04, 7,    main,  -10.60,  86448.00, 1319.29,   -0.57,    0.53, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.14, 7,    main,  -10.07,  86464.00, 1317.77,   -2.08,    0.60, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.14, 7,    main,  -10.07,  86464.00, 1317.77,   -2.08,    0.60, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.24, 7,    main,  -10.60,  86445.00, 1319.57,   -0.28,    0.67, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.34, 7,    main,  -10.07,  86446.00, 1319.48,   -0.38,    0.73, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.43, 7,    main,  -10.07,  86446.00, 1319.48,   -0.38,    0.73, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.43, 7,    main,  -10.07,  86446.00, 1319.48,   -0.38,    0.73, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.43, 7,    main,  -10.07,  86446.00, 1319.48,   -0.38,    0.73, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.43, 7,    main,  -10.07,  86446.00, 1319.48,   -0.38,    0.73, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.43, 7,    main,  -10.07,  86446.00, 1319.48,   -0.38,    0.73, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494940,-106.9154512,  1387.0, 2022,  6, 24, 15, 21, 13,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 31, 30, 13, 20,  0,  0, 33,  0, 33,  0,  0,  0,  0, 27,  0,  0,  0,  0,  0,  8,  0,  0
+6, 5115, 1,VA3NPN,   237.44, 7,    main,  -10.60,  86448.00, 1319.29,   -0.57,    0.77, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.46, 7,    main,  -10.60,  86448.00, 1319.29,   -0.57,    0.77, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.54, 7,    main,  -10.07,  86451.00, 1319.00,   -0.85,    0.79, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.64, 7,    main,  -10.07,  86427.00, 1321.28,    1.42,    0.81, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.74, 7,    main,  -10.60,  86459.00, 1318.25,   -1.61,    0.81, 31.7, 0.00, 0.00, 3.86, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.78, 7,    main,  -10.60,  86459.00, 1318.25,   -1.61,    0.81, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.84, 7,    main,  -10.07,  86439.00, 1320.14,    0.28,    0.80, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.94, 8,  landed,  -10.07,  86427.00, 1321.28,    1.42,    0.80, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 5115, 1,VA3NPN,   237.94, 8,  landed,  -10.07,  86427.00, 1321.28,    1.42,    0.80, 31.7, 0.00, 0.00, 3.87, 1, 1,  9,  32.9494937,-106.9154488,  1387.0, 2022,  6, 24, 15, 21, 14,     1172,     1172, 341,  -0,   1.7,2147483647.0,2147483647.0,  0, 33, 31,  0,  0, 33,  0,  0,  0,  0, 32, 30, 12, 21,  0,  0, 33,  0, 33,  0,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
diff --git a/data/prometheus/2022-06-24-serial-6583-flight-0003-TeleMega.csv b/data/prometheus/2022-06-24-serial-6583-flight-0003-TeleMega.csv
new file mode 100644
index 000000000..c10423dd7
--- /dev/null
+++ b/data/prometheus/2022-06-24-serial-6583-flight-0003-TeleMega.csv
@@ -0,0 +1,6235 @@
+#version,serial,flight,call,time,state,state_name,acceleration,pressure,altitude,height,speed,temperature,drogue_voltage,main_voltage,battery_voltage,accel_x,accel_y,accel_z,gyro_roll,gyro_pitch,gyro_yaw,mag_x,mag_y,mag_z,tilt,pyro,igniter_a,igniter_b,igniter_c,igniter_d,connected,locked,nsat,latitude,longitude,altitude,year,month,day,hour,minute,second,pad_dist,pad_range,pad_az,pad_el,pdop,hdop,vdop,sat01,sat02,sat03,sat04,sat05,sat06,sat07,sat08,sat09,sat10,sat11,sat12,sat13,sat14,sat15,sat16,sat17,sat18,sat19,sat20,sat21,sat22,sat23,sat24,sat25,sat26,sat27,sat28,sat29,sat30,sat31,sat32
+6, 6583, 3,VE3LIC,    -0.30, 3,   boost,    1.47,  86334.00, 1330.09,    0.28,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,   0.00,  -0.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.29, 3,   boost,   -1.47,  86336.00, 1329.90,    0.09,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.28, 3,   boost,   -0.00,  86346.00, 1328.95,   -0.85,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.27, 3,   boost,   -0.98,  86330.00, 1330.46,    0.66,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.26, 3,   boost,    0.98,  86347.00, 1328.85,   -0.95,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.25, 3,   boost,   -1.96,  86342.00, 1329.33,   -0.47,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.24, 3,   boost,   -0.98,  86337.00, 1329.80,    0.00,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.23, 3,   boost,   -0.49,  86334.00, 1330.09,    0.28,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.22, 3,   boost,   -1.47,  86340.00, 1329.52,   -0.28,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.21, 3,   boost,   -0.49,  86333.00, 1330.18,    0.38,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.20, 3,   boost,   -0.98,  86338.00, 1329.71,   -0.09,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.19, 3,   boost,    1.96,  86342.00, 1329.33,   -0.47,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.18, 3,   boost,   -0.00,  86345.00, 1329.04,   -0.76,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.17, 3,   boost,    0.49,  86335.00, 1329.99,    0.19,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.16, 3,   boost,    2.94,  86332.00, 1330.27,    0.47,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.15, 3,   boost,   -2.94,  86345.00, 1329.04,   -0.76,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.14, 3,   boost,    0.49,  86343.00, 1329.23,   -0.57,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.13, 3,   boost,   -0.49,  86331.00, 1330.37,    0.57,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.12, 3,   boost,   -1.47,  86346.00, 1328.95,   -0.85,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.11, 3,   boost,    2.94,  86334.00, 1330.09,    0.28,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.10, 3,   boost,   38.25,  86485.00, 1315.79,  -14.02,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.09, 3,   boost,   69.63,  86381.00, 1325.63,   -4.17,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.08, 3,   boost,   87.28,  86345.00, 1329.04,   -0.76,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.07, 3,   boost,   89.73,  86320.00, 1331.41,    1.61,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.06, 3,   boost,   89.73,  86333.00, 1330.18,    0.38,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.05, 3,   boost,  109.34,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.04, 3,   boost,   78.94,  86296.00, 1333.69,    3.89,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.03, 3,   boost,   79.92,  86300.00, 1333.31,    3.51,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.02, 3,   boost,   76.49,  86287.00, 1334.54,    4.74,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    -0.01, 3,   boost,   78.94,  86307.00, 1332.64,    2.84,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.00, 3,   boost,   76.98,  86319.00, 1331.51,    1.71,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.01, 3,   boost,   81.40,  86321.00, 1331.32,    1.52,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.01, 3,   boost,   81.40,  86321.00, 1331.32,    1.52,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.02, 3,   boost,   89.24,  86327.00, 1330.75,    0.95,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.02, 3,   boost,   89.24,  86327.00, 1330.75,    0.95,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.03, 3,   boost,   77.47,  86320.00, 1331.41,    1.61,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.04, 3,   boost,   79.43,  86324.00, 1331.03,    1.23,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.05, 3,   boost,   80.41,  86331.00, 1330.37,    0.57,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.06, 3,   boost,   80.90,  86312.00, 1332.17,    2.37,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.07, 3,   boost,   80.41,  86329.00, 1330.56,    0.76,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.08, 3,   boost,   76.98,  86327.00, 1330.75,    0.95,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.09, 3,   boost,   79.92,  86318.00, 1331.60,    1.80,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.10, 3,   boost,   78.45,  86347.00, 1328.85,   -0.95,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.11, 3,   boost,   75.02,  86311.00, 1332.27,    2.46,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.12, 3,   boost,   80.90,  86339.00, 1329.61,   -0.19,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.13, 3,   boost,   74.53,  86332.00, 1330.27,    0.47,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.14, 3,   boost,   74.53,  86300.00, 1333.31,    3.51,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.15, 3,   boost,   77.96,  86329.00, 1330.56,    0.76,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.16, 3,   boost,   79.43,  86310.00, 1332.36,    2.56,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.17, 3,   boost,   76.49,  86320.00, 1331.41,    1.61,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.18, 3,   boost,   75.02,  86338.00, 1329.71,   -0.09,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.19, 3,   boost,   77.96,  86298.00, 1333.50,    3.70,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.20, 3,   boost,   76.00,  86283.00, 1334.92,    5.12,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.21, 3,   boost,   81.89,  86308.00, 1332.55,    2.75,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.22, 3,   boost,   75.02,  86312.00, 1332.17,    2.37,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.23, 3,   boost,   77.96,  86288.00, 1334.45,    4.64,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.24, 3,   boost,   77.96,  86315.00, 1331.89,    2.08,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.25, 3,   boost,   77.47,  86303.00, 1333.02,    3.22,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.26, 3,   boost,   77.47,  86308.00, 1332.55,    2.75,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.27, 3,   boost,   78.94,  86288.00, 1334.45,    4.64,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.28, 3,   boost,   77.47,  86282.00, 1335.01,    5.21,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.29, 3,   boost,   76.49,  86309.00, 1332.45,    2.65,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.30, 3,   boost,   76.98,  86288.00, 1334.45,    4.64,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395109,-106.9114318,  1394.0, 2022,  6, 24, 15, 17, 16,        0,        0,   0,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.31, 3,   boost,   77.47,  86279.00, 1335.30,    5.50,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.31, 3,   boost,   77.47,  86279.00, 1335.30,    5.50,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.31, 3,   boost,   77.47,  86279.00, 1335.30,    5.50,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.32, 3,   boost,   78.94,  86275.00, 1335.68,    5.88,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.33, 3,   boost,   78.45,  86283.00, 1334.92,    5.12,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.34, 3,   boost,   75.02,  86267.00, 1336.44,    6.64,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.34, 3,   boost,   75.02,  86267.00, 1336.44,    6.64,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.35, 3,   boost,   81.40,  86265.00, 1336.63,    6.83,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.36, 3,   boost,   78.45,  86271.00, 1336.06,    6.26,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.37, 3,   boost,   77.47,  86271.00, 1336.06,    6.26,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.38, 3,   boost,   76.00,  86277.00, 1335.49,    5.69,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.39, 3,   boost,   79.92,  86256.00, 1337.48,    7.68,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.40, 3,   boost,   79.92,  86260.00, 1337.10,    7.30,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.41, 3,   boost,   78.45,  86261.00, 1337.01,    7.20,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.42, 3,   boost,   78.94,  86252.00, 1337.86,    8.06,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.43, 3,   boost,   78.94,  86251.00, 1337.95,    8.15,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.44, 3,   boost,   78.94,  86252.00, 1337.86,    8.06,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.45, 3,   boost,   76.49,  86258.00, 1337.29,    7.49,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.46, 3,   boost,   77.47,  86238.00, 1339.19,    9.39,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.47, 3,   boost,   78.94,  86231.00, 1339.85,   10.05,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.48, 3,   boost,   76.98,  86246.00, 1338.43,    8.63,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.49, 3,   boost,   78.94,  86234.00, 1339.57,    9.77,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.50, 3,   boost,   79.43,  86229.00, 1340.04,   10.24,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.51, 3,   boost,   76.49,  86234.00, 1339.57,    9.77,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.52, 3,   boost,   79.43,  86217.00, 1341.18,   11.38,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.53, 3,   boost,   85.81,  86229.00, 1340.04,   10.24,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.54, 3,   boost,   80.41,  86216.00, 1341.27,   11.47,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.55, 3,   boost,   77.47,  86201.00, 1342.70,   12.90,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.56, 3,   boost,   80.90,  86224.00, 1340.51,   10.71,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.57, 3,   boost,   78.94,  86213.00, 1341.56,   11.76,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.58, 3,   boost,   80.90,  86204.00, 1342.41,   12.61,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.59, 3,   boost,   77.47,  86216.00, 1341.27,   11.47,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.60, 3,   boost,   78.45,  86204.00, 1342.41,   12.61,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.61, 3,   boost,   80.41,  86194.00, 1343.36,   13.56,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.62, 3,   boost,   80.41,  86183.00, 1344.40,   14.60,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.63, 3,   boost,   79.43,  86183.00, 1344.40,   14.60,     NaN, 33.4, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.64, 3,   boost,   78.45,  86196.00, 1343.17,   13.37,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.65, 3,   boost,   78.94,  86173.00, 1345.35,   15.55,     NaN, 33.5, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.66, 3,   boost,   77.47,  86186.00, 1344.12,   14.32,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.66, 3,   boost,   77.47,  86186.00, 1344.12,   14.32,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.67, 3,   boost,   76.98,  86172.00, 1345.45,   15.65,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.68, 3,   boost,   77.96,  86165.00, 1346.11,   16.31,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.69, 3,   boost,   81.40,  86167.00, 1345.92,   16.12,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.70, 3,   boost,   81.40,  86168.00, 1345.83,   16.03,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.71, 3,   boost,   80.90,  86150.00, 1347.54,   17.74,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.72, 3,   boost,   79.92,  86147.00, 1347.82,   18.02,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.73, 3,   boost,   80.41,  86143.00, 1348.20,   18.40,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.74, 3,   boost,   81.40,  86148.00, 1347.73,   17.93,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.75, 3,   boost,   79.43,  86143.00, 1348.20,   18.40,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.76, 3,   boost,   78.45,  86122.00, 1350.20,   20.39,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.77, 3,   boost,   78.45,  86125.00, 1349.91,   20.11,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.78, 3,   boost,   77.47,  86131.00, 1349.34,   19.54,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.79, 3,   boost,   78.94,  86106.00, 1351.71,   21.91,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.80, 3,   boost,   82.87,  86107.00, 1351.62,   21.82,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.81, 3,   boost,   78.94,  86092.00, 1353.04,   23.24,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.82, 3,   boost,   79.92,  86108.00, 1351.52,   21.72,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.83, 3,   boost,   77.47,  86094.00, 1352.85,   23.05,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.84, 3,   boost,   76.00,  86090.00, 1353.23,   23.43,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.85, 3,   boost,   79.43,  86115.00, 1350.86,   21.06,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.86, 3,   boost,   80.41,  86094.00, 1352.85,   23.05,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.87, 3,   boost,   80.90,  86100.00, 1352.28,   22.48,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.88, 3,   boost,   80.41,  86084.00, 1353.80,   24.00,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.89, 3,   boost,   82.87,  86064.00, 1355.70,   25.90,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.90, 3,   boost,   79.43,  86084.00, 1353.80,   24.00,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.91, 3,   boost,   82.38,  86063.00, 1355.80,   26.00,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.92, 3,   boost,   79.43,  86063.00, 1355.80,   26.00,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.93, 3,   boost,   80.41,  86058.00, 1356.27,   26.47,     NaN, 33.4, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.94, 3,   boost,   82.38,  86056.00, 1356.46,   26.66,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.95, 3,   boost,   81.89,  86054.00, 1356.65,   26.85,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.96, 3,   boost,   83.36,  86043.00, 1357.70,   27.90,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.97, 3,   boost,   79.92,  86047.00, 1357.32,   27.52,     NaN, 33.5, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.98, 3,   boost,   77.47,  86021.00, 1359.79,   29.99,     NaN, 33.4, 4.00, 3.98, 4.00,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.98, 3,   boost,   77.47,  86021.00, 1359.79,   29.99,     NaN, 33.4, 4.00, 3.98, 4.00,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     0.99, 3,   boost,   83.36,  86033.00, 1358.65,   28.85,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.00, 3,   boost,   80.90,  86031.00, 1358.84,   29.04,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.01, 3,   boost,   80.90,  86018.00, 1360.08,   30.27,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.02, 3,   boost,   82.38,  86021.00, 1359.79,   29.99,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.03, 3,   boost,   80.41,  86014.00, 1360.46,   30.65,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.04, 3,   boost,   80.41,  86012.00, 1360.65,   30.84,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.05, 3,   boost,   81.89,  86007.00, 1361.12,   31.32,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.06, 3,   boost,   79.92,  86007.00, 1361.12,   31.32,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.07, 3,   boost,   80.41,  86009.00, 1360.93,   31.13,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.08, 3,   boost,   81.89,  85992.00, 1362.55,   32.75,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.09, 3,   boost,   81.40,  85985.00, 1363.21,   33.41,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.10, 3,   boost,   79.92,  85988.00, 1362.93,   33.13,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.11, 3,   boost,   81.89,  85990.00, 1362.74,   32.94,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.12, 3,   boost,   83.85,  85951.00, 1366.45,   36.64,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.13, 3,   boost,   81.40,  85961.00, 1365.49,   35.69,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.14, 3,   boost,   81.40,  85978.00, 1363.88,   34.08,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.15, 3,   boost,   80.41,  85953.00, 1366.26,   36.45,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.16, 3,   boost,   81.89,  85949.00, 1366.64,   36.83,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.17, 3,   boost,   81.89,  85927.00, 1368.73,   38.93,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.18, 3,   boost,   80.90,  85943.00, 1367.21,   37.41,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.19, 3,   boost,   83.36,  85922.00, 1369.20,   39.40,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.20, 3,   boost,   80.41,  85932.00, 1368.25,   38.45,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.21, 3,   boost,   78.45,  85922.00, 1369.20,   39.40,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.22, 3,   boost,   80.90,  85930.00, 1368.44,   38.64,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.23, 3,   boost,   78.45,  85897.00, 1371.58,   41.78,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.24, 3,   boost,   81.89,  85912.00, 1370.16,   40.35,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.25, 3,   boost,   81.89,  85913.00, 1370.06,   40.26,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.26, 3,   boost,   79.43,  85903.00, 1371.01,   41.21,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.27, 3,   boost,   82.38,  85891.00, 1372.15,   42.35,     NaN, 33.4, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.28, 3,   boost,   84.34,  85891.00, 1372.15,   42.35,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.29, 3,   boost,   81.40,  85889.00, 1372.34,   42.54,     NaN, 33.5, 4.00, 3.98, 4.00,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.30, 3,   boost,   82.87,  85905.00, 1370.82,   41.02,     NaN, 33.4, 4.00, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.30, 3,   boost,   82.87,  85905.00, 1370.82,   41.02,     NaN, 33.4, 4.00, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395110,-106.9114310,  1394.0, 2022,  6, 24, 15, 17, 17,        0,        0,  82,   0,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 32,  0,  0,  0,  0, 32, 36, 31, 27,  0,  0, 35,  0, 31, 29,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.31, 3,   boost,   82.38,  85877.00, 1373.49,   43.69,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.31, 3,   boost,   82.38,  85877.00, 1373.49,   43.69,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.31, 3,   boost,   82.38,  85877.00, 1373.49,   43.69,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.32, 3,   boost,   81.89,  85881.00, 1373.11,   43.30,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.33, 3,   boost,   82.87,  85869.00, 1374.25,   44.45,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.34, 3,   boost,   82.87,  85875.00, 1373.68,   43.88,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.35, 3,   boost,   79.92,  85843.00, 1376.72,   46.92,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.36, 3,   boost,   80.41,  85837.00, 1377.29,   47.49,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.37, 3,   boost,   80.90,  85841.00, 1376.91,   47.11,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.38, 3,   boost,   83.36,  85828.00, 1378.15,   48.35,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.39, 3,   boost,   84.34,  85842.00, 1376.82,   47.02,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.40, 3,   boost,   81.40,  85823.00, 1378.63,   48.83,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.41, 3,   boost,   78.94,  85810.00, 1379.86,   50.06,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.42, 3,   boost,   77.47,  85817.00, 1379.20,   49.40,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.43, 3,   boost,   82.38,  85806.00, 1380.25,   50.44,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.44, 3,   boost,   81.89,  85792.00, 1381.58,   51.78,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.45, 3,   boost,   80.90,  85773.00, 1383.39,   53.59,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.46, 3,   boost,   79.92,  85772.00, 1383.48,   53.68,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.47, 3,   boost,   84.34,  85777.00, 1383.01,   53.21,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.48, 3,   boost,   81.89,  85771.00, 1383.58,   53.78,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.49, 3,   boost,   77.96,  85747.00, 1385.87,   56.07,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.50, 3,   boost,   85.32,  85755.00, 1385.10,   55.30,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.51, 3,   boost,   79.92,  85743.00, 1386.25,   56.45,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.52, 3,   boost,   76.98,  85718.00, 1388.63,   58.83,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.53, 3,   boost,   78.45,  85722.00, 1388.25,   58.45,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.54, 3,   boost,   82.38,  85719.00, 1388.53,   58.73,     NaN, 33.5, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.55, 3,   boost,   79.92,  85721.00, 1388.34,   58.54,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.56, 3,   boost,   84.34,  85693.00, 1391.01,   61.21,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.57, 3,   boost,   79.92,  85697.00, 1390.63,   60.83,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.58, 3,   boost,   78.45,  85685.00, 1391.78,   61.97,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.59, 3,   boost,   81.40,  85689.00, 1391.39,   61.59,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.60, 3,   boost,   79.43,  85677.00, 1392.54,   62.74,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.61, 3,   boost,   81.89,  85673.00, 1392.92,   63.12,     NaN, 33.4, 4.00, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.62, 3,   boost,   83.36,  85679.00, 1392.35,   62.55,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.62, 3,   boost,   83.36,  85679.00, 1392.35,   62.55,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.63, 3,   boost,   81.40,  85654.00, 1394.73,   64.93,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.64, 3,   boost,   83.36,  85659.00, 1394.26,   64.45,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.65, 3,   boost,   77.47,  85673.00, 1392.92,   63.12,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.66, 3,   boost,   81.40,  85667.00, 1393.49,   63.69,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.67, 3,   boost,   79.92,  85659.00, 1394.26,   64.45,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.68, 3,   boost,   78.94,  85653.00, 1394.83,   65.03,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.69, 3,   boost,   80.90,  85659.00, 1394.26,   64.45,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.70, 3,   boost,   82.38,  85632.00, 1396.83,   67.03,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.71, 3,   boost,   80.90,  85626.00, 1397.40,   67.60,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.72, 3,   boost,   79.92,  85634.00, 1396.64,   66.84,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.73, 3,   boost,   80.90,  85626.00, 1397.40,   67.60,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.74, 3,   boost,   78.94,  85625.00, 1397.50,   67.70,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.75, 3,   boost,   82.38,  85610.00, 1398.93,   69.13,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.76, 3,   boost,   81.89,  85596.00, 1400.27,   70.46,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.77, 3,   boost,   77.96,  85607.00, 1399.22,   69.41,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.78, 3,   boost,   79.92,  85585.00, 1401.31,   71.51,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.79, 3,   boost,   80.41,  85567.00, 1403.03,   73.23,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.80, 3,   boost,   77.96,  85562.00, 1403.51,   73.71,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.81, 3,   boost,   81.89,  85576.00, 1402.17,   72.37,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.82, 3,   boost,   76.00,  85572.00, 1402.56,   72.75,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.83, 3,   boost,   81.40,  85561.00, 1403.61,   73.80,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.84, 3,   boost,   78.45,  85560.00, 1403.70,   73.90,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.85, 3,   boost,   77.96,  85571.00, 1402.65,   72.85,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.86, 3,   boost,   76.00,  85538.00, 1405.80,   76.00,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.87, 3,   boost,   77.47,  85534.00, 1406.18,   76.38,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.88, 3,   boost,   77.96,  85538.00, 1405.80,   76.00,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.89, 3,   boost,   78.45,  85541.00, 1405.51,   75.71,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.90, 3,   boost,   77.47,  85524.00, 1407.14,   77.34,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.91, 3,   boost,   77.96,  85515.00, 1408.00,   78.20,     NaN, 33.5, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.92, 3,   boost,   80.90,  85515.00, 1408.00,   78.20,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.93, 3,   boost,   80.41,  85514.00, 1408.09,   78.29,     NaN, 33.4, 4.00, 3.98, 4.00,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.94, 3,   boost,   77.96,  85523.00, 1407.23,   77.43,     NaN, 33.4, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.94, 3,   boost,   77.96,  85523.00, 1407.23,   77.43,     NaN, 33.4, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.95, 3,   boost,   78.45,  85513.00, 1408.19,   78.39,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.96, 3,   boost,   78.45,  85494.00, 1410.00,   80.20,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.97, 3,   boost,   76.98,  85478.00, 1411.53,   81.73,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.98, 3,   boost,   78.45,  85468.00, 1412.49,   82.69,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     1.99, 3,   boost,   75.51,  85468.00, 1412.49,   82.69,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.00, 3,   boost,   76.49,  85483.00, 1411.05,   81.25,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.01, 3,   boost,   77.96,  85471.00, 1412.20,   82.40,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.02, 3,   boost,   77.47,  85456.00, 1413.63,   83.83,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.03, 3,   boost,   77.47,  85475.00, 1411.82,   82.02,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.04, 3,   boost,   77.47,  85449.00, 1414.30,   84.50,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.05, 3,   boost,   80.90,  85436.00, 1415.54,   85.74,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.06, 3,   boost,   78.45,  85433.00, 1415.83,   86.03,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.07, 3,   boost,   75.51,  85414.00, 1417.65,   87.85,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.08, 3,   boost,   75.02,  85392.00, 1419.75,   89.95,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.09, 3,   boost,   78.45,  85389.00, 1420.04,   90.24,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.10, 3,   boost,   76.00,  85371.00, 1421.76,   91.96,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.11, 3,   boost,   76.00,  85351.00, 1423.67,   93.87,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.12, 3,   boost,   75.51,  85333.00, 1425.39,   95.59,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.13, 3,   boost,   77.47,  85343.00, 1424.44,   94.64,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.14, 3,   boost,   75.02,  85324.00, 1426.25,   96.45,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.15, 3,   boost,   75.02,  85305.00, 1428.07,   98.27,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.16, 3,   boost,   76.49,  85302.00, 1428.36,   98.56,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.17, 3,   boost,   75.51,  85293.00, 1429.22,   99.42,     NaN, 33.5, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.18, 3,   boost,   75.02,  85295.00, 1429.03,   99.23,     NaN, 33.5, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.19, 3,   boost,   74.04,  85268.00, 1431.61,  101.81,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.20, 3,   boost,   75.51,  85264.00, 1432.00,  102.20,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.21, 3,   boost,   74.04,  85263.00, 1432.09,  102.29,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.22, 3,   boost,   74.04,  85248.00, 1433.53,  103.73,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.23, 3,   boost,   76.98,  85241.00, 1434.20,  104.40,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.24, 3,   boost,   74.04,  85245.00, 1433.82,  104.01,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.25, 3,   boost,   73.55,  85233.00, 1434.96,  105.16,     NaN, 33.4, 4.00, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.26, 3,   boost,   74.53,  85224.00, 1435.83,  106.03,     NaN, 33.4, 3.99, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.26, 3,   boost,   74.53,  85224.00, 1435.83,  106.03,     NaN, 33.4, 3.99, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.27, 3,   boost,   78.45,  85211.00, 1437.07,  107.27,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.28, 3,   boost,   75.51,  85210.00, 1437.17,  107.37,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.29, 3,   boost,   79.43,  85190.00, 1439.08,  109.28,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.30, 3,   boost,   71.59,  85194.00, 1438.70,  108.90,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9395787,-106.9114445,  1414.0, 2022,  6, 24, 15, 17, 18,        8,       21, 351,  69,   1.4,   0.8,   1.1,  0, 21, 33,  0,  0, 18,  0,  0,  0,  0, 24, 28, 27, 32,  0,  0, 34,  0, 20, 32,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,     2.31, 3,   boost,   75.02,  85178.00, 1440.23,  110.43,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.31, 3,   boost,   75.02,  85178.00, 1440.23,  110.43,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.31, 3,   boost,   75.02,  85178.00, 1440.23,  110.43,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.32, 3,   boost,   73.55,  85173.00, 1440.71,  110.91,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.33, 3,   boost,   75.51,  85168.00, 1441.19,  111.39,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.34, 3,   boost,   74.04,  85176.00, 1440.42,  110.62,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.35, 3,   boost,   71.10,  85150.00, 1442.92,  113.11,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.36, 3,   boost,   75.51,  85130.00, 1444.83,  115.03,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.37, 3,   boost,   75.02,  85155.00, 1442.44,  112.64,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.38, 3,   boost,   73.55,  85117.00, 1446.08,  116.28,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.39, 3,   boost,   72.08,  85126.00, 1445.22,  115.41,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.40, 3,   boost,   75.02,  85114.00, 1446.37,  116.56,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.41, 3,   boost,   72.08,  85105.00, 1447.23,  117.43,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.42, 3,   boost,   72.08,  85112.00, 1446.56,  116.76,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.43, 3,   boost,   75.02,  85116.00, 1446.17,  116.37,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.44, 3,   boost,   75.51,  85099.00, 1447.80,  118.00,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.45, 3,   boost,   75.51,  85068.00, 1450.78,  120.98,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.46, 3,   boost,   74.53,  85076.00, 1450.01,  120.21,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.47, 3,   boost,   73.06,  85067.00, 1450.87,  121.07,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.48, 3,   boost,   70.61,  85053.00, 1452.22,  122.41,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.49, 3,   boost,   71.59,  85022.00, 1455.19,  125.39,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.50, 3,   boost,   71.59,  85020.00, 1455.38,  125.58,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.51, 3,   boost,   75.51,  85018.00, 1455.57,  125.77,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.52, 3,   boost,   72.57,  85000.00, 1457.30,  127.50,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.53, 3,   boost,   72.57,  84977.00, 1459.51,  129.71,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.54, 3,   boost,   69.63,  84968.00, 1460.37,  130.57,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.55, 3,   boost,   73.06,  84976.00, 1459.60,  129.80,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.56, 3,   boost,   72.57,  84959.00, 1461.24,  131.43,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.57, 3,   boost,   73.06,  84946.00, 1462.48,  132.68,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.58, 3,   boost,   69.63,  84933.00, 1463.73,  133.93,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.58, 3,   boost,   69.63,  84933.00, 1463.73,  133.93,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.01,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.59, 3,   boost,   72.57,  84916.00, 1465.36,  135.56,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.60, 3,   boost,   71.10,  84890.00, 1467.86,  138.06,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.61, 3,   boost,   73.55,  84904.00, 1466.52,  136.72,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.62, 3,   boost,   72.57,  84885.00, 1468.34,  138.54,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.63, 3,   boost,   73.06,  84869.00, 1469.88,  140.08,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.64, 3,   boost,   69.14,  84861.00, 1470.65,  140.85,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.65, 3,   boost,   69.63,  84860.00, 1470.74,  140.94,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.66, 3,   boost,   69.14,  84848.00, 1471.90,  142.10,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.67, 3,   boost,   73.06,  84801.00, 1476.42,  146.61,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.68, 3,   boost,   70.12,  84836.00, 1473.05,  143.25,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.69, 3,   boost,   72.08,  84807.00, 1475.84,  146.04,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.70, 3,   boost,   66.69,  84820.00, 1474.59,  144.79,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.71, 3,   boost,   70.61,  84787.00, 1477.76,  147.96,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.72, 3,   boost,   69.63,  84793.00, 1477.19,  147.38,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.73, 3,   boost,   73.55,  84780.00, 1478.44,  148.63,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.74, 3,   boost,   73.55,  84753.00, 1481.03,  151.23,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.75, 3,   boost,   71.10,  84768.00, 1479.59,  149.79,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.76, 3,   boost,   69.14,  84778.00, 1478.63,  148.83,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.77, 3,   boost,   69.63,  84754.00, 1480.94,  151.13,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.78, 3,   boost,   73.06,  84763.00, 1480.07,  150.27,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.79, 3,   boost,   67.18,  84730.00, 1483.24,  153.44,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.80, 3,   boost,   67.67,  84726.00, 1483.63,  153.83,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.81, 3,   boost,   69.14,  84721.00, 1484.11,  154.31,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.82, 3,   boost,   70.61,  84684.00, 1487.67,  157.87,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.83, 3,   boost,   69.63,  84697.00, 1486.42,  156.62,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.84, 3,   boost,   67.18,  84679.00, 1488.15,  158.35,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.85, 3,   boost,   67.67,  84679.00, 1488.15,  158.35,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.86, 3,   boost,   67.67,  84672.00, 1488.83,  159.03,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.87, 3,   boost,   69.63,  84639.00, 1492.00,  162.20,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.88, 3,   boost,   69.14,  84627.00, 1493.16,  163.36,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.89, 3,   boost,   68.65,  84596.00, 1496.15,  166.34,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.90, 3,   boost,   68.65,  84615.00, 1494.32,  164.51,     NaN, 33.5, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.90, 3,   boost,   68.65,  84615.00, 1494.32,  164.51,     NaN, 33.5, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.91, 3,   boost,   69.14,  84589.00, 1496.82,  167.02,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.92, 3,   boost,   63.25,  84551.00, 1500.48,  170.68,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.93, 3,   boost,   66.19,  84560.00, 1499.61,  169.81,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.94, 3,   boost,   65.70,  84550.00, 1500.58,  170.78,     NaN, 33.5, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.95, 3,   boost,   65.21,  84547.00, 1500.87,  171.07,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.96, 3,   boost,   66.69,  84533.00, 1502.22,  172.42,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.97, 3,   boost,   68.16,  84525.00, 1502.99,  173.19,     NaN, 33.5, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.98, 3,   boost,   65.70,  84511.00, 1504.34,  174.54,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     2.99, 3,   boost,   68.65,  84466.00, 1508.68,  178.88,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.00, 3,   boost,   69.14,  84474.00, 1507.91,  178.11,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.01, 3,   boost,   68.16,  84464.00, 1508.87,  179.07,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.02, 3,   boost,   65.70,  84444.00, 1510.80,  181.00,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.03, 3,   boost,   68.65,  84438.00, 1511.38,  181.58,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.04, 3,   boost,   64.72,  84405.00, 1514.56,  184.76,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.05, 3,   boost,   65.70,  84401.00, 1514.95,  185.15,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.06, 3,   boost,   68.65,  84388.00, 1516.20,  186.40,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.07, 3,   boost,   67.18,  84379.00, 1517.07,  187.27,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.08, 3,   boost,   62.27,  84354.00, 1519.49,  189.69,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.09, 3,   boost,   69.14,  84364.00, 1518.52,  188.72,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.10, 3,   boost,   67.18,  84353.00, 1519.58,  189.78,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.11, 3,   boost,   65.21,  84341.00, 1520.74,  190.94,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.12, 3,   boost,   64.72,  84331.00, 1521.71,  191.91,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.13, 3,   boost,   67.67,  84318.00, 1522.96,  193.16,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.14, 3,   boost,   65.21,  84335.00, 1521.32,  191.52,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.15, 3,   boost,   64.23,  84311.00, 1523.64,  193.84,     NaN, 33.5, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.16, 3,   boost,   67.18,  84302.00, 1524.51,  194.71,     NaN, 33.5, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.17, 3,   boost,   66.19,  84283.00, 1526.35,  196.54,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.18, 3,   boost,   67.18,  84291.00, 1525.57,  195.77,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.19, 3,   boost,   63.25,  84255.00, 1529.05,  199.25,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.20, 3,   boost,   64.23,  84227.00, 1531.76,  201.96,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.21, 3,   boost,   63.74,  84233.00, 1531.18,  201.38,     NaN, 33.4, 3.99, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.22, 3,   boost,   66.69,  84227.00, 1531.76,  201.96,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.22, 3,   boost,   66.69,  84227.00, 1531.76,  201.96,     NaN, 33.4, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  63.97,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.23, 3,   boost,   63.25,  84211.00, 1533.30,  203.50,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.24, 3,   boost,   64.72,  84186.00, 1535.72,  205.92,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.25, 3,   boost,   65.21,  84176.00, 1536.69,  206.89,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.26, 3,   boost,   60.80,  84154.00, 1538.82,  209.02,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.27, 3,   boost,   66.19,  84147.00, 1539.50,  209.69,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.28, 3,   boost,   67.67,  84132.00, 1540.95,  211.15,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.29, 3,   boost,   64.23,  84123.00, 1541.82,  212.02,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.30, 3,   boost,   61.78,  84118.00, 1542.30,  212.50,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.31, 3,   boost,   61.78,  84090.00, 1545.01,  215.21,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.31, 3,   boost,   61.78,  84090.00, 1545.01,  215.21,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.31, 3,   boost,   61.78,  84090.00, 1545.01,  215.21,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1, 10,  32.9396882,-106.9114997,  1492.0, 2022,  6, 24, 15, 17, 19,       21,      100, 342,  78,   1.5,   0.8,   1.3,  0, 17, 32,  0,  0, 14,  0,  0,  0,  0, 20, 29, 25, 24,  0,  0, 30,  0, 17, 26,  0,  0,  0, 25,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.32, 3,   boost,   62.76,  84080.00, 1545.98,  216.18,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.33, 3,   boost,   66.19,  84037.00, 1550.14,  220.34,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.34, 3,   boost,   60.31,  84049.00, 1548.98,  219.18,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.35, 3,   boost,   61.78,  84019.00, 1551.89,  222.09,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.36, 3,   boost,   61.29,  84007.00, 1553.05,  223.25,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.37, 3,   boost,   63.25,  83992.00, 1554.50,  224.70,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.38, 3,   boost,   64.72,  83968.00, 1556.83,  227.03,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.39, 3,   boost,   60.80,  83976.00, 1556.05,  226.25,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.40, 3,   boost,   59.82,  83959.00, 1557.70,  227.90,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.41, 3,   boost,   61.78,  83932.00, 1560.32,  230.52,     NaN, 33.5, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.42, 3,   boost,   62.76,  83937.00, 1559.83,  230.03,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.43, 3,   boost,   60.80,  83910.00, 1562.45,  232.65,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.44, 3,   boost,   62.76,  83908.00, 1562.65,  232.85,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.45, 3,   boost,   65.21,  83855.00, 1567.79,  237.99,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.46, 3,   boost,   60.31,  83877.00, 1565.65,  235.85,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.47, 3,   boost,   59.82,  83849.00, 1568.37,  238.57,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.48, 3,   boost,   60.80,  83842.00, 1569.05,  239.25,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.49, 3,   boost,   56.39,  83814.00, 1571.77,  241.97,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.50, 3,   boost,   60.80,  83790.00, 1574.10,  244.29,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.51, 3,   boost,   61.78,  83789.00, 1574.19,  244.39,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.52, 3,   boost,   60.31,  83782.00, 1574.87,  245.07,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.53, 3,   boost,   60.31,  83755.00, 1577.49,  247.69,     NaN, 33.4, 3.99, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.54, 3,   boost,   56.88,  83742.00, 1578.76,  248.96,     NaN, 33.4, 4.00, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.54, 3,   boost,   56.88,  83742.00, 1578.76,  248.96,     NaN, 33.4, 4.00, 3.98, 3.99,   0.07,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.55, 3,   boost,   60.31,  83713.00, 1581.57,  251.77,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.56, 3,   boost,   63.25,  83689.00, 1583.91,  254.11,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.57, 3,   boost,   58.35,  83692.00, 1583.62,  253.81,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.58, 3,   boost,   59.82,  83661.00, 1586.63,  256.83,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.59, 3,   boost,   55.41,  83628.00, 1589.84,  260.04,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.60, 3,   boost,   56.39,  83616.00, 1591.00,  261.20,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.61, 3,   boost,   56.88,  83604.00, 1592.17,  262.37,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.62, 3,   boost,   58.35,  83582.00, 1594.31,  264.51,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.63, 3,   boost,   61.29,  83573.00, 1595.19,  265.39,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.64, 3,   boost,   58.84,  83559.00, 1596.55,  266.75,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.65, 3,   boost,   63.25,  83519.00, 1600.44,  270.64,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.66, 3,   boost,   61.78,  83517.00, 1600.64,  270.84,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.67, 3,   boost,   56.39,  83504.00, 1601.90,  272.10,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.68, 3,   boost,   60.80,  83525.00, 1599.86,  270.06,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.69, 3,   boost,   57.86,  83488.00, 1603.46,  273.66,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.70, 3,   boost,   57.86,  83471.00, 1605.11,  275.31,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.71, 3,   boost,   56.39,  83432.00, 1608.91,  279.11,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.72, 3,   boost,   58.84,  83430.00, 1609.11,  279.31,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.73, 3,   boost,   54.92,  83427.00, 1609.40,  279.60,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.74, 3,   boost,   57.86,  83431.00, 1609.01,  279.21,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.75, 3,   boost,   56.39,  83388.00, 1613.20,  283.40,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.76, 3,   boost,   57.86,  83392.00, 1612.81,  283.01,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.77, 3,   boost,   59.33,  83379.00, 1614.08,  284.28,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.78, 3,   boost,   55.41,  83333.00, 1618.56,  288.76,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.79, 3,   boost,   54.43,  83349.00, 1617.00,  287.20,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.80, 3,   boost,   53.45,  83322.00, 1619.64,  289.84,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.81, 3,   boost,   54.92,  83312.00, 1620.61,  290.81,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.82, 3,   boost,   53.45,  83296.00, 1622.17,  292.37,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.83, 3,   boost,   58.35,  83259.00, 1625.78,  295.98,     NaN, 33.4, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.84, 3,   boost,   52.96,  83244.00, 1627.25,  297.45,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.85, 3,   boost,   47.56,  83192.00, 1632.32,  302.52,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.86, 3,   boost,   50.50,  83179.00, 1633.59,  303.79,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.86, 3,   boost,   50.50,  83179.00, 1633.59,  303.79,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.87, 3,   boost,   53.45,  83168.00, 1634.67,  304.87,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.88, 3,   boost,   52.47,  83146.00, 1636.82,  307.02,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.89, 3,   boost,   56.88,  83154.00, 1636.03,  306.23,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.90, 3,   boost,   54.92,  83130.00, 1638.38,  308.58,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.91, 3,   boost,   52.47,  83097.00, 1641.60,  311.80,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.92, 3,   boost,   50.50,  83083.00, 1642.97,  313.17,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.93, 3,   boost,   55.90,  83087.00, 1642.58,  312.78,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.94, 3,   boost,   55.90,  83067.00, 1644.54,  314.74,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.95, 3,   boost,   53.94,  83065.00, 1644.73,  314.93,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.96, 3,   boost,   56.88,  83032.00, 1647.96,  318.16,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.97, 3,   boost,   51.48,  83035.00, 1647.67,  317.87,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.98, 3,   boost,   54.92,  83016.00, 1649.52,  319.72,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     3.99, 3,   boost,   53.94,  83027.00, 1648.45,  318.65,     NaN, 33.4, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.00, 3,   boost,   51.48,  82995.00, 1651.58,  321.78,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.01, 3,   boost,   50.50,  82974.00, 1653.63,  323.83,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.02, 3,   boost,   49.52,  82949.00, 1656.08,  326.28,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.03, 3,   boost,   52.47,  82958.00, 1655.20,  325.40,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.04, 3,   boost,   51.48,  82934.00, 1657.55,  327.75,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.05, 3,   boost,   50.01,  82919.00, 1659.02,  329.22,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.06, 3,   boost,   57.86,  82895.00, 1661.37,  331.57,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.07, 3,   boost,   51.98,  82892.00, 1661.66,  331.86,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.08, 3,   boost,   54.92,  82813.00, 1669.40,  339.60,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.09, 3,   boost,   54.92,  82826.00, 1668.13,  338.33,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.10, 3,   boost,   55.90,  82828.00, 1667.93,  338.13,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.11, 3,   boost,   54.92,  82782.00, 1672.44,  342.64,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.12, 3,   boost,   61.29,  82763.00, 1674.30,  344.50,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.13, 3,   boost,   48.54,  82752.00, 1675.38,  345.58,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.14, 3,   boost,   52.96,  82730.00, 1677.54,  347.74,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.15, 3,   boost,   55.41,  82725.00, 1678.03,  348.23,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.16, 3,   boost,   55.90,  82689.00, 1681.56,  351.76,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.17, 3,   boost,   53.45,  82650.00, 1685.39,  355.59,     NaN, 33.5, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.18, 3,   boost,   50.99,  82659.00, 1684.51,  354.71,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.18, 3,   boost,   50.99,  82659.00, 1684.51,  354.71,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  63.91,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.19, 3,   boost,   50.01,  82627.00, 1687.65,  357.85,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.20, 3,   boost,   50.50,  82610.00, 1689.32,  359.52,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.21, 3,   boost,   57.86,  82577.00, 1692.56,  362.76,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.22, 3,   boost,   59.33,  82572.00, 1693.05,  363.25,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.23, 3,   boost,   50.99,  82544.00, 1695.80,  366.00,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.24, 3,   boost,   55.90,  82522.00, 1697.96,  368.16,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.25, 3,   boost,   50.01,  82496.00, 1700.52,  370.72,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.26, 3,   boost,   54.43,  82494.00, 1700.72,  370.92,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.27, 3,   boost,   54.43,  82481.00, 1702.00,  372.19,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.28, 3,   boost,   52.96,  82462.00, 1703.86,  374.06,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.29, 3,   boost,   57.37,  82440.00, 1706.03,  376.23,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.30, 3,   boost,   54.92,  82419.00, 1708.09,  378.29,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  8,  32.9397383,-106.9115600,  1643.0, 2022,  6, 24, 15, 17, 20,       28,      251, 335,  84,   1.7,   0.8,   1.5,  0, 10, 28,  0,  0, 11,  0,  0,  0,  0, 14, 36, 32, 25,  0,  0, 22,  0, 11, 31,  0,  0,  0, 21,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,     4.31, 3,   boost,   48.05,  82403.00, 1709.67,  379.87,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.31, 3,   boost,   48.05,  82403.00, 1709.67,  379.87,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.31, 3,   boost,   48.05,  82403.00, 1709.67,  379.87,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.32, 3,   boost,   48.54,  82391.00, 1710.85,  381.05,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.33, 3,   boost,   45.60,  82357.00, 1714.20,  384.40,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.34, 3,   boost,   48.54,  82342.00, 1715.67,  385.87,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.35, 3,   boost,   50.99,  82309.00, 1718.92,  389.12,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.36, 3,   boost,   43.15,  82294.00, 1720.40,  390.60,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.37, 3,   boost,   39.72,  82264.00, 1723.36,  393.56,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.38, 3,   boost,   36.28,  82273.00, 1722.47,  392.67,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.39, 3,   boost,   26.48,  82228.00, 1726.91,  397.10,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.40, 3,   boost,   29.91,  82212.00, 1728.48,  398.68,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.41, 3,   boost,   26.48,  82218.00, 1727.89,  398.09,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.42, 3,   boost,   20.10,  82189.00, 1730.75,  400.95,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.43, 3,   boost,   23.05,  82191.00, 1730.55,  400.75,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.44, 3,   boost,   16.67,  82168.00, 1732.82,  403.02,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.45, 3,   boost,   14.22,  82146.00, 1734.99,  405.19,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.46, 3,   boost,   15.20,  82100.00, 1739.53,  409.73,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.47, 3,   boost,   17.65,  82074.00, 1742.10,  412.30,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.48, 3,   boost,   13.73,  82063.00, 1743.18,  413.38,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.49, 3,   boost,   13.73,  81998.00, 1749.60,  419.80,     NaN, 33.5, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.50, 3,   boost,   11.77,  81979.00, 1751.48,  421.68,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.50, 3,   boost,   11.77,  81979.00, 1751.48,  421.68,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.51, 3,   boost,   14.71,  81975.00, 1751.88,  422.08,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.52, 3,   boost,   10.79,  81933.00, 1756.03,  426.23,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.53, 3,   boost,   14.22,  81883.00, 1760.97,  431.17,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.54, 3,   boost,   13.73,  81832.00, 1766.02,  436.22,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.55, 3,   boost,   15.20,  81830.00, 1766.22,  436.42,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.56, 3,   boost,   10.30,  81798.00, 1769.38,  439.58,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.57, 3,   boost,   11.77,  81783.00, 1770.87,  441.07,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.58, 3,   boost,   10.79,  81759.00, 1773.25,  443.45,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.59, 3,   boost,   11.28,  81709.00, 1778.20,  448.40,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.60, 3,   boost,   11.77,  81681.00, 1780.97,  451.17,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.61, 3,   boost,    6.37,  81653.00, 1783.75,  453.95,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.62, 3,   boost,   15.20,  81604.00, 1788.61,  458.81,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.63, 3,   boost,    6.37,  81599.00, 1789.10,  459.30,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.64, 3,   boost,    9.32,  81557.00, 1793.27,  463.47,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.65, 3,   boost,   17.16,  81558.00, 1793.17,  463.37,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.66, 3,   boost,   -0.49,  81538.00, 1795.16,  465.36,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.67, 3,   boost,    6.37,  81512.00, 1797.74,  467.94,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.68, 3,   boost,    0.98,  81473.00, 1801.61,  471.81,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.69, 3,   boost,    2.45,  81456.00, 1803.30,  473.50,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.70, 3,   boost,   -3.92,  81440.00, 1804.89,  475.09,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.71, 3,   boost,   -5.39,  81395.00, 1809.36,  479.56,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.72, 3,   boost,   -9.81,  81364.00, 1812.44,  482.64,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.73, 3,   boost,   -7.35,  81331.00, 1815.72,  485.92,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.74, 3,   boost,   -4.41,  81261.00, 1822.69,  492.89,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.75, 3,   boost,  -17.65,  81237.00, 1825.08,  495.28,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.76, 3,   boost,  -17.16,  81197.00, 1829.06,  499.26,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.77, 3,   boost,  -14.71,  81142.00, 1834.54,  504.74,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.78, 3,   boost,  -18.14,  81097.00, 1839.02,  509.22,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.79, 3,   boost,  -20.59,  81082.00, 1840.52,  510.72,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.80, 3,   boost,  -26.48,  81056.00, 1843.11,  513.31,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.81, 3,   boost,  -18.63,  81042.00, 1844.51,  514.71,     NaN, 33.5, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.82, 3,   boost,  -25.99,  80999.00, 1848.80,  519.00,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.82, 3,   boost,  -25.99,  80999.00, 1848.80,  519.00,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.83, 3,   boost,  -23.54,  80926.00, 1856.09,  526.28,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.84, 3,   boost,  -29.42,  80870.00, 1861.68,  531.88,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.85, 5,   coast,  -28.93,  80827.00, 1865.98,  536.18,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.85, 5,   coast,  -28.93,  80827.00, 1865.98,  536.18,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.86, 5,   coast,  -21.57,  80773.00, 1871.38,  541.58,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.87, 5,   coast,  -28.93,  80732.00, 1875.48,  545.68,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.88, 5,   coast,  -29.42,  80703.00, 1878.38,  548.58,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.89, 5,   coast,  -25.01,  80599.00, 1888.79,  558.99,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.90, 5,   coast,  -27.95,  80597.00, 1888.99,  559.19,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.91, 5,   coast,  -24.52,  80584.00, 1890.30,  560.50,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.92, 5,   coast,  -29.42,  80533.00, 1895.41,  565.61,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.93, 5,   coast,  -24.03,  80513.00, 1897.41,  567.61,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.94, 5,   coast,  -30.40,  80472.00, 1901.53,  571.73,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.95, 5,   coast,  -27.46,  80457.00, 1903.03,  573.23,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.96, 5,   coast,  -23.05,  80413.00, 1907.45,  577.65,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.97, 5,   coast,  -25.99,  80360.00, 1912.77,  582.97,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.98, 5,   coast,  -25.99,  80342.00, 1914.58,  584.78,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     4.99, 5,   coast,  -24.52,  80313.00, 1917.49,  587.69,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.00, 5,   coast,  -25.50,  80275.00, 1921.31,  591.51,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.01, 5,   coast,  -30.40,  80223.00, 1926.54,  596.74,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.02, 5,   coast,  -25.01,  80201.00, 1928.75,  598.95,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.03, 5,   coast,  -33.34,  80154.00, 1933.48,  603.68,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.04, 5,   coast,  -23.05,  80136.00, 1935.29,  605.49,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.05, 5,   coast,  -29.42,  80125.00, 1936.40,  606.60,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.06, 5,   coast,  -22.56,  80088.00, 1940.12,  610.32,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.07, 5,   coast,  -21.08,  80053.00, 1943.65,  613.85,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.08, 5,   coast,  -19.61,  80007.00, 1948.28,  618.48,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.09, 5,   coast,  -26.48,  79993.00, 1949.69,  619.89,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.10, 5,   coast,  -21.08,  79937.00, 1955.34,  625.54,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.11, 5,   coast,  -22.06,  79928.00, 1956.25,  626.45,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.12, 5,   coast,  -19.12,  79877.00, 1961.39,  631.59,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.13, 5,   coast,  -27.46,  79828.00, 1966.34,  636.54,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.14, 5,   coast,  -31.38,  79798.00, 1969.37,  639.57,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.14, 5,   coast,  -31.38,  79798.00, 1969.37,  639.57,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.15, 5,   coast,  -24.52,  79766.00, 1972.60,  642.80,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.16, 5,   coast,  -23.05,  79741.00, 1975.13,  645.33,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.17, 5,   coast,  -27.46,  79713.00, 1977.96,  648.16,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.18, 5,   coast,  -22.06,  79649.00, 1984.43,  654.63,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.19, 5,   coast,  -24.52,  79643.00, 1985.04,  655.24,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.20, 5,   coast,  -20.59,  79587.00, 1990.70,  660.90,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.21, 5,   coast,  -27.46,  79560.00, 1993.44,  663.64,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.22, 5,   coast,  -22.56,  79540.00, 1995.46,  665.66,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.23, 5,   coast,  -29.42,  79498.00, 1999.72,  669.92,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.24, 5,   coast,  -24.52,  79443.00, 2005.29,  675.49,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.25, 5,   coast,  -16.67,  79452.00, 2004.38,  674.58,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.26, 5,   coast,  -27.95,  79393.00, 2010.36,  680.56,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.27, 5,   coast,  -26.97,  79366.00, 2013.10,  683.30,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.28, 5,   coast,  -23.05,  79327.00, 2017.06,  687.26,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.29, 5,   coast,  -27.95,  79302.00, 2019.59,  689.79,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.30, 5,   coast,  -25.99,  79257.00, 2024.16,  694.36,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9398004,-106.9116947,  1892.0, 2022,  6, 24, 15, 17, 21,       40,      500, 323,  85,   1.9,   1.0,   1.6,  0,  8, 33,  0,  0, 10,  0,  0,  0,  0,  9, 28, 31, 28,  0,  0, 32,  0, 10, 24,  0,  0,  0, 13,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.31, 5,   coast,  -25.01,  79239.00, 2025.99,  696.19,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.31, 5,   coast,  -25.01,  79239.00, 2025.99,  696.19,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.31, 5,   coast,  -25.01,  79239.00, 2025.99,  696.19,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.32, 5,   coast,  -18.14,  79217.00, 2028.23,  698.43,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.33, 5,   coast,  -26.48,  79194.00, 2030.56,  700.76,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.34, 5,   coast,  -25.50,  79141.00, 2035.95,  706.15,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.35, 5,   coast,  -20.59,  79107.00, 2039.41,  709.61,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.36, 5,   coast,  -25.99,  79084.00, 2041.75,  711.95,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.37, 5,   coast,  -26.48,  79047.00, 2045.51,  715.71,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.38, 5,   coast,  -20.59,  79020.00, 2048.26,  718.46,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.39, 5,   coast,  -24.03,  78995.00, 2050.81,  721.01,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.40, 5,   coast,  -25.99,  78946.00, 2055.80,  726.00,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.41, 5,   coast,  -23.54,  78926.00, 2057.84,  728.04,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.42, 5,   coast,  -15.20,  78912.00, 2059.26,  729.46,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.43, 5,   coast,  -21.57,  78859.00, 2064.67,  734.87,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.44, 5,   coast,  -24.03,  78831.00, 2067.52,  737.72,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.45, 5,   coast,  -25.99,  78800.00, 2070.69,  740.88,     NaN, 33.5, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.46, 5,   coast,  -24.03,  78770.00, 2073.75,  743.95,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.46, 5,   coast,  -24.03,  78770.00, 2073.75,  743.95,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.47, 5,   coast,  -26.97,  78729.00, 2077.93,  748.13,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.48, 5,   coast,  -22.06,  78713.00, 2079.57,  749.77,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.49, 5,   coast,  -25.99,  78660.00, 2084.98,  755.18,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.50, 5,   coast,  -20.10,  78623.00, 2088.76,  758.96,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.51, 5,   coast,  -22.06,  78593.00, 2091.83,  762.03,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.52, 5,   coast,  -26.97,  78558.00, 2095.41,  765.61,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.53, 5,   coast,  -23.05,  78532.00, 2098.07,  768.27,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.54, 5,   coast,  -23.05,  78500.00, 2101.34,  771.54,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.55, 5,   coast,  -24.52,  78467.00, 2104.72,  774.92,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.56, 5,   coast,  -25.01,  78421.00, 2109.43,  779.63,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.57, 5,   coast,  -24.03,  78419.00, 2109.64,  779.84,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.58, 5,   coast,  -21.08,  78355.00, 2116.20,  786.40,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.59, 5,   coast,  -20.59,  78349.00, 2116.81,  787.01,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.60, 5,   coast,  -25.50,  78295.00, 2122.35,  792.55,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.61, 5,   coast,  -24.03,  78279.00, 2123.99,  794.19,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.62, 5,   coast,  -24.52,  78242.00, 2127.79,  797.99,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.63, 5,   coast,  -25.99,  78237.00, 2128.30,  798.50,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.64, 5,   coast,  -25.99,  78170.00, 2135.18,  805.38,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.65, 5,   coast,  -24.03,  78154.00, 2136.82,  807.02,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.66, 5,   coast,  -21.08,  78119.00, 2140.42,  810.62,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.67, 5,   coast,  -26.48,  78071.00, 2145.35,  815.55,     NaN, 33.6, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.68, 5,   coast,  -20.59,  78076.00, 2144.84,  815.04,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.69, 5,   coast,  -25.50,  78029.00, 2149.67,  819.87,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.70, 5,   coast,  -24.03,  78013.00, 2151.32,  821.51,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.71, 5,   coast,  -21.57,  77958.00, 2156.97,  827.17,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.72, 5,   coast,  -24.03,  77947.00, 2158.11,  828.31,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.73, 5,   coast,  -18.63,  77906.00, 2162.33,  832.53,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.74, 5,   coast,  -24.52,  77854.00, 2167.69,  837.88,     NaN, 33.6, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.75, 5,   coast,  -26.48,  77850.00, 2168.10,  838.30,     NaN, 33.6, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.76, 5,   coast,  -16.18,  77815.00, 2171.70,  841.90,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.77, 5,   coast,  -22.56,  77785.00, 2174.80,  845.00,     NaN, 33.6, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.78, 5,   coast,  -21.57,  77730.00, 2180.47,  850.67,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.78, 5,   coast,  -21.57,  77730.00, 2180.47,  850.67,     NaN, 33.5, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.79, 5,   coast,  -27.95,  77727.00, 2180.78,  850.98,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.80, 5,   coast,  -22.56,  77696.00, 2183.98,  854.18,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.81, 5,   coast,  -25.01,  77669.00, 2186.77,  856.97,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.82, 5,   coast,  -27.95,  77640.00, 2189.76,  859.96,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.83, 5,   coast,  -23.54,  77604.00, 2193.48,  863.68,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.84, 5,   coast,  -21.57,  77581.00, 2195.86,  866.05,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.85, 5,   coast,  -24.03,  77545.00, 2199.58,  869.77,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.86, 5,   coast,  -18.63,  77514.00, 2202.78,  872.98,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.87, 5,   coast,  -23.54,  77472.00, 2207.12,  877.32,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.88, 5,   coast,  -17.65,  77450.00, 2209.40,  879.60,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.89, 5,   coast,  -18.63,  77423.00, 2212.20,  882.39,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.90, 5,   coast,  -19.12,  77374.00, 2217.27,  887.47,     NaN, 33.5, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.91, 5,   coast,  -23.54,  77364.00, 2218.30,  888.50,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.92, 5,   coast,  -19.61,  77319.00, 2222.97,  893.16,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.93, 5,   coast,  -22.56,  77282.00, 2226.80,  897.00,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.94, 5,   coast,  -22.56,  77276.00, 2227.42,  897.62,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.95, 5,   coast,  -22.56,  77226.00, 2232.61,  902.81,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.96, 5,   coast,  -21.08,  77195.00, 2235.82,  906.02,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.97, 5,   coast,  -22.06,  77179.00, 2237.48,  907.68,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.98, 5,   coast,  -20.10,  77148.00, 2240.70,  910.90,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     5.99, 5,   coast,  -22.06,  77118.00, 2243.81,  914.01,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.00, 5,   coast,  -24.03,  77075.00, 2248.28,  918.48,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.01, 5,   coast,  -20.10,  77058.00, 2250.05,  920.25,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.02, 5,   coast,  -21.08,  77018.00, 2254.20,  924.40,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.03, 5,   coast,  -23.05,  76998.00, 2256.28,  926.48,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.04, 5,   coast,  -21.57,  76956.00, 2260.65,  930.85,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.05, 5,   coast,  -22.56,  76946.00, 2261.69,  931.89,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.06, 5,   coast,  -20.10,  76905.00, 2265.96,  936.16,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.07, 5,   coast,  -21.57,  76880.00, 2268.56,  938.76,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.08, 5,   coast,  -19.61,  76844.00, 2272.31,  942.51,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.09, 5,   coast,  -21.08,  76824.00, 2274.39,  944.59,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.10, 5,   coast,  -20.10,  76790.00, 2277.93,  948.13,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.10, 5,   coast,  -20.10,  76790.00, 2277.93,  948.13,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.11, 5,   coast,  -23.05,  76726.00, 2284.60,  954.80,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.12, 5,   coast,  -20.59,  76727.00, 2284.50,  954.70,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.13, 5,   coast,  -19.12,  76694.00, 2287.94,  958.14,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.14, 5,   coast,  -23.05,  76677.00, 2289.71,  959.91,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.15, 5,   coast,  -23.54,  76640.00, 2293.57,  963.77,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.16, 5,   coast,  -17.16,  76617.00, 2295.97,  966.17,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.17, 5,   coast,  -24.03,  76581.00, 2299.73,  969.93,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.18, 5,   coast,  -20.59,  76550.00, 2302.97,  973.17,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.19, 5,   coast,  -21.57,  76525.00, 2305.58,  975.78,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.20, 5,   coast,  -21.08,  76502.00, 2307.99,  978.18,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.21, 5,   coast,  -19.12,  76477.00, 2310.60,  980.80,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.22, 5,   coast,  -20.59,  76437.00, 2314.78,  984.98,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.23, 5,   coast,  -21.08,  76432.00, 2315.30,  985.50,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.24, 5,   coast,  -21.57,  76366.00, 2322.21,  992.41,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.25, 5,   coast,  -24.03,  76346.00, 2324.30,  994.50,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.26, 5,   coast,  -22.06,  76330.00, 2325.98,  996.18,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.27, 5,   coast,  -22.06,  76312.00, 2327.86,  998.06,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.28, 5,   coast,  -21.08,  76261.00, 2333.20, 1003.40,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.29, 5,   coast,  -24.03,  76250.00, 2334.36, 1004.56,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.30, 5,   coast,  -17.65,  76194.00, 2340.23, 1010.43,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  6,  32.9399039,-106.9119312,  2210.0, 2022,  6, 24, 15, 17, 22,       64,      818, 313,  86,   1.9,   1.0,   1.6,  0,  7, 29,  0,  0,  9,  0,  0,  0,  0,  8, 28, 34, 28,  0,  0, 32,  0, 11, 29,  0,  0,  0, 10,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     6.31, 5,   coast,  -20.10,  76185.00, 2341.17, 1011.37,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.31, 5,   coast,  -20.10,  76185.00, 2341.17, 1011.37,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.31, 5,   coast,  -20.10,  76185.00, 2341.17, 1011.37,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.32, 5,   coast,  -18.14,  76169.00, 2342.85, 1013.05,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.33, 5,   coast,  -19.12,  76120.00, 2347.99, 1018.19,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.34, 5,   coast,  -18.14,  76088.00, 2351.35, 1021.55,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.35, 5,   coast,  -22.06,  76058.00, 2354.50, 1024.70,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.36, 5,   coast,  -26.48,  76012.00, 2359.33, 1029.53,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.37, 5,   coast,  -20.59,  75994.00, 2361.22, 1031.42,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.38, 5,   coast,  -23.05,  75961.00, 2364.69, 1034.89,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.39, 5,   coast,  -25.01,  75949.00, 2365.95, 1036.15,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.40, 5,   coast,  -22.06,  75885.00, 2372.68, 1042.88,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.41, 5,   coast,  -21.57,  75911.00, 2369.95, 1040.15,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.42, 5,   coast,  -22.56,  75875.00, 2373.73, 1043.93,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.42, 5,   coast,  -22.56,  75875.00, 2373.73, 1043.93,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.43, 5,   coast,  -20.59,  75837.00, 2377.73, 1047.93,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.44, 5,   coast,  -20.10,  75813.00, 2380.26, 1050.46,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.45, 5,   coast,  -22.56,  75788.00, 2382.89, 1053.09,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.46, 5,   coast,  -21.57,  75761.00, 2385.73, 1055.93,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.47, 5,   coast,  -23.05,  75717.00, 2390.37, 1060.57,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.48, 5,   coast,  -20.59,  75690.00, 2393.22, 1063.42,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.49, 5,   coast,  -20.10,  75664.00, 2395.96, 1066.16,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.50, 5,   coast,  -18.63,  75641.00, 2398.38, 1068.58,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.51, 5,   coast,  -17.65,  75625.00, 2400.07, 1070.27,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.52, 5,   coast,  -21.08,  75583.00, 2404.50, 1074.70,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.53, 5,   coast,  -20.10,  75567.00, 2406.19, 1076.39,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.54, 5,   coast,  -21.08,  75529.00, 2410.20, 1080.40,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.55, 5,   coast,  -21.57,  75486.00, 2414.75, 1084.94,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.56, 5,   coast,  -19.61,  75469.00, 2416.54, 1086.74,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.57, 5,   coast,  -19.12,  75459.00, 2417.60, 1087.80,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.58, 5,   coast,  -23.05,  75409.00, 2422.88, 1093.08,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.59, 5,   coast,  -15.20,  75399.00, 2423.94, 1094.14,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.60, 5,   coast,  -19.12,  75350.00, 2429.12, 1099.32,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.61, 5,   coast,  -22.06,  75342.00, 2429.97, 1100.17,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.62, 5,   coast,  -16.18,  75307.00, 2433.67, 1103.87,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.63, 5,   coast,  -24.03,  75275.00, 2437.06, 1107.26,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.64, 5,   coast,  -19.61,  75251.00, 2439.60, 1109.80,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.65, 5,   coast,  -21.08,  75209.00, 2444.05, 1114.25,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.66, 5,   coast,  -24.03,  75184.00, 2446.70, 1116.90,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.67, 5,   coast,  -19.12,  75160.00, 2449.25, 1119.45,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.68, 5,   coast,  -13.24,  75140.00, 2451.37, 1121.57,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.69, 5,   coast,  -19.61,  75102.00, 2455.40, 1125.60,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.70, 5,   coast,  -22.06,  75083.00, 2457.41, 1127.61,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.71, 5,   coast,  -21.57,  75049.00, 2461.02, 1131.22,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.72, 5,   coast,  -20.10,  75008.00, 2465.38, 1135.57,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.73, 5,   coast,  -22.56,  75003.00, 2465.91, 1136.11,     NaN, 33.6, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.74, 5,   coast,  -17.65,  74958.00, 2470.69, 1140.89,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.74, 5,   coast,  -17.65,  74958.00, 2470.69, 1140.89,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  63.91,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.75, 5,   coast,  -26.48,  74934.00, 2473.24, 1143.44,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.76, 5,   coast,  -20.10,  74931.00, 2473.56, 1143.76,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.77, 5,   coast,  -24.03,  74875.00, 2479.51, 1149.71,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.78, 5,   coast,  -21.57,  74864.00, 2480.68, 1150.88,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.79, 5,   coast,  -19.12,  74850.00, 2482.17, 1152.37,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.80, 5,   coast,  -24.52,  74831.00, 2484.19, 1154.39,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.81, 5,   coast,  -16.67,  74788.00, 2488.77, 1158.97,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.82, 5,   coast,  -21.08,  74752.00, 2492.60, 1162.80,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.83, 5,   coast,  -23.54,  74731.00, 2494.84, 1165.03,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.84, 5,   coast,  -21.57,  74700.00, 2498.14, 1168.34,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.85, 5,   coast,  -18.63,  74679.00, 2500.38, 1170.58,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.86, 5,   coast,  -19.12,  74644.00, 2504.11, 1174.31,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.87, 5,   coast,  -21.57,  74613.00, 2507.41, 1177.61,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.88, 5,   coast,  -20.59,  74590.00, 2509.87, 1180.06,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.89, 5,   coast,  -21.08,  74573.00, 2511.68, 1181.88,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.90, 5,   coast,  -20.10,  74547.00, 2514.45, 1184.65,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.91, 5,   coast,  -22.06,  74503.00, 2519.15, 1189.35,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.92, 5,   coast,  -22.56,  74477.00, 2521.93, 1192.13,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.93, 5,   coast,  -20.59,  74429.00, 2527.06, 1197.25,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.94, 5,   coast,  -23.05,  74413.00, 2528.77, 1198.96,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.95, 5,   coast,  -23.05,  74392.00, 2531.01, 1201.21,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.96, 5,   coast,  -16.18,  74381.00, 2532.19, 1202.39,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.97, 5,   coast,  -21.57,  74337.00, 2536.89, 1207.09,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.98, 5,   coast,  -20.59,  74311.00, 2539.67, 1209.87,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     6.99, 5,   coast,  -18.63,  74299.00, 2540.96, 1211.16,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.00, 5,   coast,  -22.06,  74266.00, 2544.49, 1214.69,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.01, 5,   coast,  -22.56,  74244.00, 2546.85, 1217.04,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.02, 5,   coast,  -18.14,  74208.00, 2550.70, 1220.90,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.03, 5,   coast,  -23.05,  74192.00, 2552.41, 1222.61,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.04, 5,   coast,  -21.57,  74161.00, 2555.74, 1225.94,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.05, 5,   coast,  -21.08,  74123.00, 2559.81, 1230.01,     NaN, 33.6, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.06, 5,   coast,  -19.61,  74112.00, 2560.99, 1231.19,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.06, 5,   coast,  -19.61,  74112.00, 2560.99, 1231.19,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.07, 5,   coast,  -18.63,  74060.00, 2566.57, 1236.77,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.08, 5,   coast,  -20.59,  74031.00, 2569.68, 1239.88,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.09, 5,   coast,  -21.57,  74015.00, 2571.40, 1241.60,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.10, 5,   coast,  -21.08,  73992.00, 2573.87, 1244.07,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.11, 5,   coast,  -20.10,  73970.00, 2576.23, 1246.43,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.12, 5,   coast,  -12.26,  73943.00, 2579.13, 1249.33,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.13, 5,   coast,  -19.61,  73908.00, 2582.89, 1253.09,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.14, 5,   coast,  -17.16,  73878.00, 2586.11, 1256.31,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.15, 5,   coast,  -22.56,  73845.00, 2589.66, 1259.86,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.16, 5,   coast,  -25.01,  73845.00, 2589.66, 1259.86,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.17, 5,   coast,  -19.61,  73814.00, 2593.00, 1263.20,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.18, 5,   coast,  -20.59,  73780.00, 2596.66, 1266.85,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.19, 5,   coast,  -23.05,  73756.00, 2599.24, 1269.44,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.20, 5,   coast,  -16.67,  73736.00, 2601.39, 1271.59,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.21, 5,   coast,  -19.12,  73695.00, 2605.81, 1276.01,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.22, 5,   coast,  -20.10,  73691.00, 2606.24, 1276.44,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.23, 5,   coast,  -17.65,  73659.00, 2609.69, 1279.89,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.24, 5,   coast,  -17.16,  73621.00, 2613.78, 1283.98,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.25, 5,   coast,  -20.10,  73595.00, 2616.59, 1286.79,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.26, 5,   coast,  -16.18,  73572.00, 2619.07, 1289.27,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.27, 5,   coast,  -20.10,  73534.00, 2623.17, 1293.37,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.28, 5,   coast,  -18.63,  73524.00, 2624.25, 1294.45,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.29, 5,   coast,  -16.18,  73494.00, 2627.48, 1297.68,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.30, 5,   coast,  -17.16,  73473.00, 2629.75, 1299.95,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  7,  32.9399992,-106.9121774,  2529.0, 2022,  6, 24, 15, 17, 23,       88,     1138, 308,  86,   1.9,   0.9,   1.6,  0, 32, 29,  0,  0,  8,  0,  0,  0,  0,  0, 28, 30, 27,  0,  0, 32,  0,  0, 23,  0,  0,  0,  9,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     7.31, 5,   coast,  -20.10,  73427.00, 2634.72, 1304.92,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.31, 5,   coast,  -20.10,  73427.00, 2634.72, 1304.92,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.31, 5,   coast,  -20.10,  73427.00, 2634.72, 1304.92,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.32, 5,   coast,  -16.67,  73400.00, 2637.64, 1307.84,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.33, 5,   coast,  -21.08,  73391.00, 2638.61, 1308.81,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.34, 5,   coast,  -20.59,  73348.00, 2643.26, 1313.46,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.35, 5,   coast,  -15.20,  73341.00, 2644.02, 1314.22,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.36, 5,   coast,  -23.54,  73321.00, 2646.18, 1316.38,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.37, 5,   coast,  -20.59,  73272.00, 2651.48, 1321.68,     NaN, 33.6, 3.98, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.38, 5,   coast,  -18.14,  73257.00, 2653.11, 1323.30,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.38, 5,   coast,  -18.14,  73257.00, 2653.11, 1323.30,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.21,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.39, 5,   coast,  -15.69,  73227.00, 2656.35, 1326.55,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.40, 5,   coast,  -20.10,  73211.00, 2658.09, 1328.28,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.41, 5,   coast,  -15.20,  73165.00, 2663.07, 1333.27,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.42, 5,   coast,  -18.63,  73141.00, 2665.67, 1335.87,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.43, 5,   coast,  -20.59,  73101.00, 2670.01, 1340.20,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.44, 5,   coast,  -19.12,  73096.00, 2670.55, 1340.75,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.45, 5,   coast,  -17.65,  73075.00, 2672.83, 1343.02,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.46, 5,   coast,  -18.14,  73024.00, 2678.36, 1348.56,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.47, 5,   coast,  -17.65,  73011.00, 2679.77, 1349.97,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.48, 5,   coast,  -16.18,  72980.00, 2683.14, 1353.33,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.49, 5,   coast,  -21.08,  72959.00, 2685.42, 1355.61,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.50, 5,   coast,  -17.65,  72944.00, 2687.04, 1357.24,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.51, 5,   coast,  -21.08,  72943.00, 2687.15, 1357.35,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.52, 5,   coast,  -17.65,  72894.00, 2692.48, 1362.68,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.53, 5,   coast,  -18.14,  72875.00, 2694.54, 1364.74,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.54, 5,   coast,  -19.12,  72855.00, 2696.72, 1366.92,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.55, 5,   coast,  -19.61,  72813.00, 2701.28, 1371.48,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.56, 5,   coast,  -21.57,  72794.00, 2703.35, 1373.55,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.57, 5,   coast,  -18.63,  72776.00, 2705.31, 1375.51,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.58, 5,   coast,  -15.69,  72749.00, 2708.25, 1378.45,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.59, 5,   coast,  -19.61,  72734.00, 2709.88, 1380.08,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.60, 5,   coast,  -17.65,  72693.00, 2714.35, 1384.55,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.61, 5,   coast,  -15.69,  72681.00, 2715.65, 1385.85,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.62, 5,   coast,  -18.63,  72647.00, 2719.36, 1389.56,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.63, 5,   coast,  -19.61,  72619.00, 2722.41, 1392.61,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.64, 5,   coast,  -16.67,  72621.00, 2722.19, 1392.39,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.65, 5,   coast,  -19.12,  72589.00, 2725.68, 1395.88,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.66, 5,   coast,  -18.63,  72557.00, 2729.17, 1399.37,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.67, 5,   coast,  -18.14,  72525.00, 2732.66, 1402.86,     NaN, 33.6, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.68, 5,   coast,  -19.12,  72509.00, 2734.41, 1404.61,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.69, 5,   coast,  -18.63,  72481.00, 2737.47, 1407.67,     NaN, 33.7, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.70, 5,   coast,  -22.06,  72433.00, 2742.71, 1412.91,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.70, 5,   coast,  -22.06,  72433.00, 2742.71, 1412.91,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.71, 5,   coast,  -20.59,  72435.00, 2742.49, 1412.69,     NaN, 33.6, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.72, 5,   coast,  -19.12,  72409.00, 2745.33, 1415.53,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.73, 5,   coast,  -21.08,  72367.00, 2749.92, 1420.12,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.74, 5,   coast,  -20.59,  72361.00, 2750.58, 1420.78,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.75, 5,   coast,  -20.10,  72321.00, 2754.95, 1425.15,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.76, 5,   coast,  -19.61,  72289.00, 2758.45, 1428.65,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.77, 5,   coast,  -16.18,  72265.00, 2761.08, 1431.28,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.78, 5,   coast,  -17.65,  72233.00, 2764.58, 1434.78,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.79, 5,   coast,  -19.61,  72228.00, 2765.13, 1435.33,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.80, 5,   coast,  -19.61,  72198.00, 2768.41, 1438.61,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.81, 5,   coast,  -21.08,  72169.00, 2771.59, 1441.79,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.82, 5,   coast,  -16.18,  72163.00, 2772.25, 1442.45,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.83, 5,   coast,  -20.10,  72110.00, 2778.06, 1448.26,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.84, 5,   coast,  -21.08,  72089.00, 2780.36, 1450.56,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.85, 5,   coast,  -17.65,  72057.00, 2783.87, 1454.07,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.86, 5,   coast,  -23.54,  72047.00, 2784.97, 1455.17,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.87, 5,   coast,  -17.16,  72015.00, 2788.48, 1458.68,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.88, 5,   coast,  -16.67,  72008.00, 2789.25, 1459.45,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.89, 5,   coast,  -15.20,  71998.00, 2790.34, 1460.54,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.90, 5,   coast,  -19.61,  71966.00, 2793.86, 1464.06,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.91, 5,   coast,  -17.16,  71933.00, 2797.48, 1467.68,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.92, 5,   coast,  -21.08,  71922.00, 2798.69, 1468.89,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.93, 5,   coast,  -17.65,  71887.00, 2802.54, 1472.74,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.94, 5,   coast,  -18.63,  71859.00, 2805.61, 1475.81,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.95, 5,   coast,  -16.18,  71834.00, 2808.36, 1478.56,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.96, 5,   coast,  -18.63,  71810.00, 2811.00, 1481.20,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.97, 5,   coast,  -17.16,  71794.00, 2812.76, 1482.96,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.98, 5,   coast,  -18.14,  71792.00, 2812.98, 1483.18,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     7.99, 5,   coast,  -15.20,  71766.00, 2815.85, 1486.04,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.00, 5,   coast,  -16.18,  71738.00, 2818.93, 1489.13,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.01, 5,   coast,  -18.14,  71711.00, 2821.90, 1492.10,     NaN, 33.7, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.02, 5,   coast,  -14.22,  71672.00, 2826.20, 1496.40,     NaN, 33.7, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.02, 5,   coast,  -14.22,  71672.00, 2826.20, 1496.40,     NaN, 33.7, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.03, 5,   coast,  -18.63,  71649.00, 2828.73, 1498.93,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.04, 5,   coast,  -17.65,  71631.00, 2830.72, 1500.91,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.05, 5,   coast,  -19.61,  71598.00, 2834.35, 1504.55,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.06, 5,   coast,  -19.61,  71576.00, 2836.78, 1506.98,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.07, 5,   coast,  -15.69,  71550.00, 2839.65, 1509.85,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.08, 5,   coast,  -18.63,  71519.00, 2843.07, 1513.27,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.09, 5,   coast,  -17.65,  71502.00, 2844.95, 1515.14,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.10, 5,   coast,  -18.63,  71479.00, 2847.48, 1517.68,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.11, 5,   coast,  -20.10,  71452.00, 2850.47, 1520.67,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.12, 5,   coast,  -23.05,  71426.00, 2853.34, 1523.54,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.13, 5,   coast,  -17.65,  71404.00, 2855.77, 1525.97,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.14, 5,   coast,  -15.69,  71360.00, 2860.63, 1530.83,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.15, 5,   coast,  -21.57,  71360.00, 2860.63, 1530.83,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.16, 5,   coast,  -13.73,  71324.00, 2864.61, 1534.81,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.17, 5,   coast,  -17.16,  71323.00, 2864.73, 1534.92,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.18, 5,   coast,  -18.14,  71280.00, 2869.48, 1539.68,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.19, 5,   coast,  -21.08,  71281.00, 2869.37, 1539.57,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.20, 5,   coast,  -21.08,  71250.00, 2872.80, 1543.00,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.21, 5,   coast,  -17.65,  71195.00, 2878.89, 1549.09,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.22, 5,   coast,  -18.14,  71179.00, 2880.67, 1550.87,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.23, 5,   coast,  -21.08,  71185.00, 2880.00, 1550.20,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.24, 5,   coast,  -20.10,  71150.00, 2883.88, 1554.08,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.25, 5,   coast,  -21.57,  71129.00, 2886.21, 1556.41,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.26, 5,   coast,  -16.67,  71101.00, 2889.31, 1559.51,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.27, 5,   coast,  -19.61,  71071.00, 2892.64, 1562.84,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.28, 5,   coast,  -18.63,  71039.00, 2896.19, 1566.39,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.29, 5,   coast,  -16.18,  71021.00, 2898.19, 1568.39,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.30, 5,   coast,  -19.12,  70989.00, 2901.74, 1571.94,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.31, 5,   coast,  -18.14,  70974.00, 2903.41, 1573.61,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1,  9,  32.9400882,-106.9124212,  2829.0, 2022,  6, 24, 15, 17, 24,      112,     1439, 305,  86,   1.5,   0.8,   1.2,  0, 30, 29,  0,  0, 36,  0,  0,  0,  0, 24, 29, 30, 28,  0,  0, 37,  0, 28, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 21,  0,  0
+6, 6583, 3,VE3LIC,     8.32, 5,   coast,  -17.65,  70958.00, 2905.18, 1575.38,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.32, 5,   coast,  -17.65,  70958.00, 2905.18, 1575.38,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.32, 5,   coast,  -17.65,  70958.00, 2905.18, 1575.38,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.33, 5,   coast,  -22.56,  70956.00, 2905.41, 1575.61,     NaN, 33.7, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.34, 5,   coast,  -14.71,  70902.00, 2911.41, 1581.61,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.34, 5,   coast,  -14.71,  70902.00, 2911.41, 1581.61,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.35, 5,   coast,  -16.18,  70894.00, 2912.30, 1582.49,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.36, 5,   coast,  -18.63,  70877.00, 2914.19, 1584.38,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.37, 5,   coast,  -16.18,  70847.00, 2917.52, 1587.72,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.38, 5,   coast,  -16.18,  70822.00, 2920.30, 1590.50,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.39, 5,   coast,  -18.14,  70817.00, 2920.86, 1591.06,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.40, 5,   coast,  -15.20,  70794.00, 2923.42, 1593.62,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.41, 5,   coast,  -17.16,  70765.00, 2926.65, 1596.84,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.42, 5,   coast,  -17.65,  70740.00, 2929.43, 1599.63,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.43, 5,   coast,  -19.12,  70695.00, 2934.44, 1604.64,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.44, 5,   coast,  -21.57,  70681.00, 2936.00, 1606.20,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.45, 5,   coast,  -16.67,  70649.00, 2939.57, 1609.77,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.46, 5,   coast,  -13.73,  70642.00, 2940.35, 1610.55,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.47, 5,   coast,  -21.57,  70634.00, 2941.24, 1611.44,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.48, 5,   coast,  -16.18,  70596.00, 2945.48, 1615.68,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.49, 5,   coast,  -18.63,  70587.00, 2946.48, 1616.68,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.50, 5,   coast,  -17.16,  70566.00, 2948.82, 1619.02,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.51, 5,   coast,  -14.22,  70517.00, 2954.29, 1624.49,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.52, 5,   coast,  -15.20,  70516.00, 2954.40, 1624.60,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.53, 5,   coast,  -19.12,  70479.00, 2958.54, 1628.73,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.54, 5,   coast,  -16.18,  70460.00, 2960.66, 1630.86,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.55, 5,   coast,  -15.20,  70438.00, 2963.12, 1633.32,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.56, 5,   coast,  -15.20,  70407.00, 2966.58, 1636.78,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.57, 5,   coast,  -18.63,  70387.00, 2968.82, 1639.02,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.58, 5,   coast,  -16.67,  70384.00, 2969.15, 1639.35,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.59, 5,   coast,  -14.22,  70349.00, 2973.07, 1643.27,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.60, 5,   coast,  -16.67,  70324.00, 2975.86, 1646.06,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.61, 5,   coast,  -14.22,  70305.00, 2977.99, 1648.19,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.62, 5,   coast,  -17.16,  70271.00, 2981.79, 1651.99,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.63, 5,   coast,  -16.67,  70260.00, 2983.03, 1653.23,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.64, 5,   coast,  -20.10,  70227.00, 2986.72, 1656.92,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.65, 5,   coast,  -18.63,  70201.00, 2989.63, 1659.83,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.66, 5,   coast,  -18.63,  70174.00, 2992.66, 1662.86,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.66, 5,   coast,  -18.63,  70174.00, 2992.66, 1662.86,     NaN, 33.7, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.67, 5,   coast,  -16.67,  70155.00, 2994.79, 1664.99,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.68, 5,   coast,  -15.20,  70122.00, 2998.49, 1668.69,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.69, 5,   coast,  -18.63,  70129.00, 2997.71, 1667.90,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.70, 5,   coast,  -14.71,  70102.00, 3000.73, 1670.93,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.71, 5,   coast,  -19.12,  70073.00, 3003.99, 1674.19,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.72, 5,   coast,  -13.24,  70050.00, 3006.57, 1676.77,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.73, 5,   coast,  -19.12,  70035.00, 3008.25, 1678.45,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.74, 5,   coast,  -13.73,  69996.00, 3012.63, 1682.83,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.75, 5,   coast,  -18.63,  69980.00, 3014.43, 1684.63,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.76, 5,   coast,  -17.65,  69954.00, 3017.35, 1687.55,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.77, 5,   coast,  -19.61,  69942.00, 3018.70, 1688.90,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.78, 5,   coast,  -17.16,  69918.00, 3021.40, 1691.59,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.79, 5,   coast,  -16.67,  69873.00, 3026.46, 1696.65,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.80, 5,   coast,  -17.16,  69868.00, 3027.02, 1697.22,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.81, 5,   coast,  -16.67,  69843.00, 3029.83, 1700.03,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.82, 5,   coast,  -18.14,  69815.00, 3032.98, 1703.18,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.83, 5,   coast,  -16.18,  69791.00, 3035.68, 1705.88,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.84, 5,   coast,  -16.18,  69766.00, 3038.50, 1708.70,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.85, 5,   coast,  -17.65,  69730.00, 3042.55, 1712.75,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.86, 5,   coast,  -15.20,  69732.00, 3042.33, 1712.53,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.87, 5,   coast,  -16.67,  69710.00, 3044.81, 1715.00,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.88, 5,   coast,  -18.14,  69684.00, 3047.74, 1717.93,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.89, 5,   coast,  -16.18,  69651.00, 3051.46, 1721.65,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.90, 5,   coast,  -18.63,  69636.00, 3053.15, 1723.35,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.91, 5,   coast,  -16.67,  69623.00, 3054.61, 1724.81,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.92, 5,   coast,  -16.67,  69609.00, 3056.19, 1726.39,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.93, 5,   coast,  -17.65,  69593.00, 3058.00, 1728.20,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.94, 5,   coast,  -16.67,  69564.00, 3061.27, 1731.47,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.95, 5,   coast,  -15.69,  69546.00, 3063.30, 1733.50,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.96, 5,   coast,  -16.67,  69529.00, 3065.22, 1735.42,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.97, 5,   coast,  -17.16,  69506.00, 3067.82, 1738.02,     NaN, 33.7, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.98, 5,   coast,  -16.18,  69489.00, 3069.74, 1739.94,     NaN, 33.7, 3.99, 3.98, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.98, 5,   coast,  -16.18,  69489.00, 3069.74, 1739.94,     NaN, 33.7, 3.99, 3.98, 3.99,   0.08,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     8.99, 5,   coast,  -20.59,  69463.00, 3072.68, 1742.88,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.00, 5,   coast,  -17.65,  69447.00, 3074.49, 1744.69,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.01, 5,   coast,  -18.63,  69423.00, 3077.20, 1747.40,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.02, 5,   coast,  -15.69,  69393.00, 3080.59, 1750.79,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.03, 5,   coast,  -17.16,  69384.00, 3081.61, 1751.81,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.04, 5,   coast,  -14.71,  69354.00, 3085.00, 1755.20,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.05, 5,   coast,  -18.63,  69336.00, 3087.04, 1757.24,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.06, 5,   coast,  -16.18,  69318.00, 3089.08, 1759.28,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.07, 5,   coast,  -16.18,  69294.00, 3091.80, 1761.99,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.08, 5,   coast,  -14.22,  69265.00, 3095.08, 1765.28,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.09, 5,   coast,  -17.65,  69253.00, 3096.44, 1766.64,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.10, 5,   coast,  -17.16,  69252.00, 3096.55, 1766.75,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.11, 5,   coast,  -14.22,  69209.00, 3101.42, 1771.62,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.12, 5,   coast,  -17.16,  69195.00, 3103.01, 1773.21,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.13, 5,   coast,  -15.69,  69156.00, 3107.43, 1777.63,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.14, 5,   coast,  -18.14,  69145.00, 3108.68, 1778.88,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.15, 5,   coast,  -16.67,  69125.00, 3110.95, 1781.15,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.16, 5,   coast,  -14.22,  69095.00, 3114.35, 1784.55,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.17, 5,   coast,  -14.22,  69069.00, 3117.31, 1787.51,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.18, 5,   coast,  -15.69,  69058.00, 3118.56, 1788.75,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.19, 5,   coast,  -16.67,  69027.00, 3122.08, 1792.27,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.20, 5,   coast,  -17.65,  69004.00, 3124.69, 1794.89,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.21, 5,   coast,  -17.16,  68980.00, 3127.42, 1797.61,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.22, 5,   coast,  -20.10,  68970.00, 3128.55, 1798.75,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.23, 5,   coast,  -14.71,  68954.00, 3130.37, 1800.57,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.24, 5,   coast,  -17.65,  68930.00, 3133.10, 1803.30,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.25, 5,   coast,  -19.61,  68909.00, 3135.49, 1805.69,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.26, 5,   coast,  -14.22,  68878.00, 3139.01, 1809.21,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.27, 5,   coast,  -14.71,  68874.00, 3139.47, 1809.67,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.28, 5,   coast,  -14.71,  68844.00, 3142.88, 1813.08,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.29, 5,   coast,  -16.18,  68835.00, 3143.91, 1814.11,     NaN, 33.7, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.30, 5,   coast,  -17.65,  68809.00, 3146.87, 1817.07,     NaN, 33.7, 4.01, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.30, 5,   coast,  -17.65,  68809.00, 3146.87, 1817.07,     NaN, 33.7, 4.01, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9401936,-106.9126653,  3100.0, 2022,  6, 24, 15, 17, 25,      138,     1712, 303,  85,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 33,  0,  0,  0,  0, 30, 36, 34, 28,  0,  0, 24,  0, 29, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,     9.31, 5,   coast,  -16.18,  68782.00, 3149.94, 1820.14,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.31, 5,   coast,  -16.18,  68782.00, 3149.94, 1820.14,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.31, 5,   coast,  -16.18,  68782.00, 3149.94, 1820.14,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.32, 5,   coast,  -15.69,  68781.00, 3150.06, 1820.26,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.33, 5,   coast,  -13.73,  68747.00, 3153.93, 1824.13,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.34, 5,   coast,  -17.16,  68733.00, 3155.53, 1825.73,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.35, 5,   coast,  -14.22,  68712.00, 3157.92, 1828.12,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.36, 5,   coast,  -15.20,  68668.00, 3162.94, 1833.14,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.37, 5,   coast,  -14.71,  68679.00, 3161.68, 1831.88,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.38, 5,   coast,  -15.20,  68651.00, 3164.88, 1835.08,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.39, 5,   coast,  -16.18,  68639.00, 3166.25, 1836.45,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.40, 5,   coast,  -16.18,  68607.00, 3169.90, 1840.10,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.41, 5,   coast,  -15.20,  68580.00, 3172.98, 1843.18,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.42, 5,   coast,  -16.67,  68557.00, 3175.61, 1845.81,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.43, 5,   coast,  -14.22,  68552.00, 3176.18, 1846.38,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.44, 5,   coast,  -18.63,  68522.00, 3179.61, 1849.81,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.45, 5,   coast,  -14.22,  68514.00, 3180.52, 1850.72,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.46, 5,   coast,  -15.69,  68479.00, 3184.52, 1854.72,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.47, 5,   coast,  -16.18,  68454.00, 3187.38, 1857.58,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.48, 5,   coast,  -17.65,  68433.00, 3189.78, 1859.98,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.49, 5,   coast,  -18.63,  68416.00, 3191.73, 1861.93,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.50, 5,   coast,  -15.69,  68381.00, 3195.73, 1865.93,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.51, 5,   coast,  -17.16,  68370.00, 3196.99, 1867.19,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.52, 5,   coast,  -18.63,  68368.00, 3197.22, 1867.42,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.53, 5,   coast,  -18.63,  68332.00, 3201.34, 1871.54,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.54, 5,   coast,  -17.16,  68317.00, 3203.06, 1873.26,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.55, 5,   coast,  -18.14,  68287.00, 3206.50, 1876.70,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.56, 5,   coast,  -17.16,  68268.00, 3208.67, 1878.87,     NaN, 33.8, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.57, 5,   coast,  -15.20,  68237.00, 3212.23, 1882.43,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.58, 5,   coast,  -15.20,  68219.00, 3214.29, 1884.49,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.59, 5,   coast,  -11.77,  68211.00, 3215.21, 1885.41,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.60, 5,   coast,  -16.18,  68193.00, 3217.27, 1887.47,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.61, 5,   coast,  -17.65,  68164.00, 3220.60, 1890.80,     NaN, 33.7, 4.01, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.62, 5,   coast,  -19.12,  68126.00, 3224.96, 1895.16,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.62, 5,   coast,  -19.12,  68126.00, 3224.96, 1895.16,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.63, 5,   coast,  -16.18,  68119.00, 3225.77, 1895.96,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.64, 5,   coast,  -17.16,  68099.00, 3228.06, 1898.26,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.65, 5,   coast,  -17.65,  68082.00, 3230.01, 1900.21,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.66, 5,   coast,  -19.12,  68066.00, 3231.85, 1902.05,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.67, 5,   coast,  -17.65,  68027.00, 3236.33, 1906.53,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.68, 5,   coast,  -16.18,  68023.00, 3236.79, 1906.99,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.69, 5,   coast,  -22.56,  67994.00, 3240.13, 1910.33,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.70, 5,   coast,  -17.65,  67968.00, 3243.12, 1913.32,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.71, 5,   coast,  -16.18,  67965.00, 3243.46, 1913.66,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.72, 5,   coast,  -17.16,  67943.00, 3245.99, 1916.19,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.73, 5,   coast,  -17.65,  67916.00, 3249.10, 1919.30,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.74, 5,   coast,  -14.22,  67896.00, 3251.40, 1921.60,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.75, 5,   coast,  -16.18,  67870.00, 3254.40, 1924.59,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.76, 5,   coast,  -16.67,  67860.00, 3255.55, 1925.75,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.77, 5,   coast,  -18.63,  67823.00, 3259.81, 1930.01,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.78, 5,   coast,  -16.67,  67826.00, 3259.46, 1929.66,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.79, 5,   coast,  -16.18,  67795.00, 3263.04, 1933.23,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.80, 5,   coast,  -13.73,  67781.00, 3264.65, 1934.85,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.81, 5,   coast,  -19.12,  67753.00, 3267.88, 1938.08,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.82, 5,   coast,  -17.65,  67735.00, 3269.95, 1940.15,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.83, 5,   coast,  -14.22,  67702.00, 3273.76, 1943.96,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.84, 5,   coast,  -16.18,  67707.00, 3273.18, 1943.38,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.85, 5,   coast,  -15.20,  67676.00, 3276.76, 1946.96,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.86, 5,   coast,  -14.22,  67657.00, 3278.95, 1949.15,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.87, 5,   coast,  -16.18,  67655.00, 3279.18, 1949.38,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.88, 5,   coast,  -15.20,  67600.00, 3285.54, 1955.74,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.89, 5,   coast,  -13.24,  67591.00, 3286.58, 1956.78,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.90, 5,   coast,  -16.67,  67584.00, 3287.39, 1957.58,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.91, 5,   coast,  -17.65,  67570.00, 3289.00, 1959.20,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.92, 5,   coast,  -21.08,  67547.00, 3291.66, 1961.86,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.93, 5,   coast,  -14.22,  67516.00, 3295.25, 1965.44,     NaN, 33.7, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.94, 5,   coast,  -18.14,  67508.00, 3296.17, 1966.37,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.94, 5,   coast,  -18.14,  67508.00, 3296.17, 1966.37,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  64.21,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.95, 5,   coast,  -16.67,  67504.00, 3296.63, 1966.83,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.96, 5,   coast,  -17.65,  67487.00, 3298.60, 1968.80,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.97, 5,   coast,  -19.12,  67460.00, 3301.72, 1971.92,     NaN, 33.7, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.98, 5,   coast,  -15.20,  67446.00, 3303.34, 1973.54,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,     9.99, 5,   coast,  -16.18,  67434.00, 3304.73, 1974.93,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.00, 5,   coast,  -18.14,  67395.00, 3309.25, 1979.45,     NaN, 33.7, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.01, 5,   coast,  -15.20,  67397.00, 3309.02, 1979.22,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.02, 5,   coast,  -17.16,  67376.00, 3311.45, 1981.65,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.03, 5,   coast,  -15.20,  67345.00, 3315.04, 1985.24,     NaN, 33.7, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.04, 5,   coast,  -18.63,  67328.00, 3317.01, 1987.21,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.05, 5,   coast,  -16.18,  67302.00, 3320.02, 1990.22,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.06, 5,   coast,  -15.69,  67293.00, 3321.07, 1991.27,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.07, 5,   coast,  -17.16,  67275.00, 3323.15, 1993.35,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.08, 5,   coast,  -18.14,  67271.00, 3323.62, 1993.82,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.09, 5,   coast,  -18.14,  67244.00, 3326.75, 1996.95,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.10, 5,   coast,  -14.71,  67214.00, 3330.23, 2000.43,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.11, 5,   coast,  -16.18,  67197.00, 3332.21, 2002.40,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.12, 5,   coast,  -14.71,  67182.00, 3333.95, 2004.15,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.13, 5,   coast,  -14.71,  67147.00, 3338.01, 2008.21,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.14, 5,   coast,  -13.73,  67125.00, 3340.57, 2010.77,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.15, 5,   coast,  -13.24,  67109.00, 3342.43, 2012.63,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.16, 5,   coast,  -14.22,  67097.00, 3343.82, 2014.02,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.17, 5,   coast,  -17.65,  67074.00, 3346.49, 2016.69,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.18, 5,   coast,  -13.73,  67055.00, 3348.70, 2018.90,     NaN, 33.7, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.19, 5,   coast,  -14.71,  67015.00, 3353.36, 2023.55,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.20, 5,   coast,  -14.71,  67030.00, 3351.61, 2021.81,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.21, 5,   coast,  -17.16,  67005.00, 3354.52, 2024.72,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.22, 5,   coast,  -15.20,  66969.00, 3358.71, 2028.91,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.23, 5,   coast,  -15.20,  66956.00, 3360.22, 2030.42,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.24, 5,   coast,  -17.65,  66946.00, 3361.39, 2031.59,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.25, 5,   coast,  -14.71,  66914.00, 3365.11, 2035.31,     NaN, 33.8, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.26, 5,   coast,  -13.73,  66881.00, 3368.96, 2039.16,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.26, 5,   coast,  -13.73,  66881.00, 3368.96, 2039.16,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.27, 5,   coast,  -13.24,  66866.00, 3370.71, 2040.91,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.28, 5,   coast,  -15.20,  66850.00, 3372.57, 2042.77,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.29, 5,   coast,  -14.22,  66818.00, 3376.30, 2046.50,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.30, 5,   coast,  -18.14,  66813.00, 3376.89, 2047.08,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9402986,-106.9128861,  3350.0, 2022,  6, 24, 15, 17, 26,      162,     1963, 303,  85,   1.4,   0.9,   1.1,  0, 38, 32,  0,  0, 31,  0,  0,  0,  0, 38, 28, 30, 29,  0,  0, 32,  0, 33, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.31, 5,   coast,  -13.73,  66797.00, 3378.75, 2048.95,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.31, 5,   coast,  -13.73,  66797.00, 3378.75, 2048.95,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.31, 5,   coast,  -13.73,  66797.00, 3378.75, 2048.95,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.32, 5,   coast,  -16.18,  66787.00, 3379.92, 2050.12,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.33, 5,   coast,  -14.71,  66770.00, 3381.90, 2052.10,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.34, 5,   coast,  -14.71,  66738.00, 3385.64, 2055.84,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.35, 5,   coast,  -15.20,  66718.00, 3387.97, 2058.17,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.36, 5,   coast,  -14.71,  66692.00, 3391.01, 2061.21,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.37, 5,   coast,  -16.67,  66683.00, 3392.06, 2062.26,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.38, 5,   coast,  -19.12,  66675.00, 3392.99, 2063.19,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.39, 5,   coast,  -11.28,  66653.00, 3395.56, 2065.76,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.40, 5,   coast,  -15.20,  66629.00, 3398.37, 2068.57,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.41, 5,   coast,  -15.69,  66604.00, 3401.29, 2071.49,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.42, 5,   coast,  -14.22,  66591.00, 3402.81, 2073.01,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.43, 5,   coast,  -12.75,  66576.00, 3404.56, 2074.76,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.44, 5,   coast,  -17.16,  66553.00, 3407.26, 2077.45,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.45, 5,   coast,  -15.20,  66540.00, 3408.78, 2078.98,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.46, 5,   coast,  -15.20,  66528.00, 3410.18, 2080.38,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.47, 5,   coast,  -15.69,  66506.00, 3412.76, 2082.95,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.48, 5,   coast,  -14.22,  66486.00, 3415.10, 2085.30,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.49, 5,   coast,  -17.16,  66471.00, 3416.85, 2087.05,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.50, 5,   coast,  -15.20,  66460.00, 3418.14, 2088.34,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.51, 5,   coast,  -15.69,  66442.00, 3420.25, 2090.45,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.52, 5,   coast,  -16.18,  66426.00, 3422.12, 2092.32,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.53, 5,   coast,  -17.65,  66386.00, 3426.81, 2097.01,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.54, 5,   coast,  -16.18,  66372.00, 3428.45, 2098.65,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.55, 5,   coast,  -14.71,  66355.00, 3430.45, 2100.65,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.56, 5,   coast,  -15.20,  66331.00, 3433.26, 2103.46,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.57, 5,   coast,  -16.67,  66312.00, 3435.49, 2105.69,     NaN, 33.8, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.58, 5,   coast,  -16.18,  66287.00, 3438.43, 2108.63,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.58, 5,   coast,  -16.18,  66287.00, 3438.43, 2108.63,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.59, 5,   coast,  -15.20,  66286.00, 3438.54, 2108.74,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.60, 5,   coast,  -14.71,  66272.00, 3440.19, 2110.39,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.61, 5,   coast,  -14.22,  66242.00, 3443.71, 2113.91,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.62, 5,   coast,  -15.20,  66228.00, 3445.35, 2115.55,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.63, 5,   coast,  -13.73,  66215.00, 3446.88, 2117.08,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.64, 5,   coast,  -13.73,  66181.00, 3450.88, 2121.07,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.65, 5,   coast,  -16.18,  66162.00, 3453.11, 2123.31,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.66, 5,   coast,  -17.16,  66147.00, 3454.87, 2125.07,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.67, 5,   coast,  -13.73,  66129.00, 3456.99, 2127.19,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.68, 5,   coast,  -17.16,  66122.00, 3457.81, 2128.01,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.69, 5,   coast,  -18.14,  66097.00, 3460.75, 2130.95,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.70, 5,   coast,  -15.20,  66085.00, 3462.16, 2132.36,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.71, 5,   coast,  -15.69,  66064.00, 3464.64, 2134.83,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.72, 5,   coast,  -16.18,  66049.00, 3466.40, 2136.60,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.73, 5,   coast,  -13.24,  66030.00, 3468.64, 2138.84,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.74, 5,   coast,  -14.71,  66010.00, 3470.99, 2141.19,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.75, 5,   coast,  -17.16,  65987.00, 3473.70, 2143.90,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.76, 5,   coast,  -15.69,  65978.00, 3474.76, 2144.96,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.77, 5,   coast,  -16.67,  65953.00, 3477.71, 2147.91,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.78, 5,   coast,  -16.18,  65930.00, 3480.42, 2150.62,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.79, 5,   coast,  -12.75,  65926.00, 3480.89, 2151.09,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.80, 5,   coast,  -16.18,  65911.00, 3482.66, 2152.86,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.81, 5,   coast,  -15.69,  65877.00, 3486.67, 2156.87,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.82, 5,   coast,  -17.16,  65850.00, 3489.86, 2160.05,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.83, 5,   coast,  -14.71,  65833.00, 3491.86, 2162.06,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.84, 5,   coast,  -14.22,  65821.00, 3493.28, 2163.48,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.85, 5,   coast,  -13.24,  65810.00, 3494.58, 2164.78,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.86, 5,   coast,  -16.18,  65788.00, 3497.17, 2167.37,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.87, 5,   coast,  -15.69,  65787.00, 3497.29, 2167.49,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.88, 5,   coast,  -18.14,  65744.00, 3502.37, 2172.57,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.89, 5,   coast,  -18.14,  65724.00, 3504.74, 2174.93,     NaN, 33.8, 4.00, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.90, 5,   coast,  -16.18,  65722.00, 3504.97, 2175.17,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.90, 5,   coast,  -16.18,  65722.00, 3504.97, 2175.17,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.91,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.91, 5,   coast,  -15.20,  65708.00, 3506.63, 2176.83,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.92, 5,   coast,  -13.73,  65685.00, 3509.35, 2179.54,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.93, 5,   coast,  -15.20,  65670.00, 3511.12, 2181.32,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.94, 5,   coast,  -16.18,  65651.00, 3513.37, 2183.57,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.95, 5,   coast,  -14.22,  65636.00, 3515.14, 2185.34,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.96, 5,   coast,  -13.24,  65604.00, 3518.93, 2189.13,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.97, 5,   coast,  -10.79,  65613.00, 3517.86, 2188.06,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.98, 5,   coast,  -18.14,  65566.00, 3523.43, 2193.63,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    10.99, 5,   coast,  -17.65,  65552.00, 3525.09, 2195.28,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.00, 5,   coast,  -15.20,  65530.00, 3527.69, 2197.89,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.01, 5,   coast,  -15.20,  65536.00, 3526.98, 2197.18,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.02, 5,   coast,  -11.77,  65513.00, 3529.71, 2199.90,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.03, 5,   coast,  -13.73,  65489.00, 3532.55, 2202.75,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.04, 5,   coast,  -16.18,  65486.00, 3532.91, 2203.10,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.05, 5,   coast,  -11.77,  65459.00, 3536.11, 2206.31,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.06, 5,   coast,  -14.22,  65457.00, 3536.34, 2206.54,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.07, 5,   coast,  -14.22,  65433.00, 3539.19, 2209.39,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.08, 5,   coast,  -16.67,  65405.00, 3542.51, 2212.71,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.09, 5,   coast,  -16.67,  65393.00, 3543.94, 2214.13,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.10, 5,   coast,  -16.18,  65369.00, 3546.78, 2216.98,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.11, 5,   coast,  -16.67,  65353.00, 3548.68, 2218.88,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.12, 5,   coast,  -16.18,  65350.00, 3549.04, 2219.24,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.13, 5,   coast,  -15.69,  65325.00, 3552.01, 2222.21,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.14, 5,   coast,  -11.28,  65291.00, 3556.05, 2226.25,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.15, 5,   coast,  -14.71,  65290.00, 3556.17, 2226.37,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.16, 5,   coast,  -13.24,  65265.00, 3559.14, 2229.34,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.17, 5,   coast,  -13.24,  65250.00, 3560.92, 2231.12,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.18, 5,   coast,  -15.69,  65230.00, 3563.30, 2233.50,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.19, 5,   coast,  -15.69,  65223.00, 3564.13, 2234.33,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.20, 5,   coast,  -14.22,  65205.00, 3566.27, 2236.47,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.21, 5,   coast,  -15.20,  65192.00, 3567.82, 2238.02,     NaN, 33.8, 3.99, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.22, 5,   coast,  -18.14,  65158.00, 3571.86, 2242.06,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.22, 5,   coast,  -18.14,  65158.00, 3571.86, 2242.06,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.84,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.23, 5,   coast,  -14.22,  65151.00, 3572.70, 2242.90,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.24, 5,   coast,  -16.18,  65144.00, 3573.53, 2243.73,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.25, 5,   coast,  -16.18,  65113.00, 3577.22, 2247.42,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.26, 5,   coast,  -15.69,  65103.00, 3578.41, 2248.61,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.27, 5,   coast,  -13.24,  65078.00, 3581.39, 2251.59,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.28, 5,   coast,  -15.20,  65068.00, 3582.58, 2252.78,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.29, 5,   coast,  -15.20,  65031.00, 3586.99, 2257.19,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.30, 5,   coast,  -13.73,  65037.00, 3586.28, 2256.47,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9404084,-106.9131029,  3585.0, 2022,  6, 24, 15, 17, 27,      185,     2199, 303,  85,   1.4,   0.8,   1.1,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 24, 33, 26, 29,  0,  0, 37,  0, 33, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    11.31, 5,   coast,  -17.16,  65020.00, 3588.30, 2258.50,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.31, 5,   coast,  -17.16,  65020.00, 3588.30, 2258.50,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.31, 5,   coast,  -17.16,  65020.00, 3588.30, 2258.50,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.32, 5,   coast,  -15.20,  64989.00, 3592.00, 2262.20,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.33, 5,   coast,  -16.18,  64978.00, 3593.31, 2263.51,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.34, 5,   coast,  -14.22,  64965.00, 3594.86, 2265.06,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.35, 5,   coast,  -11.77,  64945.00, 3597.25, 2267.45,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.36, 5,   coast,  -16.67,  64930.00, 3599.04, 2269.24,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.37, 5,   coast,  -12.75,  64915.00, 3600.83, 2271.03,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.38, 5,   coast,  -13.24,  64903.00, 3602.26, 2272.46,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.39, 5,   coast,  -12.75,  64880.00, 3605.01, 2275.21,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.40, 5,   coast,  -12.75,  64851.00, 3608.47, 2278.67,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.41, 5,   coast,  -16.18,  64845.00, 3609.19, 2279.39,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.42, 5,   coast,  -16.18,  64816.00, 3612.65, 2282.85,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.43, 5,   coast,  -15.20,  64797.00, 3614.93, 2285.12,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.44, 5,   coast,  -14.22,  64792.00, 3615.52, 2285.72,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.45, 5,   coast,  -15.20,  64775.00, 3617.56, 2287.75,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.46, 5,   coast,  -14.22,  64754.00, 3620.07, 2290.27,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.47, 5,   coast,  -15.20,  64729.00, 3623.06, 2293.26,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.48, 5,   coast,  -12.26,  64717.00, 3624.49, 2294.69,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.49, 5,   coast,  -12.75,  64712.00, 3625.09, 2295.29,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.50, 5,   coast,  -13.73,  64674.00, 3629.64, 2299.84,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.51, 5,   coast,  -13.73,  64672.00, 3629.88, 2300.08,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.52, 5,   coast,  -14.71,  64646.00, 3633.00, 2303.19,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.53, 5,   coast,  -15.69,  64635.00, 3634.31, 2304.51,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.54, 5,   coast,  -13.73,  64620.00, 3636.11, 2306.31,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.54, 5,   coast,  -13.73,  64620.00, 3636.11, 2306.31,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.55, 5,   coast,  -16.67,  64600.00, 3638.51, 2308.71,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.56, 5,   coast,  -12.26,  64586.00, 3640.18, 2310.38,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.57, 5,   coast,  -17.16,  64571.00, 3641.98, 2312.18,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.58, 5,   coast,  -14.71,  64539.00, 3645.82, 2316.02,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.59, 5,   coast,  -10.79,  64534.00, 3646.42, 2316.62,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.60, 5,   coast,  -12.75,  64526.00, 3647.38, 2317.58,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.61, 5,   coast,  -13.73,  64493.00, 3651.34, 2321.54,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.62, 5,   coast,  -15.20,  64479.00, 3653.02, 2323.22,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.63, 5,   coast,  -11.77,  64463.00, 3654.94, 2325.14,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.64, 5,   coast,  -15.69,  64457.00, 3655.66, 2325.86,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.65, 5,   coast,  -15.69,  64424.00, 3659.62, 2329.82,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.66, 5,   coast,  -15.69,  64418.00, 3660.34, 2330.54,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.67, 5,   coast,  -15.69,  64402.00, 3662.27, 2332.47,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.68, 5,   coast,  -14.71,  64399.00, 3662.63, 2332.83,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.69, 5,   coast,  -16.18,  64361.00, 3667.19, 2337.39,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.70, 5,   coast,  -15.20,  64343.00, 3669.36, 2339.56,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.71, 5,   coast,  -13.24,  64351.00, 3668.40, 2338.59,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.72, 5,   coast,  -14.71,  64316.00, 3672.60, 2342.80,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.73, 5,   coast,  -15.69,  64302.00, 3674.29, 2344.49,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.74, 5,   coast,  -12.75,  64296.00, 3675.01, 2345.21,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.75, 5,   coast,  -12.26,  64267.00, 3678.50, 2348.70,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.76, 5,   coast,  -15.20,  64254.00, 3680.06, 2350.26,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.77, 5,   coast,  -12.75,  64238.00, 3681.99, 2352.19,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.78, 5,   coast,  -13.24,  64217.00, 3684.52, 2354.72,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.79, 5,   coast,  -12.26,  64206.00, 3685.84, 2356.04,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.80, 5,   coast,  -15.69,  64190.00, 3687.77, 2357.97,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.81, 5,   coast,  -15.69,  64170.00, 3690.18, 2360.38,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.82, 5,   coast,  -15.69,  64157.00, 3691.75, 2361.95,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.83, 5,   coast,  -14.22,  64129.00, 3695.12, 2365.32,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.84, 5,   coast,  -18.14,  64113.00, 3697.05, 2367.25,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.85, 5,   coast,  -16.67,  64102.00, 3698.38, 2368.58,     NaN, 33.8, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.86, 5,   coast,  -13.73,  64089.00, 3699.95, 2370.15,     NaN, 33.8, 4.00, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.86, 5,   coast,  -13.73,  64089.00, 3699.95, 2370.15,     NaN, 33.8, 4.00, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.87, 5,   coast,  -12.75,  64059.00, 3703.57, 2373.76,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.88, 5,   coast,  -13.73,  64049.00, 3704.77, 2374.97,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.89, 5,   coast,  -13.73,  64050.00, 3704.65, 2374.85,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.90, 5,   coast,  -13.24,  64016.00, 3708.76, 2378.95,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.91, 5,   coast,  -12.26,  64002.00, 3710.45, 2380.65,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.92, 5,   coast,  -16.67,  64008.00, 3709.72, 2379.92,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.93, 5,   coast,  -12.75,  63987.00, 3712.26, 2382.46,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.94, 5,   coast,  -17.16,  63960.00, 3715.52, 2385.72,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.95, 5,   coast,  -12.75,  63951.00, 3716.61, 2386.81,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.96, 5,   coast,  -17.65,  63936.00, 3718.42, 2388.62,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.97, 5,   coast,  -13.73,  63930.00, 3719.14, 2389.34,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.98, 5,   coast,  -13.24,  63895.00, 3723.38, 2393.57,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    11.99, 5,   coast,  -12.26,  63890.00, 3723.98, 2394.18,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.00, 5,   coast,  -15.69,  63877.00, 3725.55, 2395.75,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.01, 5,   coast,  -16.67,  63881.00, 3725.07, 2395.27,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.02, 5,   coast,  -10.79,  63843.00, 3729.67, 2399.86,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.03, 5,   coast,  -12.75,  63844.00, 3729.54, 2399.74,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.04, 5,   coast,  -17.16,  63807.00, 3734.02, 2404.22,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.05, 5,   coast,  -14.71,  63792.00, 3735.84, 2406.04,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.06, 5,   coast,  -14.22,  63782.00, 3737.05, 2407.25,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.07, 5,   coast,  -15.20,  63766.00, 3738.99, 2409.19,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.08, 5,   coast,  -17.16,  63740.00, 3742.14, 2412.34,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.09, 5,   coast,  -13.73,  63729.00, 3743.47, 2413.67,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.10, 5,   coast,  -14.22,  63714.00, 3745.29, 2415.49,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.11, 5,   coast,  -14.71,  63691.00, 3748.08, 2418.27,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.12, 5,   coast,  -13.24,  63670.00, 3750.62, 2420.82,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.13, 5,   coast,  -18.63,  63655.00, 3752.44, 2422.64,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.14, 5,   coast,  -13.73,  63655.00, 3752.44, 2422.64,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.15, 5,   coast,  -12.75,  63632.00, 3755.23, 2425.43,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.16, 5,   coast,  -15.69,  63615.00, 3757.29, 2427.49,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.17, 5,   coast,  -15.20,  63594.00, 3759.84, 2430.04,     NaN, 33.8, 4.00, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.18, 5,   coast,  -15.20,  63586.00, 3760.81, 2431.01,     NaN, 33.8, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.18, 5,   coast,  -15.20,  63586.00, 3760.81, 2431.01,     NaN, 33.8, 4.00, 3.99, 3.99,   0.08,   0.00,   0.00,  64.15,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.19, 5,   coast,  -13.24,  63568.00, 3763.00, 2433.20,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.20, 5,   coast,  -13.24,  63552.00, 3764.94, 2435.14,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.21, 5,   coast,  -13.73,  63543.00, 3766.03, 2436.23,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.22, 5,   coast,  -14.22,  63521.00, 3768.71, 2438.91,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.23, 5,   coast,  -13.24,  63512.00, 3769.80, 2440.00,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.24, 5,   coast,  -15.20,  63494.00, 3771.99, 2442.19,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.25, 5,   coast,  -13.24,  63464.00, 3775.63, 2445.83,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.26, 5,   coast,  -14.71,  63462.00, 3775.88, 2446.08,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.27, 5,   coast,  -15.69,  63431.00, 3779.65, 2449.85,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.28, 5,   coast,  -13.24,  63416.00, 3781.47, 2451.67,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.29, 5,   coast,  -13.24,  63405.00, 3782.81, 2453.01,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.30, 5,   coast,  -12.75,  63413.00, 3781.84, 2452.04,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9405044,-106.9133132,  3798.0, 2022,  6, 24, 15, 17, 28,      207,     2413, 302,  85,   1.4,   0.8,   1.1,  0, 32, 29,  0,  0, 27,  0,  0,  0,  0, 31, 34, 31, 28,  0,  0, 25,  0, 32, 33,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    12.31, 5,   coast,  -13.24,  63387.00, 3785.00, 2455.20,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.31, 5,   coast,  -13.24,  63387.00, 3785.00, 2455.20,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.31, 5,   coast,  -13.24,  63387.00, 3785.00, 2455.20,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.32, 5,   coast,  -14.22,  63363.00, 3787.92, 2458.12,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.33, 5,   coast,  -15.69,  63347.00, 3789.87, 2460.07,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.34, 5,   coast,  -14.22,  63335.00, 3791.33, 2461.53,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.35, 5,   coast,  -13.73,  63322.00, 3792.92, 2463.11,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.36, 5,   coast,  -12.26,  63313.00, 3794.01, 2464.21,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.37, 5,   coast,  -12.75,  63292.00, 3796.57, 2466.77,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.38, 5,   coast,  -10.30,  63281.00, 3797.91, 2468.11,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.39, 5,   coast,  -15.20,  63263.00, 3800.10, 2470.30,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.40, 5,   coast,  -13.73,  63241.00, 3802.79, 2472.99,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.41, 5,   coast,  -12.26,  63230.00, 3804.13, 2474.33,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.42, 5,   coast,  -14.71,  63213.00, 3806.20, 2476.40,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.43, 5,   coast,  -14.22,  63196.00, 3808.27, 2478.47,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.44, 5,   coast,  -14.71,  63187.00, 3809.37, 2479.57,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.45, 5,   coast,  -19.12,  63169.00, 3811.57, 2481.77,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.46, 5,   coast,  -13.24,  63168.00, 3811.69, 2481.89,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.47, 5,   coast,  -17.65,  63144.00, 3814.62, 2484.82,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.48, 5,   coast,  -12.75,  63121.00, 3817.43, 2487.63,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.49, 5,   coast,  -15.69,  63095.00, 3820.60, 2490.80,     NaN, 33.8, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.50, 5,   coast,  -14.71,  63089.00, 3821.34, 2491.54,     NaN, 33.8, 3.98, 3.97, 3.97,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.50, 5,   coast,  -14.71,  63089.00, 3821.34, 2491.54,     NaN, 33.8, 3.98, 3.97, 3.97,   0.03,   0.00,   0.00,  64.27,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.51, 5,   coast,  -15.69,  63072.00, 3823.41, 2493.61,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.52, 5,   coast,  -15.20,  63070.00, 3823.66, 2493.86,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.53, 5,   coast,  -11.28,  63045.00, 3826.71, 2496.91,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.54, 5,   coast,  -15.20,  63032.00, 3828.30, 2498.50,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.55, 5,   coast,  -13.73,  63010.00, 3830.99, 2501.19,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.56, 5,   coast,  -11.77,  62994.00, 3832.95, 2503.15,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.57, 5,   coast,  -14.71,  62977.00, 3835.03, 2505.23,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.58, 5,   coast,  -14.22,  62979.00, 3834.79, 2504.98,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.59, 5,   coast,  -11.28,  62974.00, 3835.40, 2505.60,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.60, 5,   coast,  -13.24,  62945.00, 3838.95, 2509.15,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.61, 5,   coast,  -13.24,  62935.00, 3840.17, 2510.37,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.62, 5,   coast,  -13.24,  62916.00, 3842.50, 2512.70,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.63, 5,   coast,  -11.77,  62893.00, 3845.31, 2515.51,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.64, 5,   coast,  -12.26,  62878.00, 3847.15, 2517.35,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.65, 5,   coast,  -13.73,  62854.00, 3850.09, 2520.29,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.66, 5,   coast,  -13.73,  62840.00, 3851.81, 2522.01,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.67, 5,   coast,  -12.75,  62837.00, 3852.17, 2522.37,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.68, 5,   coast,  -13.73,  62829.00, 3853.15, 2523.35,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.69, 5,   coast,  -14.22,  62814.00, 3854.99, 2525.19,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.70, 5,   coast,  -14.71,  62793.00, 3857.57, 2527.77,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.71, 5,   coast,  -15.69,  62782.00, 3858.92, 2529.12,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.72, 5,   coast,  -10.79,  62768.00, 3860.63, 2530.83,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.73, 5,   coast,  -14.71,  62745.00, 3863.46, 2533.66,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.74, 5,   coast,  -15.69,  62735.00, 3864.68, 2534.88,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.75, 5,   coast,  -15.69,  62725.00, 3865.91, 2536.11,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.76, 5,   coast,  -13.73,  62714.00, 3867.26, 2537.46,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.77, 5,   coast,  -10.79,  62683.00, 3871.07, 2541.27,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.78, 5,   coast,  -17.65,  62684.00, 3870.94, 2541.14,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.79, 5,   coast,  -15.20,  62667.00, 3873.03, 2543.23,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.80, 5,   coast,  -12.75,  62646.00, 3875.61, 2545.81,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.81, 5,   coast,  -13.73,  62641.00, 3876.23, 2546.43,     NaN, 33.8, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.82, 5,   coast,  -14.22,  62617.00, 3879.18, 2549.38,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.82, 5,   coast,  -14.22,  62617.00, 3879.18, 2549.38,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  63.91,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.83, 5,   coast,  -16.67,  62610.00, 3880.04, 2550.24,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.84, 5,   coast,  -14.71,  62585.00, 3883.11, 2553.31,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.85, 5,   coast,  -14.71,  62566.00, 3885.45, 2555.65,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.86, 5,   coast,  -17.16,  62567.00, 3885.32, 2555.52,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.87, 5,   coast,  -12.26,  62549.00, 3887.54, 2557.74,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.88, 5,   coast,  -14.22,  62538.00, 3888.89, 2559.09,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.89, 5,   coast,  -14.71,  62524.00, 3890.61, 2560.81,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.90, 5,   coast,  -12.26,  62494.00, 3894.31, 2564.51,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.91, 5,   coast,  -13.73,  62487.00, 3895.17, 2565.37,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.92, 5,   coast,  -12.75,  62485.00, 3895.41, 2565.61,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.93, 5,   coast,  -13.24,  62454.00, 3899.23, 2569.43,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.94, 5,   coast,  -12.75,  62454.00, 3899.23, 2569.43,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.95, 5,   coast,  -11.77,  62430.00, 3902.19, 2572.39,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.96, 5,   coast,  -13.73,  62418.00, 3903.67, 2573.87,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.97, 5,   coast,  -14.71,  62413.00, 3904.28, 2574.48,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.98, 5,   coast,  -11.77,  62378.00, 3908.60, 2578.80,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    12.99, 5,   coast,  -15.69,  62383.00, 3907.98, 2578.18,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.00, 5,   coast,  -13.24,  62357.00, 3911.19, 2581.39,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.01, 5,   coast,  -14.71,  62342.00, 3913.04, 2583.24,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.02, 5,   coast,  -13.24,  62333.00, 3914.15, 2584.35,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.03, 5,   coast,  -14.71,  62306.00, 3917.48, 2587.68,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.04, 5,   coast,  -11.77,  62303.00, 3917.85, 2588.05,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.05, 5,   coast,  -12.26,  62279.00, 3920.81, 2591.01,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.06, 5,   coast,  -10.79,  62274.00, 3921.43, 2591.63,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.07, 5,   coast,  -11.28,  62249.00, 3924.52, 2594.72,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.08, 5,   coast,  -14.22,  62241.00, 3925.50, 2595.70,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.09, 5,   coast,  -14.71,  62228.00, 3927.11, 2597.31,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.10, 5,   coast,  -14.22,  62209.00, 3929.46, 2599.66,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.11, 5,   coast,  -11.28,  62214.00, 3928.84, 2599.04,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.12, 5,   coast,  -12.75,  62203.00, 3930.20, 2600.40,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.13, 5,   coast,  -12.26,  62192.00, 3931.56, 2601.76,     NaN, 33.8, 4.01, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.14, 5,   coast,  -13.24,  62158.00, 3935.76, 2605.96,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.14, 5,   coast,  -13.24,  62158.00, 3935.76, 2605.96,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.21,  64.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.15, 5,   coast,  -12.26,  62158.00, 3935.76, 2605.96,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.16, 5,   coast,  -14.71,  62109.00, 3941.82, 2612.02,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.17, 5,   coast,  -15.20,  62110.00, 3941.70, 2611.90,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.18, 5,   coast,  -12.26,  62093.00, 3943.80, 2614.00,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.19, 5,   coast,  -15.20,  62074.00, 3946.15, 2616.35,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.20, 5,   coast,  -13.24,  62066.00, 3947.14, 2617.34,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.21, 5,   coast,  -14.22,  62066.00, 3947.14, 2617.34,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.22, 5,   coast,  -16.18,  62041.00, 3950.24, 2620.44,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.23, 5,   coast,  -13.24,  62023.00, 3952.47, 2622.67,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.24, 5,   coast,  -13.24,  62015.00, 3953.46, 2623.66,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.25, 5,   coast,   -9.81,  62002.00, 3955.07, 2625.27,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.26, 5,   coast,  -13.24,  61978.00, 3958.04, 2628.24,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.27, 5,   coast,  -10.79,  61974.00, 3958.54, 2628.74,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.28, 5,   coast,  -13.24,  61957.00, 3960.65, 2630.85,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.29, 5,   coast,  -15.20,  61943.00, 3962.38, 2632.58,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.30, 5,   coast,  -10.79,  61926.00, 3964.49, 2634.69,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9405996,-106.9135024,  3995.0, 2022,  6, 24, 15, 17, 29,      228,     2611, 302,  85,   1.6,   0.9,   1.3,  0, 27, 28,  0,  0, 27,  0,  0,  0,  0, 25, 28, 31, 35,  0,  0, 34,  0, 32, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    13.31, 5,   coast,  -14.71,  61899.00, 3967.84, 2638.04,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.31, 5,   coast,  -14.71,  61899.00, 3967.84, 2638.04,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.31, 5,   coast,  -14.71,  61899.00, 3967.84, 2638.04,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.32, 5,   coast,  -12.26,  61911.00, 3966.35, 2636.55,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.33, 5,   coast,  -14.22,  61897.00, 3968.09, 2638.29,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.34, 5,   coast,  -12.75,  61884.00, 3969.70, 2639.90,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.35, 5,   coast,  -13.24,  61875.00, 3970.82, 2641.02,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.36, 5,   coast,  -14.71,  61845.00, 3974.54, 2644.74,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.37, 5,   coast,  -10.79,  61838.00, 3975.41, 2645.61,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.38, 5,   coast,  -11.28,  61810.00, 3978.89, 2649.09,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.39, 5,   coast,  -12.75,  61800.00, 3980.13, 2650.33,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.40, 5,   coast,  -13.73,  61780.00, 3982.62, 2652.82,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.41, 5,   coast,  -14.71,  61779.00, 3982.74, 2652.94,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.42, 5,   coast,  -11.28,  61765.00, 3984.48, 2654.68,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.43, 5,   coast,  -11.77,  61750.00, 3986.34, 2656.54,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.44, 5,   coast,  -13.24,  61742.00, 3987.34, 2657.54,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.45, 5,   coast,  -10.30,  61721.00, 3989.95, 2660.15,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.46, 5,   coast,  -12.75,  61712.00, 3991.07, 2661.27,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.46, 5,   coast,  -12.75,  61712.00, 3991.07, 2661.27,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.47, 5,   coast,  -10.30,  61696.00, 3993.06, 2663.26,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.48, 5,   coast,  -15.20,  61688.00, 3994.05, 2664.25,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.49, 5,   coast,  -14.22,  61672.00, 3996.05, 2666.24,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.50, 5,   coast,  -12.75,  61661.00, 3997.41, 2667.61,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.51, 5,   coast,  -14.22,  61631.00, 4001.15, 2671.35,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.52, 5,   coast,  -12.26,  61631.00, 4001.15, 2671.35,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.53, 5,   coast,  -11.77,  61622.00, 4002.27, 2672.47,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.54, 5,   coast,  -12.75,  61603.00, 4004.64, 2674.83,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.55, 5,   coast,  -13.73,  61581.00, 4007.38, 2677.58,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.56, 5,   coast,  -13.24,  61576.00, 4008.00, 2678.20,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.57, 5,   coast,  -11.28,  61567.00, 4009.12, 2679.32,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.58, 5,   coast,  -10.30,  61539.00, 4012.61, 2682.81,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.59, 5,   coast,  -13.24,  61540.00, 4012.49, 2682.68,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.60, 5,   coast,  -13.73,  61512.00, 4015.98, 2686.18,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.61, 5,   coast,  -11.28,  61508.00, 4016.48, 2686.67,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.62, 5,   coast,  -12.26,  61484.00, 4019.47, 2689.67,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.63, 5,   coast,  -12.75,  61481.00, 4019.84, 2690.04,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.64, 5,   coast,  -12.75,  61473.00, 4020.84, 2691.04,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.65, 5,   coast,  -12.26,  61457.00, 4022.84, 2693.04,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.66, 5,   coast,  -13.73,  61441.00, 4024.83, 2695.03,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.67, 5,   coast,  -12.75,  61431.00, 4026.08, 2696.28,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.68, 5,   coast,  -13.24,  61407.00, 4029.08, 2699.28,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.69, 5,   coast,  -11.28,  61390.00, 4031.20, 2701.40,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.70, 5,   coast,  -13.73,  61378.00, 4032.70, 2702.90,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.71, 5,   coast,  -16.18,  61370.00, 4033.70, 2703.90,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.72, 5,   coast,  -12.26,  61363.00, 4034.57, 2704.77,     NaN, 33.9, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.73, 5,   coast,  -12.75,  61357.00, 4035.32, 2705.52,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.74, 5,   coast,  -10.79,  61316.00, 4040.45, 2710.65,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.75, 5,   coast,  -13.24,  61314.00, 4040.70, 2710.90,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.76, 5,   coast,  -14.22,  61310.00, 4041.20, 2711.40,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.77, 5,   coast,  -12.75,  61280.00, 4044.95, 2715.15,     NaN, 33.8, 3.98, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.78, 5,   coast,  -15.69,  61277.00, 4045.33, 2715.52,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.78, 5,   coast,  -15.69,  61277.00, 4045.33, 2715.52,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.79, 5,   coast,  -13.73,  61256.00, 4047.95, 2718.15,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.80, 5,   coast,  -14.22,  61247.00, 4049.08, 2719.28,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.81, 5,   coast,  -13.24,  61236.00, 4050.46, 2720.65,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.82, 5,   coast,  -11.77,  61223.00, 4052.08, 2722.28,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.83, 5,   coast,  -14.22,  61203.00, 4054.59, 2724.79,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.84, 5,   coast,  -15.69,  61199.00, 4055.09, 2725.29,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.85, 5,   coast,  -11.28,  61183.00, 4057.09, 2727.29,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.86, 5,   coast,  -11.77,  61161.00, 4059.85, 2730.05,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.87, 5,   coast,  -11.28,  61152.00, 4060.97, 2731.17,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.88, 5,   coast,  -11.28,  61143.00, 4062.10, 2732.30,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.89, 5,   coast,  -13.24,  61124.00, 4064.48, 2734.68,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.90, 5,   coast,  -12.75,  61122.00, 4064.73, 2734.93,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.91, 5,   coast,  -10.79,  61106.00, 4066.74, 2736.94,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.92, 5,   coast,  -13.73,  61096.00, 4067.99, 2738.19,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.93, 5,   coast,  -15.20,  61072.00, 4071.00, 2741.20,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.94, 5,   coast,  -11.77,  61074.00, 4070.75, 2740.95,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.95, 5,   coast,  -14.22,  61047.00, 4074.14, 2744.34,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.96, 5,   coast,  -15.69,  61036.00, 4075.52, 2745.72,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.97, 5,   coast,  -13.73,  61036.00, 4075.52, 2745.72,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.98, 5,   coast,  -12.26,  61033.00, 4075.90, 2746.09,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    13.99, 5,   coast,  -13.73,  61017.00, 4077.90, 2748.10,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.00, 5,   coast,  -12.26,  60988.00, 4081.54, 2751.74,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.01, 5,   coast,  -12.75,  60965.00, 4084.43, 2754.63,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.02, 5,   coast,  -12.26,  60966.00, 4084.31, 2754.51,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.03, 5,   coast,  -14.22,  60942.00, 4087.32, 2757.52,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.04, 5,   coast,  -10.30,  60936.00, 4088.08, 2758.28,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.05, 5,   coast,  -12.75,  60917.00, 4090.46, 2760.66,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.06, 5,   coast,  -14.22,  60915.00, 4090.72, 2760.91,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.07, 5,   coast,  -10.79,  60911.00, 4091.22, 2761.42,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.08, 5,   coast,  -11.28,  60884.00, 4094.61, 2764.81,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.09, 5,   coast,  -14.22,  60889.00, 4093.98, 2764.18,     NaN, 33.8, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.10, 5,   coast,  -12.75,  60859.00, 4097.76, 2767.96,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.10, 5,   coast,  -12.75,  60859.00, 4097.76, 2767.96,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.11, 5,   coast,  -11.77,  60855.00, 4098.26, 2768.46,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.12, 5,   coast,  -11.77,  60842.00, 4099.89, 2770.09,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.13, 5,   coast,  -12.26,  60827.00, 4101.78, 2771.98,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.14, 5,   coast,  -11.28,  60814.00, 4103.42, 2773.62,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.15, 5,   coast,  -11.77,  60811.00, 4103.80, 2773.99,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.16, 5,   coast,  -11.77,  60798.00, 4105.43, 2775.63,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.17, 5,   coast,  -13.24,  60780.00, 4107.70, 2777.90,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.18, 5,   coast,  -13.24,  60756.00, 4110.72, 2780.92,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.19, 5,   coast,  -12.26,  60759.00, 4110.34, 2780.54,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.20, 5,   coast,  -14.22,  60736.00, 4113.24, 2783.44,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.21, 5,   coast,  -10.79,  60736.00, 4113.24, 2783.44,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.22, 5,   coast,  -12.75,  60716.00, 4115.76, 2785.96,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.23, 5,   coast,   -9.32,  60701.00, 4117.65, 2787.85,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.24, 5,   coast,  -11.77,  60690.00, 4119.04, 2789.24,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.25, 5,   coast,  -11.28,  60669.00, 4121.68, 2791.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.26, 5,   coast,  -11.77,  60668.00, 4121.81, 2792.01,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.27, 5,   coast,  -11.28,  60639.00, 4125.47, 2795.67,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.28, 5,   coast,  -12.75,  60638.00, 4125.59, 2795.79,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.29, 5,   coast,  -12.75,  60626.00, 4127.11, 2797.31,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.30, 5,   coast,  -10.30,  60604.00, 4129.88, 2800.08,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.31, 5,   coast,  -13.24,  60585.00, 4132.28, 2802.48,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.31, 5,   coast,  -13.24,  60585.00, 4132.28, 2802.48,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.31, 5,   coast,  -13.24,  60585.00, 4132.28, 2802.48,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9406937,-106.9137032,  4184.0, 2022,  6, 24, 15, 17, 30,      249,     2801, 302,  85,   1.4,   0.9,   1.1,  0, 33, 29,  0,  0, 37,  0,  0,  0,  0, 30, 36, 32, 28,  0,  0, 29,  0, 28, 29,  0,  0,  0, 37,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.32, 5,   coast,  -12.26,  60590.00, 4131.65, 2801.85,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.33, 5,   coast,  -12.75,  60567.00, 4134.56, 2804.75,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.34, 5,   coast,   -9.81,  60573.00, 4133.80, 2804.00,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.35, 5,   coast,  -13.73,  60554.00, 4136.20, 2806.40,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.36, 5,   coast,  -11.28,  60540.00, 4137.97, 2808.16,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.37, 5,   coast,   -9.81,  60527.00, 4139.61, 2809.81,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.38, 5,   coast,   -9.81,  60530.00, 4139.23, 2809.43,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.39, 5,   coast,  -14.71,  60504.00, 4142.51, 2812.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.40, 5,   coast,  -14.71,  60495.00, 4143.65, 2813.85,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.41, 5,   coast,  -13.24,  60490.00, 4144.28, 2814.48,     NaN, 33.8, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.42, 5,   coast,  -11.77,  60465.00, 4147.44, 2817.64,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.42, 5,   coast,  -11.77,  60465.00, 4147.44, 2817.64,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.43, 5,   coast,  -12.26,  60451.00, 4149.21, 2819.41,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.44, 5,   coast,  -15.20,  60437.00, 4150.99, 2821.18,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.45, 5,   coast,  -12.75,  60427.00, 4152.25, 2822.45,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.46, 5,   coast,  -11.28,  60426.00, 4152.38, 2822.58,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.47, 5,   coast,  -14.22,  60412.00, 4154.15, 2824.35,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.48, 5,   coast,  -12.75,  60378.00, 4158.45, 2828.65,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.49, 5,   coast,  -11.77,  60370.00, 4159.46, 2829.66,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.50, 5,   coast,  -12.26,  60369.00, 4159.59, 2829.79,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.51, 5,   coast,  -13.73,  60344.00, 4162.76, 2832.96,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.52, 5,   coast,  -13.24,  60331.00, 4164.40, 2834.60,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.53, 5,   coast,  -12.75,  60316.00, 4166.30, 2836.50,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.54, 5,   coast,  -10.30,  60318.00, 4166.05, 2836.25,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.55, 5,   coast,  -12.26,  60300.00, 4168.33, 2838.53,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.56, 5,   coast,  -10.30,  60285.00, 4170.23, 2840.43,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.57, 5,   coast,  -13.73,  60267.00, 4172.51, 2842.71,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.58, 5,   coast,  -11.77,  60264.00, 4172.89, 2843.09,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.59, 5,   coast,  -14.22,  60257.00, 4173.78, 2843.98,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.60, 5,   coast,  -10.79,  60244.00, 4175.43, 2845.63,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.61, 5,   coast,  -11.77,  60234.00, 4176.70, 2846.90,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.62, 5,   coast,  -10.30,  60216.00, 4178.98, 2849.18,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.63, 5,   coast,  -13.24,  60205.00, 4180.38, 2850.58,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.64, 5,   coast,  -12.75,  60198.00, 4181.27, 2851.46,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.65, 5,   coast,  -15.20,  60200.00, 4181.01, 2851.21,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.66, 5,   coast,  -15.69,  60173.00, 4184.44, 2854.64,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.67, 5,   coast,  -12.26,  60162.00, 4185.83, 2856.03,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.68, 5,   coast,  -12.75,  60153.00, 4186.98, 2857.18,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.69, 5,   coast,  -13.24,  60120.00, 4191.17, 2861.37,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.70, 5,   coast,  -12.26,  60137.00, 4189.01, 2859.21,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.71, 5,   coast,  -12.26,  60114.00, 4191.93, 2862.13,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.72, 5,   coast,  -14.71,  60090.00, 4194.98, 2865.18,     NaN, 33.8, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.73, 5,   coast,   -9.81,  60097.00, 4194.09, 2864.29,     NaN, 33.9, 3.97, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.74, 5,   coast,  -11.77,  60082.00, 4196.00, 2866.20,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.74, 5,   coast,  -11.77,  60082.00, 4196.00, 2866.20,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  63.91,  63.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.75, 5,   coast,  -13.24,  60075.00, 4196.89, 2867.09,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.76, 5,   coast,  -14.71,  60064.00, 4198.28, 2868.48,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.77, 5,   coast,  -12.26,  60046.00, 4200.57, 2870.77,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.78, 5,   coast,  -15.20,  60045.00, 4200.70, 2870.90,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.79, 5,   coast,  -13.24,  60019.00, 4204.01, 2874.21,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.80, 5,   coast,  -12.75,  60006.00, 4205.66, 2875.86,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.81, 5,   coast,  -12.75,  60007.00, 4205.53, 2875.73,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.82, 5,   coast,  -12.75,  59978.00, 4209.22, 2879.42,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.83, 5,   coast,  -11.28,  59974.00, 4209.73, 2879.93,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.84, 5,   coast,  -11.77,  59961.00, 4211.39, 2881.59,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.85, 5,   coast,  -13.73,  59947.00, 4213.17, 2883.37,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.86, 5,   coast,  -12.75,  59945.00, 4213.42, 2883.62,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.87, 5,   coast,  -12.26,  59917.00, 4216.99, 2887.19,     NaN, 33.8, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.88, 5,   coast,  -11.28,  59915.00, 4217.25, 2887.44,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.89, 5,   coast,  -15.69,  59892.00, 4220.18, 2890.37,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.90, 5,   coast,  -11.77,  59894.00, 4219.92, 2890.12,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.91, 5,   coast,  -11.28,  59871.00, 4222.85, 2893.05,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.92, 5,   coast,  -11.28,  59854.00, 4225.02, 2895.22,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.93, 5,   coast,  -13.73,  59849.00, 4225.66, 2895.86,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.94, 5,   coast,  -13.24,  59836.00, 4227.31, 2897.51,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.95, 5,   coast,  -15.20,  59824.00, 4228.84, 2899.04,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.96, 5,   coast,  -10.79,  59810.00, 4230.63, 2900.83,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.97, 5,   coast,  -12.75,  59803.00, 4231.52, 2901.72,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.98, 5,   coast,  -14.22,  59800.00, 4231.91, 2902.11,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    14.99, 5,   coast,  -11.28,  59779.00, 4234.59, 2904.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.00, 5,   coast,  -12.26,  59756.00, 4237.52, 2907.72,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.01, 5,   coast,  -12.75,  59743.00, 4239.18, 2909.38,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.02, 5,   coast,  -13.24,  59732.00, 4240.59, 2910.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.03, 5,   coast,  -11.28,  59726.00, 4241.35, 2911.55,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.04, 5,   coast,  -14.71,  59702.00, 4244.42, 2914.62,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.05, 5,   coast,   -9.81,  59686.00, 4246.46, 2916.66,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.06, 5,   coast,  -13.24,  59695.00, 4245.31, 2915.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.06, 5,   coast,  -13.24,  59695.00, 4245.31, 2915.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.07, 5,   coast,  -12.26,  59675.00, 4247.87, 2918.07,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.08, 5,   coast,  -13.73,  59653.00, 4250.68, 2920.88,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.09, 5,   coast,  -13.24,  59646.00, 4251.57, 2921.77,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.10, 5,   coast,  -11.28,  59644.00, 4251.83, 2922.03,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.11, 5,   coast,  -12.75,  59630.00, 4253.62, 2923.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.12, 5,   coast,  -11.77,  59611.00, 4256.05, 2926.25,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.13, 5,   coast,  -13.73,  59611.00, 4256.05, 2926.25,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.14, 5,   coast,  -11.28,  59592.00, 4258.48, 2928.68,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.15, 5,   coast,  -12.26,  59566.00, 4261.81, 2932.01,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.16, 5,   coast,  -12.75,  59549.00, 4263.98, 2934.18,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.17, 5,   coast,  -11.77,  59554.00, 4263.34, 2933.54,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.18, 5,   coast,  -12.75,  59546.00, 4264.37, 2934.57,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.19, 5,   coast,  -11.77,  59542.00, 4264.88, 2935.08,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.20, 5,   coast,  -11.28,  59517.00, 4268.08, 2938.28,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.21, 5,   coast,  -13.24,  59501.00, 4270.13, 2940.33,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.22, 5,   coast,  -11.77,  59503.00, 4269.87, 2940.07,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.23, 5,   coast,  -11.77,  59482.00, 4272.56, 2942.76,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.24, 5,   coast,  -12.75,  59466.00, 4274.61, 2944.81,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.25, 5,   coast,  -11.77,  59454.00, 4276.15, 2946.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.26, 5,   coast,  -13.73,  59454.00, 4276.15, 2946.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.27, 5,   coast,  -11.77,  59438.00, 4278.20, 2948.40,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.28, 5,   coast,  -15.20,  59415.00, 4281.15, 2951.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.29, 5,   coast,  -11.77,  59405.00, 4282.44, 2952.63,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.30, 5,   coast,  -14.22,  59416.00, 4281.02, 2951.22,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9407952,-106.9138926,  4353.0, 2022,  6, 24, 15, 17, 31,      270,     2971, 302,  85,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 24,  0,  0,  0,  0, 24, 25, 31, 34,  0,  0, 34,  0, 30, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    15.31, 5,   coast,  -12.75,  59384.00, 4285.13, 2955.33,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.31, 5,   coast,  -12.75,  59384.00, 4285.13, 2955.33,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.31, 5,   coast,  -12.75,  59384.00, 4285.13, 2955.33,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.32, 5,   coast,  -13.24,  59395.00, 4283.72, 2953.92,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.33, 5,   coast,  -12.75,  59368.00, 4287.18, 2957.38,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.34, 5,   coast,  -12.26,  59363.00, 4287.82, 2958.02,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.35, 5,   coast,  -11.77,  59349.00, 4289.62, 2959.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.36, 5,   coast,  -10.30,  59344.00, 4290.26, 2960.46,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.37, 5,   coast,  -14.22,  59332.00, 4291.80, 2962.00,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.38, 5,   coast,  -16.18,  59329.00, 4292.19, 2962.39,     NaN, 33.9, 3.99, 3.99, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.38, 5,   coast,  -16.18,  59329.00, 4292.19, 2962.39,     NaN, 33.9, 3.99, 3.99, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.39, 5,   coast,  -11.28,  59304.00, 4295.40, 2965.60,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.40, 5,   coast,  -14.71,  59321.00, 4293.22, 2963.42,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.41, 5,   coast,  -12.75,  59284.00, 4297.97, 2968.17,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.42, 5,   coast,  -11.28,  59272.00, 4299.51, 2969.71,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.43, 5,   coast,  -12.26,  59263.00, 4300.67, 2970.87,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.44, 5,   coast,  -15.69,  59243.00, 4303.24, 2973.44,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.45, 5,   coast,  -12.26,  59230.00, 4304.91, 2975.11,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.46, 5,   coast,  -12.75,  59228.00, 4305.17, 2975.37,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.47, 5,   coast,  -12.75,  59209.00, 4307.61, 2977.81,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.48, 5,   coast,  -11.77,  59208.00, 4307.74, 2977.94,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.49, 5,   coast,  -13.24,  59183.00, 4310.95, 2981.15,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.50, 5,   coast,  -12.75,  59187.00, 4310.44, 2980.64,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.51, 5,   coast,  -14.22,  59164.00, 4313.40, 2983.60,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.52, 5,   coast,  -12.75,  59152.00, 4314.94, 2985.14,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.53, 5,   coast,  -10.30,  59153.00, 4314.81, 2985.01,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.54, 5,   coast,  -13.24,  59137.00, 4316.87, 2987.07,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.55, 5,   coast,  -11.77,  59128.00, 4318.03, 2988.23,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.56, 5,   coast,  -12.75,  59120.00, 4319.06, 2989.26,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.57, 5,   coast,  -13.73,  59095.00, 4322.28, 2992.48,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.58, 5,   coast,  -11.77,  59081.00, 4324.09, 2994.29,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.59, 5,   coast,  -13.73,  59084.00, 4323.70, 2993.90,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.60, 5,   coast,  -12.75,  59079.00, 4324.34, 2994.54,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.61, 5,   coast,  -12.26,  59060.00, 4326.79, 2996.99,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.62, 5,   coast,  -13.24,  59044.00, 4328.85, 2999.05,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.63, 5,   coast,  -14.22,  59037.00, 4329.76, 2999.96,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.64, 5,   coast,  -12.75,  59025.00, 4331.30, 3001.50,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.65, 5,   coast,  -10.30,  59016.00, 4332.46, 3002.66,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.66, 5,   coast,  -12.26,  59004.00, 4334.01, 3004.21,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.67, 5,   coast,  -12.26,  58985.00, 4336.46, 3006.66,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.68, 5,   coast,  -14.22,  58979.00, 4337.24, 3007.44,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.69, 5,   coast,  -11.77,  58957.00, 4340.08, 3010.27,     NaN, 33.9, 3.99, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.70, 5,   coast,  -11.77,  58960.00, 4339.69, 3009.89,     NaN, 33.9, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.70, 5,   coast,  -11.77,  58960.00, 4339.69, 3009.89,     NaN, 33.9, 3.99, 3.98, 3.98,   0.03,   0.00,   0.00,  64.27,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.71, 5,   coast,  -12.75,  58943.00, 4341.88, 3012.08,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.72, 5,   coast,  -13.24,  58948.00, 4341.24, 3011.44,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.73, 5,   coast,  -10.30,  58924.00, 4344.34, 3014.53,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.74, 5,   coast,  -11.77,  58918.00, 4345.11, 3015.31,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.75, 5,   coast,  -14.22,  58905.00, 4346.79, 3016.99,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.76, 5,   coast,  -11.28,  58887.00, 4349.11, 3019.31,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.77, 5,   coast,  -12.26,  58880.00, 4350.02, 3020.22,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.78, 5,   coast,  -10.79,  58880.00, 4350.02, 3020.22,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.79, 5,   coast,  -12.75,  58864.00, 4352.09, 3022.28,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.80, 5,   coast,  -12.75,  58844.00, 4354.67, 3024.87,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.81, 5,   coast,  -11.77,  58846.00, 4354.41, 3024.61,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.82, 5,   coast,   -9.81,  58840.00, 4355.19, 3025.39,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.83, 5,   coast,  -13.24,  58815.00, 4358.42, 3028.62,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.84, 5,   coast,  -11.28,  58808.00, 4359.32, 3029.52,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.85, 5,   coast,  -12.26,  58804.00, 4359.84, 3030.04,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.86, 5,   coast,  -12.75,  58791.00, 4361.52, 3031.72,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.87, 5,   coast,  -10.79,  58773.00, 4363.85, 3034.05,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.88, 5,   coast,  -14.22,  58760.00, 4365.53, 3035.73,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.89, 5,   coast,  -13.24,  58766.00, 4364.76, 3034.96,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.90, 5,   coast,  -12.75,  58757.00, 4365.92, 3036.12,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.91, 5,   coast,  -13.24,  58740.00, 4368.12, 3038.32,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.92, 5,   coast,  -13.24,  58725.00, 4370.06, 3040.26,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.93, 5,   coast,  -13.73,  58714.00, 4371.49, 3041.69,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.94, 5,   coast,  -15.20,  58705.00, 4372.65, 3042.85,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.95, 5,   coast,  -10.30,  58691.00, 4374.47, 3044.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.96, 5,   coast,   -9.81,  58691.00, 4374.47, 3044.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.97, 5,   coast,   -9.32,  58660.00, 4378.48, 3048.68,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.98, 5,   coast,  -10.79,  58656.00, 4379.00, 3049.20,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    15.99, 5,   coast,  -12.26,  58651.00, 4379.65, 3049.85,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.00, 5,   coast,  -11.77,  58639.00, 4381.21, 3051.40,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.01, 5,   coast,  -13.73,  58632.00, 4382.11, 3052.31,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.02, 5,   coast,  -10.79,  58627.00, 4382.76, 3052.96,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.02, 5,   coast,  -10.79,  58627.00, 4382.76, 3052.96,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.03, 5,   coast,  -11.28,  58603.00, 4385.87, 3056.07,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.04, 5,   coast,  -13.73,  58592.00, 4387.30, 3057.50,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.05, 5,   coast,  -13.24,  58578.00, 4389.12, 3059.31,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.06, 5,   coast,  -11.28,  58584.00, 4388.34, 3058.54,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.07, 5,   coast,  -11.77,  58556.00, 4391.97, 3062.17,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.08, 5,   coast,  -10.30,  58564.00, 4390.93, 3061.13,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.09, 5,   coast,  -11.77,  58541.00, 4393.92, 3064.12,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.10, 5,   coast,  -11.28,  58512.00, 4397.68, 3067.88,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.11, 5,   coast,  -11.77,  58519.00, 4396.77, 3066.97,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.12, 5,   coast,  -14.22,  58507.00, 4398.33, 3068.53,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.13, 5,   coast,  -14.71,  58505.00, 4398.59, 3068.79,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.14, 5,   coast,  -11.28,  58482.00, 4401.58, 3071.78,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.15, 5,   coast,  -15.20,  58475.00, 4402.49, 3072.69,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.16, 5,   coast,  -12.26,  58461.00, 4404.31, 3074.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.17, 5,   coast,  -14.22,  58461.00, 4404.31, 3074.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.18, 5,   coast,  -10.79,  58445.00, 4406.39, 3076.59,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.19, 5,   coast,  -12.26,  58442.00, 4406.78, 3076.97,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.20, 5,   coast,  -10.30,  58410.00, 4410.94, 3081.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.21, 5,   coast,  -12.75,  58417.00, 4410.03, 3080.22,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.22, 5,   coast,  -11.28,  58405.00, 4411.59, 3081.79,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.23, 5,   coast,  -11.77,  58392.00, 4413.28, 3083.48,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.24, 5,   coast,  -14.22,  58378.00, 4415.10, 3085.30,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.25, 5,   coast,  -13.24,  58366.00, 4416.66, 3086.86,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.26, 5,   coast,  -12.75,  58368.00, 4416.40, 3086.60,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.27, 5,   coast,  -11.77,  58342.00, 4419.78, 3089.98,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.28, 5,   coast,  -14.22,  58334.00, 4420.82, 3091.02,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.29, 5,   coast,  -10.79,  58325.00, 4422.00, 3092.19,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.30, 5,   coast,  -12.26,  58317.00, 4423.04, 3093.24,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9408982,-106.9140824,  4509.0, 2022,  6, 24, 15, 17, 32,      292,     3129, 302,  85,   1.4,   0.9,   1.1,  0, 32, 30,  0,  0, 34,  0,  0,  0,  0, 31, 35, 31, 22,  0,  0, 24,  0, 30, 28,  0,  0,  0,  0,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.31, 5,   coast,  -12.75,  58307.00, 4424.34, 3094.54,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.31, 5,   coast,  -12.75,  58307.00, 4424.34, 3094.54,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.31, 5,   coast,  -12.75,  58307.00, 4424.34, 3094.54,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.32, 5,   coast,  -13.24,  58293.00, 4426.16, 3096.36,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.33, 5,   coast,  -12.75,  58277.00, 4428.25, 3098.45,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.34, 5,   coast,  -10.79,  58270.00, 4429.16, 3099.36,     NaN, 33.9, 4.00, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.34, 5,   coast,  -10.79,  58270.00, 4429.16, 3099.36,     NaN, 33.9, 4.00, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.35, 5,   coast,  -14.71,  58275.00, 4428.51, 3098.71,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.36, 5,   coast,  -12.75,  58251.00, 4431.63, 3101.83,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.37, 5,   coast,  -11.77,  58247.00, 4432.16, 3102.35,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.38, 5,   coast,  -12.75,  58232.00, 4434.11, 3104.31,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.39, 5,   coast,  -12.26,  58233.00, 4433.98, 3104.18,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.40, 5,   coast,  -12.26,  58216.00, 4436.20, 3106.40,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.41, 5,   coast,  -11.28,  58199.00, 4438.41, 3108.61,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.42, 5,   coast,  -12.26,  58193.00, 4439.20, 3109.40,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.43, 5,   coast,  -13.24,  58194.00, 4439.07, 3109.26,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.44, 5,   coast,  -12.26,  58170.00, 4442.20, 3112.40,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.45, 5,   coast,  -11.28,  58173.00, 4441.80, 3112.00,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.46, 5,   coast,  -15.20,  58158.00, 4443.76, 3113.96,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.47, 5,   coast,  -11.28,  58150.00, 4444.81, 3115.01,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.48, 5,   coast,  -14.71,  58128.00, 4447.68, 3117.88,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.49, 5,   coast,  -11.77,  58131.00, 4447.29, 3117.48,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.50, 5,   coast,  -12.75,  58123.00, 4448.33, 3118.53,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.51, 5,   coast,   -9.32,  58109.00, 4450.16, 3120.36,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.52, 5,   coast,  -12.26,  58094.00, 4452.12, 3122.32,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.53, 5,   coast,  -11.28,  58083.00, 4453.55, 3123.75,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.54, 5,   coast,  -12.26,  58082.00, 4453.68, 3123.88,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.55, 5,   coast,  -17.16,  58077.00, 4454.34, 3124.54,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.56, 5,   coast,  -10.79,  58055.00, 4457.21, 3127.41,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.57, 5,   coast,  -12.26,  58054.00, 4457.34, 3127.54,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.58, 5,   coast,  -11.28,  58039.00, 4459.30, 3129.50,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.59, 5,   coast,  -13.24,  58032.00, 4460.22, 3130.42,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.60, 5,   coast,  -13.24,  58021.00, 4461.66, 3131.86,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.61, 5,   coast,  -11.77,  58010.00, 4463.09, 3133.29,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.62, 5,   coast,  -10.79,  57991.00, 4465.58, 3135.78,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.63, 5,   coast,  -11.28,  57989.00, 4465.84, 3136.04,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.64, 5,   coast,  -13.24,  57994.00, 4465.19, 3135.39,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.65, 5,   coast,  -12.26,  57979.00, 4467.15, 3137.35,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.66, 5,   coast,  -10.79,  57966.00, 4468.85, 3139.05,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.66, 5,   coast,  -10.79,  57966.00, 4468.85, 3139.05,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.67, 5,   coast,   -9.81,  57956.00, 4470.16, 3140.36,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.68, 5,   coast,  -10.79,  57936.00, 4472.78, 3142.97,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.69, 5,   coast,   -9.81,  57925.00, 4474.22, 3144.41,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.70, 5,   coast,  -14.71,  57923.00, 4474.48, 3144.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.71, 5,   coast,  -13.24,  57916.00, 4475.39, 3145.59,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.72, 5,   coast,  -11.77,  57903.00, 4477.10, 3147.30,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.73, 5,   coast,  -14.71,  57895.00, 4478.14, 3148.34,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.74, 5,   coast,  -12.26,  57882.00, 4479.85, 3150.05,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.75, 5,   coast,   -8.83,  57867.00, 4481.81, 3152.01,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.76, 5,   coast,  -13.24,  57870.00, 4481.42, 3151.62,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.77, 5,   coast,  -15.20,  57857.00, 4483.12, 3153.32,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.78, 5,   coast,  -12.26,  57839.00, 4485.48, 3155.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.79, 5,   coast,  -10.30,  57838.00, 4485.61, 3155.81,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.80, 5,   coast,  -13.24,  57822.00, 4487.71, 3157.91,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.81, 5,   coast,  -10.30,  57822.00, 4487.71, 3157.91,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.82, 5,   coast,  -12.75,  57812.00, 4489.02, 3159.22,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.83, 5,   coast,  -12.26,  57786.00, 4492.43, 3162.63,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.84, 5,   coast,  -13.24,  57796.00, 4491.12, 3161.32,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.85, 5,   coast,  -14.22,  57769.00, 4494.66, 3164.86,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.86, 5,   coast,  -10.30,  57769.00, 4494.66, 3164.86,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.87, 5,   coast,  -10.79,  57756.00, 4496.37, 3166.57,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.88, 5,   coast,  -12.75,  57738.00, 4498.73, 3168.93,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.89, 5,   coast,  -13.24,  57746.00, 4497.68, 3167.88,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.90, 5,   coast,  -10.79,  57726.00, 4500.30, 3170.50,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.91, 5,   coast,  -12.75,  57714.00, 4501.88, 3172.08,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.92, 5,   coast,  -14.22,  57711.00, 4502.27, 3172.47,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.93, 5,   coast,  -13.73,  57708.00, 4502.67, 3172.87,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.94, 5,   coast,  -11.28,  57687.00, 4505.43, 3175.62,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.95, 5,   coast,  -11.28,  57674.00, 4507.13, 3177.33,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.96, 5,   coast,   -9.32,  57675.00, 4507.00, 3177.20,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.97, 5,   coast,  -11.77,  57654.00, 4509.76, 3179.96,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.98, 5,   coast,  -10.79,  57657.00, 4509.37, 3179.57,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.98, 5,   coast,  -10.79,  57657.00, 4509.37, 3179.57,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    16.99, 5,   coast,  -11.28,  57645.00, 4510.94, 3181.14,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.00, 5,   coast,  -11.77,  57628.00, 4513.18, 3183.38,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.01, 5,   coast,  -11.77,  57628.00, 4513.18, 3183.38,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.02, 5,   coast,  -12.75,  57620.00, 4514.23, 3184.43,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.03, 5,   coast,  -13.73,  57609.00, 4515.68, 3185.88,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.04, 5,   coast,  -12.26,  57599.00, 4516.99, 3187.19,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.05, 5,   coast,  -11.77,  57588.00, 4518.44, 3188.64,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.06, 5,   coast,  -13.73,  57587.00, 4518.57, 3188.77,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.07, 5,   coast,  -10.79,  57567.00, 4521.20, 3191.40,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.08, 5,   coast,  -12.26,  57565.00, 4521.46, 3191.66,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.09, 5,   coast,  -10.30,  57567.00, 4521.20, 3191.40,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.10, 5,   coast,  -10.30,  57547.00, 4523.83, 3194.03,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.11, 5,   coast,  -10.30,  57531.00, 4525.94, 3196.14,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.12, 5,   coast,  -13.24,  57528.00, 4526.33, 3196.53,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.13, 5,   coast,  -12.26,  57515.00, 4528.05, 3198.24,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.14, 5,   coast,  -13.24,  57500.00, 4530.02, 3200.22,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.15, 5,   coast,  -12.75,  57485.00, 4532.00, 3202.20,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.16, 5,   coast,  -11.77,  57477.00, 4533.05, 3203.25,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.17, 5,   coast,  -13.24,  57474.00, 4533.45, 3203.64,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.18, 5,   coast,  -11.77,  57453.00, 4536.21, 3206.41,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.19, 5,   coast,  -12.26,  57456.00, 4535.82, 3206.02,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.20, 5,   coast,  -10.30,  57458.00, 4535.55, 3205.75,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.21, 5,   coast,  -10.30,  57442.00, 4537.66, 3207.86,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.22, 5,   coast,  -12.26,  57424.00, 4540.03, 3210.23,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.23, 5,   coast,  -12.75,  57425.00, 4539.90, 3210.10,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.24, 5,   coast,  -12.26,  57407.00, 4542.28, 3212.48,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.25, 5,   coast,  -12.26,  57408.00, 4542.14, 3212.34,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.26, 5,   coast,  -13.24,  57390.00, 4544.52, 3214.72,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.27, 5,   coast,  -10.30,  57373.00, 4546.76, 3216.96,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.28, 5,   coast,  -11.28,  57379.00, 4545.97, 3216.17,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.29, 5,   coast,  -12.26,  57368.00, 4547.42, 3217.62,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.30, 5,   coast,  -13.73,  57356.00, 4549.00, 3219.20,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.30, 5,   coast,  -13.73,  57356.00, 4549.00, 3219.20,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  63.84,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9409983,-106.9142610,  4653.0, 2022,  6, 24, 15, 17, 33,      312,     3274, 302,  85,   1.4,   0.8,   1.1,  0, 25, 33,  0,  0, 27,  0,  0,  0,  0, 25, 32, 28, 36,  0,  0, 31,  0, 29, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    17.31, 5,   coast,  -11.77,  57338.00, 4551.38, 3221.58,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.31, 5,   coast,  -11.77,  57338.00, 4551.38, 3221.58,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.31, 5,   coast,  -11.77,  57338.00, 4551.38, 3221.58,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.32, 5,   coast,  -14.71,  57329.00, 4552.57, 3222.77,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.33, 5,   coast,  -10.30,  57335.00, 4551.78, 3221.97,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.34, 5,   coast,  -12.26,  57310.00, 4555.08, 3225.28,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.35, 5,   coast,   -8.83,  57317.00, 4554.15, 3224.35,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.36, 5,   coast,  -10.30,  57314.00, 4554.55, 3224.75,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.37, 5,   coast,  -12.75,  57288.00, 4557.98, 3228.18,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.38, 5,   coast,   -9.81,  57279.00, 4559.17, 3229.37,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.39, 5,   coast,  -12.26,  57283.00, 4558.64, 3228.84,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.40, 5,   coast,  -10.79,  57267.00, 4560.76, 3230.96,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.41, 5,   coast,  -12.26,  57252.00, 4562.74, 3232.94,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.42, 5,   coast,  -14.22,  57235.00, 4564.99, 3235.18,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.43, 5,   coast,  -13.73,  57244.00, 4563.80, 3233.99,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.44, 5,   coast,   -9.32,  57225.00, 4566.31, 3236.51,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.45, 5,   coast,  -12.26,  57219.00, 4567.10, 3237.30,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.46, 5,   coast,  -10.30,  57209.00, 4568.42, 3238.62,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.47, 5,   coast,  -13.73,  57208.00, 4568.56, 3238.75,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.48, 5,   coast,  -14.22,  57196.00, 4570.14, 3240.34,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.49, 5,   coast,  -11.77,  57188.00, 4571.20, 3241.40,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.50, 5,   coast,   -9.32,  57179.00, 4572.39, 3242.59,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.51, 5,   coast,   -9.81,  57170.00, 4573.58, 3243.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.52, 5,   coast,  -10.30,  57145.00, 4576.89, 3247.09,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.53, 5,   coast,  -12.26,  57141.00, 4577.42, 3247.62,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.54, 5,   coast,  -12.26,  57136.00, 4578.08, 3248.28,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.55, 5,   coast,  -12.26,  57128.00, 4579.14, 3249.34,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.56, 5,   coast,  -11.28,  57121.00, 4580.07, 3250.27,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.57, 5,   coast,  -14.22,  57109.00, 4581.66, 3251.86,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.58, 5,   coast,  -13.24,  57095.00, 4583.51, 3253.71,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.59, 5,   coast,  -11.77,  57094.00, 4583.64, 3253.84,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.60, 5,   coast,  -12.26,  57078.00, 4585.76, 3255.96,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.61, 5,   coast,  -12.26,  57075.00, 4586.16, 3256.36,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.62, 5,   coast,   -7.85,  57075.00, 4586.16, 3256.36,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.62, 5,   coast,   -7.85,  57075.00, 4586.16, 3256.36,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.63, 5,   coast,  -11.28,  57057.00, 4588.55, 3258.74,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.64, 5,   coast,  -12.26,  57043.00, 4590.40, 3260.60,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.65, 5,   coast,   -9.81,  57040.00, 4590.80, 3261.00,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.66, 5,   coast,   -8.83,  57027.00, 4592.52, 3262.72,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.67, 5,   coast,  -15.69,  57028.00, 4592.39, 3262.59,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.68, 5,   coast,  -12.26,  57013.00, 4594.38, 3264.58,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.69, 5,   coast,  -13.73,  56999.00, 4596.23, 3266.43,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.70, 5,   coast,  -11.77,  56993.00, 4597.03, 3267.23,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.71, 5,   coast,  -10.79,  56987.00, 4597.83, 3268.03,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.72, 5,   coast,  -11.77,  56967.00, 4600.48, 3270.68,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.73, 5,   coast,  -14.22,  56969.00, 4600.21, 3270.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.74, 5,   coast,  -11.77,  56939.00, 4604.20, 3274.40,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.75, 5,   coast,  -14.22,  56958.00, 4601.67, 3271.87,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.76, 5,   coast,  -10.79,  56930.00, 4605.39, 3275.59,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.77, 5,   coast,  -10.79,  56927.00, 4605.79, 3275.99,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.78, 5,   coast,  -12.26,  56929.00, 4605.52, 3275.72,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.79, 5,   coast,  -13.24,  56919.00, 4606.85, 3277.05,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.80, 5,   coast,  -10.79,  56891.00, 4610.57, 3280.77,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.81, 5,   coast,  -12.26,  56913.00, 4607.65, 3277.85,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.82, 5,   coast,  -12.75,  56899.00, 4609.51, 3279.71,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.83, 5,   coast,  -10.79,  56881.00, 4611.90, 3282.10,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.84, 5,   coast,  -12.75,  56888.00, 4610.97, 3281.17,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.85, 5,   coast,  -11.77,  56863.00, 4614.29, 3284.49,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.86, 5,   coast,  -12.75,  56873.00, 4612.96, 3283.16,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.87, 5,   coast,  -12.26,  56845.00, 4616.68, 3286.88,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.88, 5,   coast,  -10.30,  56842.00, 4617.08, 3287.28,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.89, 5,   coast,  -13.73,  56832.00, 4618.41, 3288.61,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.90, 5,   coast,  -10.79,  56817.00, 4620.41, 3290.60,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.91, 5,   coast,   -8.34,  56812.00, 4621.07, 3291.27,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.92, 5,   coast,  -10.79,  56802.00, 4622.40, 3292.60,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.93, 5,   coast,   -9.81,  56794.00, 4623.46, 3293.66,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.94, 5,   coast,  -10.30,  56799.00, 4622.80, 3293.00,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.94, 5,   coast,  -10.30,  56799.00, 4622.80, 3293.00,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.95, 5,   coast,  -12.26,  56785.00, 4624.66, 3294.86,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.96, 5,   coast,  -10.79,  56776.00, 4625.86, 3296.06,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.97, 5,   coast,   -9.81,  56776.00, 4625.86, 3296.06,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.98, 5,   coast,  -12.75,  56756.00, 4628.52, 3298.72,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    17.99, 5,   coast,  -12.75,  56742.00, 4630.38, 3300.58,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.00, 5,   coast,  -12.26,  56738.00, 4630.92, 3301.12,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.01, 5,   coast,  -13.73,  56725.00, 4632.65, 3302.85,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.02, 5,   coast,  -16.67,  56710.00, 4634.65, 3304.84,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.03, 5,   coast,  -12.75,  56725.00, 4632.65, 3302.85,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.04, 5,   coast,  -11.77,  56702.00, 4635.71, 3305.91,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.05, 5,   coast,  -15.20,  56693.00, 4636.91, 3307.11,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.06, 5,   coast,  -11.28,  56684.00, 4638.11, 3308.31,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.07, 5,   coast,  -10.79,  56677.00, 4639.04, 3309.24,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.08, 5,   coast,  -10.79,  56679.00, 4638.77, 3308.97,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.09, 5,   coast,  -11.28,  56662.00, 4641.04, 3311.24,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.10, 5,   coast,  -11.28,  56658.00, 4641.57, 3311.77,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.11, 5,   coast,  -11.77,  56655.00, 4641.97, 3312.17,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.12, 5,   coast,   -8.83,  56643.00, 4643.57, 3313.77,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.13, 5,   coast,  -12.75,  56626.00, 4645.84, 3316.04,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.14, 5,   coast,  -10.79,  56626.00, 4645.84, 3316.04,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.15, 5,   coast,  -13.24,  56617.00, 4647.04, 3317.24,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.16, 5,   coast,   -8.83,  56605.00, 4648.64, 3318.84,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.17, 5,   coast,  -12.26,  56590.00, 4650.64, 3320.84,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.18, 5,   coast,  -13.73,  56582.00, 4651.71, 3321.91,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.19, 5,   coast,  -13.73,  56583.00, 4651.57, 3321.77,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.20, 5,   coast,  -11.77,  56572.00, 4653.04, 3323.24,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.21, 5,   coast,  -10.79,  56559.00, 4654.78, 3324.98,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.22, 5,   coast,  -13.73,  56551.00, 4655.84, 3326.04,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.23, 5,   coast,  -12.75,  56542.00, 4657.05, 3327.25,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.24, 5,   coast,  -13.73,  56538.00, 4657.58, 3327.78,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.25, 5,   coast,  -10.79,  56528.00, 4658.92, 3329.11,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.26, 5,   coast,   -9.81,  56523.00, 4659.58, 3329.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.26, 5,   coast,   -9.81,  56523.00, 4659.58, 3329.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  63.97,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.27, 5,   coast,   -9.81,  56515.00, 4660.65, 3330.85,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.28, 5,   coast,  -11.77,  56507.00, 4661.72, 3331.92,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.29, 5,   coast,  -11.28,  56508.00, 4661.59, 3331.79,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.30, 5,   coast,   -9.81,  56492.00, 4663.72, 3333.92,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9410871,-106.9144475,  4785.0, 2022,  6, 24, 15, 17, 34,      332,     3407, 302,  84,   1.4,   0.8,   1.1,  0, 37, 32,  0,  0, 31,  0,  0,  0,  0, 31, 29, 33, 33,  0,  0, 31,  0, 34, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 18,  0,  0
+6, 6583, 3,VE3LIC,    18.31, 5,   coast,  -12.75,  56488.00, 4664.26, 3334.46,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.31, 5,   coast,  -12.75,  56488.00, 4664.26, 3334.46,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.31, 5,   coast,  -12.75,  56488.00, 4664.26, 3334.46,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.32, 5,   coast,   -9.81,  56461.00, 4667.87, 3338.07,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.33, 5,   coast,  -13.73,  56463.00, 4667.60, 3337.80,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.34, 5,   coast,  -14.22,  56460.00, 4668.00, 3338.20,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.35, 5,   coast,   -9.32,  56443.00, 4670.27, 3340.47,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.36, 5,   coast,  -12.26,  56441.00, 4670.54, 3340.74,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.37, 5,   coast,  -12.75,  56416.00, 4673.88, 3344.08,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.38, 5,   coast,  -14.71,  56415.00, 4674.02, 3344.22,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.39, 5,   coast,  -10.30,  56404.00, 4675.49, 3345.69,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.40, 5,   coast,   -9.32,  56398.00, 4676.29, 3346.49,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.41, 5,   coast,  -11.28,  56390.00, 4677.36, 3347.56,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.42, 5,   coast,   -7.35,  56378.00, 4678.97, 3349.17,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.43, 5,   coast,  -10.30,  56372.00, 4679.77, 3349.97,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.44, 5,   coast,  -12.75,  56370.00, 4680.04, 3350.24,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.45, 5,   coast,  -13.73,  56366.00, 4680.57, 3350.77,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.46, 5,   coast,  -10.79,  56347.00, 4683.12, 3353.31,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.47, 5,   coast,  -11.77,  56360.00, 4681.38, 3351.57,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.48, 5,   coast,  -12.26,  56337.00, 4684.45, 3354.65,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.49, 5,   coast,  -10.30,  56336.00, 4684.59, 3354.79,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.50, 5,   coast,  -10.30,  56319.00, 4686.86, 3357.06,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.51, 5,   coast,   -9.32,  56316.00, 4687.27, 3357.47,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.52, 5,   coast,  -14.71,  56305.00, 4688.74, 3358.94,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.53, 5,   coast,  -13.24,  56307.00, 4688.47, 3358.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.54, 5,   coast,  -11.77,  56297.00, 4689.81, 3360.01,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.55, 5,   coast,  -10.30,  56286.00, 4691.29, 3361.48,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.56, 5,   coast,  -11.28,  56275.00, 4692.76, 3362.96,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.57, 5,   coast,   -9.81,  56269.00, 4693.56, 3363.76,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.58, 5,   coast,  -10.30,  56254.00, 4695.57, 3365.77,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.58, 5,   coast,  -10.30,  56254.00, 4695.57, 3365.77,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.59, 5,   coast,  -11.28,  56258.00, 4695.04, 3365.24,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.60, 5,   coast,  -10.79,  56249.00, 4696.24, 3366.44,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.61, 5,   coast,   -8.83,  56230.00, 4698.79, 3368.99,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.62, 5,   coast,  -11.77,  56223.00, 4699.73, 3369.93,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.63, 5,   coast,  -12.26,  56223.00, 4699.73, 3369.93,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.64, 5,   coast,  -10.79,  56214.00, 4700.94, 3371.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.65, 5,   coast,  -14.22,  56206.00, 4702.01, 3372.21,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.66, 5,   coast,  -10.30,  56190.00, 4704.16, 3374.36,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.67, 5,   coast,  -13.73,  56184.00, 4704.96, 3375.16,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.68, 5,   coast,  -12.26,  56177.00, 4705.90, 3376.10,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.69, 5,   coast,  -11.28,  56160.00, 4708.18, 3378.38,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.70, 5,   coast,  -11.28,  56173.00, 4706.44, 3376.64,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.71, 5,   coast,  -12.26,  56171.00, 4706.71, 3376.91,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.72, 5,   coast,  -11.77,  56146.00, 4710.06, 3380.26,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.73, 5,   coast,  -13.24,  56143.00, 4710.47, 3380.67,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.74, 5,   coast,  -13.73,  56140.00, 4710.87, 3381.07,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.75, 5,   coast,  -10.30,  56121.00, 4713.42, 3383.62,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.76, 5,   coast,  -10.79,  56120.00, 4713.56, 3383.75,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.77, 5,   coast,  -12.75,  56115.00, 4714.23, 3384.43,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.78, 5,   coast,  -11.77,  56112.00, 4714.63, 3384.83,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.79, 5,   coast,  -10.79,  56101.00, 4716.11, 3386.31,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.80, 5,   coast,  -11.77,  56088.00, 4717.85, 3388.05,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.81, 5,   coast,  -10.79,  56089.00, 4717.72, 3387.92,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.82, 5,   coast,   -9.81,  56070.00, 4720.27, 3390.47,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.83, 5,   coast,  -12.75,  56057.00, 4722.02, 3392.22,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.84, 5,   coast,  -11.28,  56057.00, 4722.02, 3392.22,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.85, 5,   coast,  -13.73,  56054.00, 4722.42, 3392.62,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.86, 5,   coast,  -12.26,  56051.00, 4722.83, 3393.03,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.87, 5,   coast,   -9.81,  56040.00, 4724.31, 3394.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.88, 5,   coast,  -11.28,  56022.00, 4726.73, 3396.93,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.89, 5,   coast,  -11.77,  56013.00, 4727.94, 3398.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.90, 5,   coast,  -12.26,  56012.00, 4728.07, 3398.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.90, 5,   coast,  -12.26,  56012.00, 4728.07, 3398.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.91, 5,   coast,  -11.77,  56004.00, 4729.15, 3399.35,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.92, 5,   coast,  -13.24,  55992.00, 4730.76, 3400.96,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.93, 5,   coast,  -10.79,  55992.00, 4730.76, 3400.96,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.94, 5,   coast,  -11.28,  55992.00, 4730.76, 3400.96,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.95, 5,   coast,  -11.77,  55975.00, 4733.05, 3403.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.96, 5,   coast,  -10.79,  55974.00, 4733.19, 3403.38,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.97, 5,   coast,  -10.79,  55954.00, 4735.88, 3406.08,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.98, 5,   coast,  -11.77,  55953.00, 4736.01, 3406.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    18.99, 5,   coast,  -11.28,  55950.00, 4736.42, 3406.62,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.00, 5,   coast,  -12.75,  55943.00, 4737.36, 3407.56,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.01, 5,   coast,  -11.77,  55926.00, 4739.65, 3409.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.02, 5,   coast,  -10.30,  55916.00, 4741.00, 3411.19,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.03, 5,   coast,  -11.77,  55917.00, 4740.86, 3411.06,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.04, 5,   coast,   -9.81,  55905.00, 4742.48, 3412.68,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.05, 5,   coast,  -12.75,  55906.00, 4742.34, 3412.54,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.06, 5,   coast,  -10.30,  55891.00, 4744.36, 3414.56,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.07, 5,   coast,  -10.79,  55873.00, 4746.79, 3416.99,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.08, 5,   coast,   -8.34,  55873.00, 4746.79, 3416.99,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.09, 5,   coast,   -9.81,  55864.00, 4748.00, 3418.20,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.10, 5,   coast,  -10.30,  55858.00, 4748.81, 3419.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.11, 5,   coast,  -11.77,  55848.00, 4750.16, 3420.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.12, 5,   coast,  -11.28,  55846.00, 4750.43, 3420.63,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.13, 5,   coast,   -8.83,  55838.00, 4751.51, 3421.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.14, 5,   coast,  -11.28,  55831.00, 4752.45, 3422.65,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.15, 5,   coast,  -12.26,  55818.00, 4754.21, 3424.41,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.16, 5,   coast,  -11.28,  55819.00, 4754.07, 3424.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.17, 5,   coast,   -9.32,  55803.00, 4756.23, 3426.43,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.18, 5,   coast,  -10.79,  55802.00, 4756.37, 3426.56,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.19, 5,   coast,  -12.75,  55799.00, 4756.77, 3426.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.20, 5,   coast,  -11.28,  55789.00, 4758.12, 3428.32,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.21, 5,   coast,  -10.30,  55769.00, 4760.82, 3431.02,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.22, 5,   coast,  -11.28,  55771.00, 4760.55, 3430.75,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.22, 5,   coast,  -11.28,  55771.00, 4760.55, 3430.75,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.23, 5,   coast,  -11.28,  55764.00, 4761.49, 3431.69,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.24, 5,   coast,  -12.26,  55767.00, 4761.09, 3431.29,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.25, 5,   coast,   -8.83,  55745.00, 4764.06, 3434.26,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.26, 5,   coast,  -12.75,  55756.00, 4762.57, 3432.77,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.27, 5,   coast,  -11.28,  55729.00, 4766.22, 3436.42,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.28, 5,   coast,  -12.26,  55725.00, 4766.76, 3436.96,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.29, 5,   coast,   -8.83,  55723.00, 4767.03, 3437.23,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.30, 5,   coast,  -10.30,  55717.00, 4767.84, 3438.04,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9411842,-106.9146261,  4907.0, 2022,  6, 24, 15, 17, 35,      351,     3531, 302,  84,   1.4,   0.8,   1.1,  0, 21, 30,  0,  0, 37,  0,  0,  0,  0, 26, 30, 34, 25,  0,  0, 32,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.31, 5,   coast,   -8.83,  55716.00, 4767.98, 3438.18,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.31, 5,   coast,   -8.83,  55716.00, 4767.98, 3438.18,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.31, 5,   coast,   -8.83,  55716.00, 4767.98, 3438.18,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.32, 5,   coast,   -9.81,  55699.00, 4770.27, 3440.47,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.33, 5,   coast,  -11.28,  55687.00, 4771.90, 3442.09,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.34, 5,   coast,   -9.32,  55687.00, 4771.90, 3442.09,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.35, 5,   coast,  -10.30,  55685.00, 4772.17, 3442.36,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.36, 5,   coast,   -9.81,  55669.00, 4774.33, 3444.53,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.37, 5,   coast,  -13.24,  55651.00, 4776.76, 3446.96,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.38, 5,   coast,  -11.77,  55674.00, 4773.65, 3443.85,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.39, 5,   coast,  -10.79,  55653.00, 4776.49, 3446.69,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.40, 5,   coast,  -10.79,  55636.00, 4778.79, 3448.99,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.41, 5,   coast,  -11.77,  55639.00, 4778.39, 3448.58,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.42, 5,   coast,  -11.28,  55628.00, 4779.87, 3450.07,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.43, 5,   coast,  -11.28,  55611.00, 4782.17, 3452.37,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.44, 5,   coast,  -13.24,  55613.00, 4781.90, 3452.10,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.45, 5,   coast,  -12.26,  55604.00, 4783.12, 3453.32,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.46, 5,   coast,  -11.77,  55592.00, 4784.74, 3454.94,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.47, 5,   coast,  -12.75,  55588.00, 4785.29, 3455.49,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.48, 5,   coast,  -10.30,  55585.00, 4785.69, 3455.89,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.49, 5,   coast,  -13.24,  55572.00, 4787.45, 3457.65,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.50, 5,   coast,   -9.81,  55570.00, 4787.72, 3457.92,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.51, 5,   coast,  -11.28,  55558.00, 4789.35, 3459.55,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.52, 5,   coast,   -9.32,  55565.00, 4788.40, 3458.60,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.53, 5,   coast,   -8.34,  55561.00, 4788.94, 3459.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.54, 5,   coast,  -14.22,  55558.00, 4789.35, 3459.55,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.54, 5,   coast,  -14.22,  55558.00, 4789.35, 3459.55,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.55, 5,   coast,   -9.81,  55550.00, 4790.43, 3460.63,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.56, 5,   coast,  -11.28,  55533.00, 4792.73, 3462.93,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.57, 5,   coast,  -12.75,  55531.00, 4793.00, 3463.20,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.58, 5,   coast,  -12.75,  55509.00, 4795.99, 3466.18,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.59, 5,   coast,  -12.75,  55515.00, 4795.17, 3465.37,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.60, 5,   coast,  -13.24,  55503.00, 4796.80, 3467.00,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.61, 5,   coast,  -12.75,  55502.00, 4796.93, 3467.13,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.62, 5,   coast,  -11.77,  55505.00, 4796.53, 3466.73,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.63, 5,   coast,   -9.81,  55492.00, 4798.29, 3468.49,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.64, 5,   coast,  -10.79,  55481.00, 4799.78, 3469.98,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.65, 5,   coast,  -11.28,  55475.00, 4800.59, 3470.79,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.66, 5,   coast,  -10.79,  55472.00, 4801.00, 3471.20,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.67, 5,   coast,  -12.26,  55462.00, 4802.36, 3472.56,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.68, 5,   coast,  -10.79,  55453.00, 4803.58, 3473.78,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.69, 5,   coast,  -11.77,  55444.00, 4804.80, 3475.00,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.70, 5,   coast,  -11.28,  55421.00, 4807.92, 3478.12,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.71, 5,   coast,  -14.22,  55434.00, 4806.15, 3476.35,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.72, 5,   coast,  -10.79,  55419.00, 4808.19, 3478.39,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.73, 5,   coast,  -10.79,  55416.00, 4808.60, 3478.80,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.74, 5,   coast,  -11.28,  55416.00, 4808.60, 3478.80,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.75, 5,   coast,  -12.26,  55398.00, 4811.04, 3481.24,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.76, 5,   coast,  -10.79,  55383.00, 4813.07, 3483.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.77, 5,   coast,  -11.77,  55372.00, 4814.57, 3484.77,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.78, 5,   coast,  -13.73,  55375.00, 4814.16, 3484.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.79, 5,   coast,  -11.77,  55378.00, 4813.75, 3483.95,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.80, 5,   coast,  -10.30,  55361.00, 4816.06, 3486.26,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.81, 5,   coast,  -11.77,  55356.00, 4816.74, 3486.94,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.82, 5,   coast,  -11.28,  55356.00, 4816.74, 3486.94,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.83, 5,   coast,  -10.79,  55343.00, 4818.51, 3488.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.84, 5,   coast,  -11.77,  55333.00, 4819.87, 3490.06,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.85, 5,   coast,  -11.77,  55331.00, 4820.14, 3490.34,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.86, 5,   coast,  -12.26,  55322.00, 4821.36, 3491.56,     NaN, 33.9, 3.99, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.86, 5,   coast,  -12.26,  55322.00, 4821.36, 3491.56,     NaN, 33.9, 3.99, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.87, 5,   coast,  -11.28,  55313.00, 4822.58, 3492.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.88, 5,   coast,  -11.77,  55321.00, 4821.50, 3491.69,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.89, 5,   coast,   -9.81,  55305.00, 4823.67, 3493.87,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.90, 5,   coast,  -10.30,  55296.00, 4824.89, 3495.09,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.91, 5,   coast,  -11.28,  55280.00, 4827.07, 3497.27,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.92, 5,   coast,  -10.79,  55287.00, 4826.12, 3496.32,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.93, 5,   coast,  -10.30,  55280.00, 4827.07, 3497.27,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.94, 5,   coast,  -12.75,  55274.00, 4827.88, 3498.08,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.95, 5,   coast,  -13.24,  55255.00, 4830.47, 3500.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.96, 5,   coast,  -14.22,  55258.00, 4830.06, 3500.26,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.97, 5,   coast,  -14.22,  55257.00, 4830.20, 3500.40,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.98, 5,   coast,  -12.75,  55248.00, 4831.42, 3501.62,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    19.99, 5,   coast,  -10.30,  55232.00, 4833.60, 3503.80,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.00, 5,   coast,  -11.28,  55232.00, 4833.60, 3503.80,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.01, 5,   coast,   -9.81,  55223.00, 4834.82, 3505.02,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.02, 5,   coast,  -13.24,  55212.00, 4836.32, 3506.52,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.03, 5,   coast,  -11.28,  55208.00, 4836.86, 3507.06,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.04, 5,   coast,  -11.28,  55214.00, 4836.05, 3506.25,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.05, 5,   coast,  -11.28,  55194.00, 4838.77, 3508.97,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.06, 5,   coast,   -9.32,  55198.00, 4838.22, 3508.42,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.07, 5,   coast,   -9.81,  55189.00, 4839.45, 3509.65,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.08, 5,   coast,  -10.79,  55176.00, 4841.22, 3511.42,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.09, 5,   coast,  -12.75,  55172.00, 4841.76, 3511.96,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.10, 5,   coast,   -9.81,  55168.00, 4842.31, 3512.51,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.11, 5,   coast,  -12.26,  55168.00, 4842.31, 3512.51,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.12, 5,   coast,   -9.32,  55154.00, 4844.22, 3514.42,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.13, 5,   coast,   -9.81,  55131.00, 4847.35, 3517.55,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.14, 5,   coast,  -11.28,  55149.00, 4844.90, 3515.10,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.15, 5,   coast,  -10.30,  55141.00, 4845.99, 3516.19,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.16, 5,   coast,  -11.28,  55129.00, 4847.62, 3517.82,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.17, 5,   coast,  -11.28,  55120.00, 4848.85, 3519.05,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.18, 5,   coast,   -9.32,  55107.00, 4850.62, 3520.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.18, 5,   coast,   -9.32,  55107.00, 4850.62, 3520.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.19, 5,   coast,  -10.30,  55108.00, 4850.48, 3520.68,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.20, 5,   coast,  -12.75,  55110.00, 4850.21, 3520.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.21, 5,   coast,  -14.22,  55091.00, 4852.80, 3523.00,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.22, 5,   coast,  -10.79,  55084.00, 4853.76, 3523.96,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.23, 5,   coast,  -10.79,  55090.00, 4852.94, 3523.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.24, 5,   coast,  -11.77,  55080.00, 4854.30, 3524.50,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.25, 5,   coast,  -11.28,  55087.00, 4853.35, 3523.55,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.26, 5,   coast,  -11.28,  55062.00, 4856.76, 3526.96,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.27, 5,   coast,   -9.32,  55058.00, 4857.30, 3527.50,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.28, 5,   coast,  -11.77,  55046.00, 4858.94, 3529.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.29, 5,   coast,  -10.30,  55049.00, 4858.53, 3528.73,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.30, 5,   coast,  -12.75,  55037.00, 4860.17, 3530.37,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9412842,-106.9148084,  5015.0, 2022,  6, 24, 15, 17, 36,      372,     3640, 302,  84,   1.4,   0.8,   1.1,  0, 22, 31,  0,  0, 26,  0,  0,  0,  0, 25, 26, 30, 37,  0,  0, 29,  0, 30, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 19,  0,  0
+6, 6583, 3,VE3LIC,    20.31, 5,   coast,  -10.79,  55022.00, 4862.21, 3532.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.31, 5,   coast,  -10.79,  55022.00, 4862.21, 3532.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.31, 5,   coast,  -10.79,  55022.00, 4862.21, 3532.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.32, 5,   coast,  -11.77,  55015.00, 4863.17, 3533.37,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.33, 5,   coast,  -13.24,  55015.00, 4863.17, 3533.37,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.34, 5,   coast,  -10.30,  55020.00, 4862.49, 3532.69,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.35, 5,   coast,  -11.28,  55005.00, 4864.53, 3534.73,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.36, 5,   coast,  -12.75,  55015.00, 4863.17, 3533.37,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.37, 5,   coast,   -8.83,  54994.00, 4866.04, 3536.24,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.38, 5,   coast,  -11.28,  54993.00, 4866.17, 3536.37,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.39, 5,   coast,   -7.35,  54985.00, 4867.27, 3537.46,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.40, 5,   coast,  -11.28,  54971.00, 4869.18, 3539.38,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.41, 5,   coast,   -9.32,  54972.00, 4869.04, 3539.24,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.42, 5,   coast,   -9.81,  54965.00, 4870.00, 3540.20,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.43, 5,   coast,  -11.77,  54960.00, 4870.68, 3540.88,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.44, 5,   coast,   -9.32,  54937.00, 4873.82, 3544.02,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.45, 5,   coast,   -8.83,  54940.00, 4873.41, 3543.61,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.46, 5,   coast,  -12.26,  54942.00, 4873.14, 3543.34,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.47, 5,   coast,  -11.77,  54935.00, 4874.10, 3544.29,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.48, 5,   coast,   -8.83,  54923.00, 4875.74, 3545.93,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.49, 5,   coast,  -13.24,  54915.00, 4876.83, 3547.03,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.50, 5,   coast,  -12.26,  54908.00, 4877.79, 3547.98,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.50, 5,   coast,  -12.26,  54908.00, 4877.79, 3547.98,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.51, 5,   coast,  -10.30,  54912.00, 4877.24, 3547.44,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.52, 5,   coast,   -9.81,  54899.00, 4879.02, 3549.22,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.53, 5,   coast,  -13.24,  54891.00, 4880.11, 3550.31,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.54, 5,   coast,   -8.34,  54889.00, 4880.38, 3550.58,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.55, 5,   coast,   -8.34,  54877.00, 4882.02, 3552.22,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.56, 5,   coast,  -13.24,  54875.00, 4882.30, 3552.50,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.57, 5,   coast,  -11.28,  54878.00, 4881.89, 3552.09,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.58, 5,   coast,  -11.77,  54868.00, 4883.26, 3553.45,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.59, 5,   coast,  -11.28,  54857.00, 4884.76, 3554.96,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.60, 5,   coast,  -11.28,  54846.00, 4886.27, 3556.46,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.61, 5,   coast,  -10.30,  54852.00, 4885.44, 3555.64,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.62, 5,   coast,   -8.34,  54840.00, 4887.09, 3557.29,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.63, 5,   coast,  -11.77,  54834.00, 4887.91, 3558.11,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.64, 5,   coast,  -10.30,  54825.00, 4889.14, 3559.34,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.65, 5,   coast,   -9.81,  54825.00, 4889.14, 3559.34,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.66, 5,   coast,   -9.81,  54821.00, 4889.69, 3559.89,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.67, 5,   coast,  -13.73,  54807.00, 4891.60, 3561.80,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.68, 5,   coast,  -12.75,  54800.00, 4892.56, 3562.76,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.69, 5,   coast,  -11.28,  54798.00, 4892.84, 3563.04,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.70, 5,   coast,  -10.30,  54797.00, 4892.97, 3563.17,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.71, 5,   coast,  -12.26,  54785.00, 4894.62, 3564.82,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.72, 5,   coast,   -8.83,  54780.00, 4895.30, 3565.50,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.73, 5,   coast,   -9.81,  54778.00, 4895.58, 3565.77,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.74, 5,   coast,  -13.24,  54772.00, 4896.40, 3566.60,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.75, 5,   coast,   -8.83,  54765.00, 4897.36, 3567.56,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.76, 5,   coast,  -10.30,  54758.00, 4898.31, 3568.51,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.77, 5,   coast,  -11.77,  54757.00, 4898.45, 3568.65,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.78, 5,   coast,  -10.30,  54749.00, 4899.55, 3569.75,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.79, 5,   coast,   -8.83,  54731.00, 4902.02, 3572.21,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.80, 5,   coast,  -11.28,  54733.00, 4901.74, 3571.94,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.81, 5,   coast,  -11.28,  54724.00, 4902.97, 3573.17,     NaN, 33.9, 3.97, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.82, 5,   coast,  -10.79,  54729.00, 4902.29, 3572.49,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.82, 5,   coast,  -10.79,  54729.00, 4902.29, 3572.49,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  63.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.83, 5,   coast,  -10.79,  54711.00, 4904.76, 3574.96,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.84, 5,   coast,  -10.30,  54713.00, 4904.48, 3574.68,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.85, 5,   coast,  -10.79,  54700.00, 4906.27, 3576.46,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.86, 5,   coast,  -11.77,  54701.00, 4906.13, 3576.33,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.87, 5,   coast,  -11.77,  54689.00, 4907.77, 3577.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.88, 5,   coast,  -12.26,  54700.00, 4906.27, 3576.46,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.89, 5,   coast,  -13.24,  54677.00, 4909.42, 3579.62,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.90, 5,   coast,  -11.77,  54682.00, 4908.73, 3578.93,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.91, 5,   coast,  -12.26,  54672.00, 4910.11, 3580.30,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.92, 5,   coast,  -12.26,  54657.00, 4912.16, 3582.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.93, 5,   coast,  -11.28,  54648.00, 4913.40, 3583.60,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.94, 5,   coast,  -12.75,  54645.00, 4913.81, 3584.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.95, 5,   coast,  -10.79,  54640.00, 4914.50, 3584.70,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.96, 5,   coast,  -11.77,  54634.00, 4915.32, 3585.52,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.97, 5,   coast,  -11.77,  54638.00, 4914.77, 3584.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.98, 5,   coast,   -9.81,  54624.00, 4916.69, 3586.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    20.99, 5,   coast,  -10.30,  54636.00, 4915.05, 3585.24,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.00, 5,   coast,   -7.85,  54613.00, 4918.20, 3588.40,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.01, 5,   coast,   -9.81,  54605.00, 4919.30, 3589.50,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.02, 5,   coast,  -11.28,  54613.00, 4918.20, 3588.40,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.03, 5,   coast,  -10.30,  54581.00, 4922.60, 3592.80,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.04, 5,   coast,   -8.34,  54595.00, 4920.67, 3590.87,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.05, 5,   coast,   -8.34,  54579.00, 4922.87, 3593.07,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.06, 5,   coast,   -9.32,  54578.00, 4923.01, 3593.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.07, 5,   coast,  -11.28,  54567.00, 4924.52, 3594.72,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.08, 5,   coast,  -10.30,  54551.00, 4926.72, 3596.92,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.09, 5,   coast,  -11.28,  54565.00, 4924.80, 3595.00,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.10, 5,   coast,   -7.85,  54555.00, 4926.17, 3596.37,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.11, 5,   coast,  -11.77,  54541.00, 4928.09, 3598.29,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.12, 5,   coast,   -9.81,  54539.00, 4928.37, 3598.57,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.13, 5,   coast,  -10.79,  54546.00, 4927.41, 3597.61,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.14, 5,   coast,  -10.79,  54529.00, 4929.74, 3599.94,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.14, 5,   coast,  -10.79,  54529.00, 4929.74, 3599.94,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.15, 5,   coast,  -13.24,  54530.00, 4929.61, 3599.81,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.16, 5,   coast,  -10.79,  54522.00, 4930.71, 3600.91,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.17, 5,   coast,  -11.77,  54509.00, 4932.49, 3602.69,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.18, 5,   coast,   -6.37,  54502.00, 4933.46, 3603.66,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.19, 5,   coast,  -11.77,  54512.00, 4932.08, 3602.28,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.20, 5,   coast,  -11.28,  54498.00, 4934.01, 3604.21,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.21, 5,   coast,  -12.75,  54500.00, 4933.73, 3603.93,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.22, 5,   coast,   -9.81,  54484.00, 4935.93, 3606.13,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.23, 5,   coast,   -7.85,  54469.00, 4938.00, 3608.20,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.24, 5,   coast,  -12.75,  54480.00, 4936.48, 3606.68,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.25, 5,   coast,   -9.81,  54466.00, 4938.41, 3608.61,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.26, 5,   coast,  -10.79,  54466.00, 4938.41, 3608.61,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.27, 5,   coast,  -10.79,  54449.00, 4940.75, 3610.95,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.28, 5,   coast,  -11.77,  54452.00, 4940.34, 3610.54,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.29, 5,   coast,  -10.79,  54455.00, 4939.92, 3610.12,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.30, 5,   coast,   -8.83,  54445.00, 4941.30, 3611.50,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9413720,-106.9149919,  5113.0, 2022,  6, 24, 15, 17, 37,      391,     3740, 302,  84,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 32,  0,  0,  0,  0, 37, 28, 29, 35,  0,  0, 27,  0, 35, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 20,  0,  0
+6, 6583, 3,VE3LIC,    21.31, 5,   coast,  -11.28,  54427.00, 4943.78, 3613.98,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.31, 5,   coast,  -11.28,  54427.00, 4943.78, 3613.98,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.31, 5,   coast,  -11.28,  54427.00, 4943.78, 3613.98,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.32, 5,   coast,  -11.77,  54436.00, 4942.54, 3612.74,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.33, 5,   coast,   -9.32,  54428.00, 4943.64, 3613.84,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.34, 5,   coast,  -12.26,  54412.00, 4945.84, 3616.04,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.35, 5,   coast,  -13.24,  54424.00, 4944.19, 3614.39,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.36, 5,   coast,  -12.26,  54408.00, 4946.39, 3616.59,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.37, 5,   coast,  -10.79,  54415.00, 4945.43, 3615.63,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.38, 5,   coast,  -11.28,  54396.00, 4948.05, 3618.25,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.39, 5,   coast,  -11.28,  54394.00, 4948.32, 3618.52,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.40, 5,   coast,  -10.30,  54391.00, 4948.74, 3618.93,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.41, 5,   coast,  -13.24,  54383.00, 4949.84, 3620.04,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.42, 5,   coast,  -11.77,  54373.00, 4951.22, 3621.41,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.43, 5,   coast,  -10.30,  54378.00, 4950.53, 3620.73,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.44, 5,   coast,   -9.32,  54368.00, 4951.90, 3622.10,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.45, 5,   coast,  -11.77,  54371.00, 4951.49, 3621.69,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.46, 5,   coast,  -10.30,  54363.00, 4952.59, 3622.79,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.46, 5,   coast,  -10.30,  54363.00, 4952.59, 3622.79,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  64.15,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.47, 5,   coast,  -12.75,  54356.00, 4953.56, 3623.76,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.48, 5,   coast,  -10.30,  54341.00, 4955.63, 3625.83,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.49, 5,   coast,  -11.77,  54339.00, 4955.90, 3626.10,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.50, 5,   coast,   -9.81,  54333.00, 4956.73, 3626.93,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.51, 5,   coast,   -9.81,  54328.00, 4957.42, 3627.62,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.52, 5,   coast,  -11.77,  54323.00, 4958.11, 3628.31,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.53, 5,   coast,   -8.34,  54314.00, 4959.35, 3629.55,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.54, 5,   coast,  -11.28,  54312.00, 4959.63, 3629.82,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.55, 5,   coast,  -10.30,  54309.00, 4960.04, 3630.24,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.56, 5,   coast,   -8.83,  54301.00, 4961.14, 3631.34,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.57, 5,   coast,  -11.28,  54312.00, 4959.63, 3629.82,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.58, 5,   coast,  -11.28,  54299.00, 4961.42, 3631.62,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.59, 5,   coast,  -11.28,  54276.00, 4964.59, 3634.79,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.60, 5,   coast,  -11.28,  54282.00, 4963.76, 3633.96,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.61, 5,   coast,  -12.75,  54275.00, 4964.73, 3634.93,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.62, 5,   coast,  -11.77,  54269.00, 4965.56, 3635.76,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.63, 5,   coast,  -11.28,  54264.00, 4966.25, 3636.45,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.64, 5,   coast,  -10.30,  54252.00, 4967.90, 3638.10,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.65, 5,   coast,  -12.26,  54259.00, 4966.94, 3637.14,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.66, 5,   coast,  -13.73,  54237.00, 4969.98, 3640.17,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.67, 5,   coast,  -11.28,  54244.00, 4969.01, 3639.21,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.68, 5,   coast,  -11.77,  54233.00, 4970.53, 3640.73,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.69, 5,   coast,  -11.77,  54242.00, 4969.28, 3639.48,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.70, 5,   coast,  -14.22,  54231.00, 4970.80, 3641.00,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.71, 5,   coast,   -9.81,  54224.00, 4971.77, 3641.97,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.72, 5,   coast,   -9.32,  54214.00, 4973.15, 3643.35,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.73, 5,   coast,   -8.34,  54212.00, 4973.43, 3643.63,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.74, 5,   coast,  -12.75,  54209.00, 4973.84, 3644.04,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.75, 5,   coast,  -12.75,  54198.00, 4975.36, 3645.56,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.76, 5,   coast,  -11.77,  54209.00, 4973.84, 3644.04,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.77, 5,   coast,  -10.79,  54196.00, 4975.64, 3645.84,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.78, 5,   coast,  -11.28,  54175.00, 4978.54, 3648.74,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.78, 5,   coast,  -11.28,  54175.00, 4978.54, 3648.74,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.79, 5,   coast,  -12.26,  54193.00, 4976.05, 3646.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.80, 5,   coast,  -10.30,  54177.00, 4978.26, 3648.46,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.81, 5,   coast,  -10.30,  54175.00, 4978.54, 3648.74,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.82, 5,   coast,  -10.79,  54180.00, 4977.85, 3648.05,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.83, 5,   coast,  -12.26,  54165.00, 4979.92, 3650.12,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.84, 5,   coast,  -11.28,  54162.00, 4980.34, 3650.54,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.85, 5,   coast,  -10.30,  54155.00, 4981.30, 3651.50,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.86, 5,   coast,   -8.83,  54138.00, 4983.65, 3653.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.87, 5,   coast,  -10.79,  54147.00, 4982.41, 3652.61,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.88, 5,   coast,  -11.77,  54134.00, 4984.21, 3654.41,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.89, 5,   coast,  -10.30,  54126.00, 4985.31, 3655.51,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.90, 5,   coast,  -13.24,  54122.00, 4985.87, 3656.07,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.91, 5,   coast,  -10.30,  54116.00, 4986.70, 3656.90,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.92, 5,   coast,  -11.28,  54116.00, 4986.70, 3656.90,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.93, 5,   coast,   -9.81,  54113.00, 4987.11, 3657.31,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.94, 5,   coast,  -11.28,  54106.00, 4988.08, 3658.28,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.95, 5,   coast,  -10.79,  54101.00, 4988.77, 3658.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.96, 5,   coast,  -12.75,  54087.00, 4990.71, 3660.91,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.97, 5,   coast,   -8.34,  54091.00, 4990.16, 3660.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.98, 5,   coast,   -9.81,  54088.00, 4990.57, 3660.77,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    21.99, 5,   coast,   -8.83,  54084.00, 4991.13, 3661.32,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.00, 5,   coast,   -9.81,  54080.00, 4991.68, 3661.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.01, 5,   coast,  -12.26,  54088.00, 4990.57, 3660.77,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.02, 5,   coast,  -14.22,  54059.00, 4994.59, 3664.78,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.03, 5,   coast,  -12.26,  54063.00, 4994.03, 3664.23,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.04, 5,   coast,  -12.75,  54057.00, 4994.86, 3665.06,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.05, 5,   coast,   -9.81,  54048.00, 4996.11, 3666.31,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.06, 5,   coast,   -8.83,  54040.00, 4997.22, 3667.42,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.07, 5,   coast,  -10.79,  54047.00, 4996.25, 3666.45,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.08, 5,   coast,  -12.75,  54031.00, 4998.46, 3668.66,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.09, 5,   coast,  -10.79,  54037.00, 4997.63, 3667.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.10, 5,   coast,   -8.83,  54034.00, 4998.05, 3668.25,     NaN, 33.9, 3.99, 3.99, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.10, 5,   coast,   -8.83,  54034.00, 4998.05, 3668.25,     NaN, 33.9, 3.99, 3.99, 3.99,   0.00,   0.00,   0.00,  64.15,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.11, 5,   coast,  -11.28,  54017.00, 5000.40, 3670.60,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.12, 5,   coast,  -10.30,  54020.00, 4999.99, 3670.19,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.13, 5,   coast,  -10.79,  54017.00, 5000.40, 3670.60,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.14, 5,   coast,  -10.30,  54008.00, 5001.65, 3671.85,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.15, 5,   coast,  -11.28,  54010.00, 5001.37, 3671.57,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.16, 5,   coast,  -11.28,  53997.00, 5003.17, 3673.37,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.17, 5,   coast,   -9.32,  53985.00, 5004.84, 3675.04,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.18, 5,   coast,   -8.83,  53976.00, 5006.08, 3676.28,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.19, 5,   coast,  -12.75,  53983.00, 5005.11, 3675.31,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.20, 5,   coast,   -8.34,  53980.00, 5005.53, 3675.73,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.21, 5,   coast,  -11.28,  53975.00, 5006.22, 3676.42,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.22, 5,   coast,  -10.30,  53958.00, 5008.58, 3678.78,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.23, 5,   coast,  -10.30,  53974.00, 5006.36, 3676.56,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.24, 5,   coast,  -10.30,  53979.00, 5005.67, 3675.87,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.25, 5,   coast,  -12.26,  53956.00, 5008.86, 3679.06,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.26, 5,   coast,  -11.28,  53961.00, 5008.16, 3678.36,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.27, 5,   coast,   -9.32,  53952.00, 5009.41, 3679.61,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.28, 5,   coast,   -9.81,  53933.00, 5012.05, 3682.25,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.29, 5,   coast,  -10.30,  53929.00, 5012.60, 3682.80,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.30, 5,   coast,  -12.75,  53929.00, 5012.60, 3682.80,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9414798,-106.9151756,  5200.0, 2022,  6, 24, 15, 17, 38,      412,     3828, 302,  84,   1.4,   0.8,   1.1,  0, 33, 29,  0,  0, 34,  0,  0,  0,  0, 33, 37, 30, 27,  0,  0, 27,  0, 30, 33,  0,  0,  0, 37,  0,  0,  0,  0,  0, 22,  0,  0
+6, 6583, 3,VE3LIC,    22.31, 5,   coast,   -9.81,  53923.00, 5013.43, 3683.63,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.31, 5,   coast,   -9.81,  53923.00, 5013.43, 3683.63,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.31, 5,   coast,   -9.81,  53923.00, 5013.43, 3683.63,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.32, 5,   coast,   -8.34,  53920.00, 5013.85, 3684.05,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.33, 5,   coast,   -7.85,  53919.00, 5013.99, 3684.19,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.34, 5,   coast,   -9.81,  53929.00, 5012.60, 3682.80,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.35, 5,   coast,  -11.28,  53912.00, 5014.96, 3685.16,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.36, 5,   coast,  -10.30,  53895.00, 5017.32, 3687.52,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.37, 5,   coast,  -10.30,  53909.00, 5015.38, 3685.57,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.38, 5,   coast,  -12.75,  53902.00, 5016.35, 3686.55,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.39, 5,   coast,  -10.30,  53895.00, 5017.32, 3687.52,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.40, 5,   coast,  -10.79,  53870.00, 5020.79, 3690.99,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.41, 5,   coast,  -11.28,  53884.00, 5018.85, 3689.04,     NaN, 33.9, 3.99, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.42, 5,   coast,  -10.79,  53869.00, 5020.93, 3691.13,     NaN, 33.9, 4.01, 3.98, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.42, 5,   coast,  -10.79,  53869.00, 5020.93, 3691.13,     NaN, 33.9, 4.01, 3.98, 3.99,   0.03,   0.00,   0.00,  64.21,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.43, 5,   coast,  -10.30,  53865.00, 5021.48, 3691.68,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.44, 5,   coast,  -10.79,  53868.00, 5021.07, 3691.27,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.45, 5,   coast,   -9.32,  53851.00, 5023.43, 3693.63,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.46, 5,   coast,   -9.81,  53855.00, 5022.87, 3693.07,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.47, 5,   coast,  -10.79,  53836.00, 5025.51, 3695.71,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.48, 5,   coast,   -8.83,  53852.00, 5023.29, 3693.49,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.49, 5,   coast,  -13.24,  53844.00, 5024.40, 3694.60,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.50, 5,   coast,  -11.77,  53844.00, 5024.40, 3694.60,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.51, 5,   coast,   -7.85,  53825.00, 5027.04, 3697.24,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.52, 5,   coast,  -11.28,  53823.00, 5027.32, 3697.52,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.53, 5,   coast,  -10.79,  53833.00, 5025.93, 3696.13,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.54, 5,   coast,   -9.81,  53814.00, 5028.57, 3698.77,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.55, 5,   coast,  -10.79,  53812.00, 5028.85, 3699.04,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.56, 5,   coast,   -8.83,  53817.00, 5028.15, 3698.35,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.57, 5,   coast,   -9.32,  53805.00, 5029.82, 3700.02,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.58, 5,   coast,   -6.86,  53797.00, 5030.93, 3701.13,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.59, 5,   coast,  -13.24,  53798.00, 5030.79, 3700.99,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.60, 5,   coast,  -10.79,  53795.00, 5031.21, 3701.41,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.61, 5,   coast,   -8.83,  53787.00, 5032.32, 3702.52,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.62, 5,   coast,   -9.81,  53791.00, 5031.76, 3701.96,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.63, 5,   coast,   -8.83,  53781.00, 5033.15, 3703.35,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.64, 5,   coast,  -10.30,  53780.00, 5033.29, 3703.49,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.65, 5,   coast,  -10.79,  53776.00, 5033.85, 3704.05,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.66, 5,   coast,  -11.28,  53775.00, 5033.99, 3704.19,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.67, 5,   coast,  -10.79,  53757.00, 5036.49, 3706.69,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.68, 5,   coast,  -10.79,  53762.00, 5035.80, 3705.99,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.69, 5,   coast,   -8.83,  53745.00, 5038.16, 3708.36,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.70, 5,   coast,  -10.79,  53765.00, 5035.38, 3705.58,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.71, 5,   coast,  -10.79,  53746.00, 5038.02, 3708.22,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.72, 5,   coast,   -9.32,  53741.00, 5038.72, 3708.92,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.73, 5,   coast,  -11.28,  53731.00, 5040.11, 3710.31,     NaN, 33.9, 4.01, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.74, 5,   coast,  -12.26,  53730.00, 5040.25, 3710.45,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.74, 5,   coast,  -12.26,  53730.00, 5040.25, 3710.45,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.75, 5,   coast,  -10.79,  53729.00, 5040.39, 3710.59,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.76, 5,   coast,  -10.30,  53728.00, 5040.53, 3710.72,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.77, 5,   coast,  -10.30,  53722.00, 5041.36, 3711.56,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.78, 5,   coast,   -8.34,  53721.00, 5041.50, 3711.70,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.79, 5,   coast,   -9.32,  53712.00, 5042.75, 3712.95,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.80, 5,   coast,   -9.32,  53703.00, 5044.00, 3714.20,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.81, 5,   coast,  -10.79,  53700.00, 5044.42, 3714.62,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.82, 5,   coast,  -10.79,  53682.00, 5046.93, 3717.13,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.83, 5,   coast,  -12.75,  53702.00, 5044.14, 3714.34,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.84, 5,   coast,  -10.30,  53691.00, 5045.67, 3715.87,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.85, 5,   coast,  -10.79,  53686.00, 5046.37, 3716.57,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.86, 5,   coast,   -9.81,  53679.00, 5047.35, 3717.54,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.87, 5,   coast,  -10.30,  53677.00, 5047.62, 3717.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.88, 5,   coast,   -9.81,  53684.00, 5046.65, 3716.85,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.89, 5,   coast,   -9.81,  53659.00, 5050.13, 3720.33,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.90, 5,   coast,   -9.81,  53660.00, 5049.99, 3720.19,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.91, 5,   coast,  -10.79,  53666.00, 5049.16, 3719.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.92, 5,   coast,  -10.30,  53653.00, 5050.97, 3721.17,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.93, 5,   coast,   -9.81,  53649.00, 5051.52, 3721.72,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.94, 5,   coast,   -6.86,  53655.00, 5050.69, 3720.89,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.95, 5,   coast,  -11.28,  53644.00, 5052.22, 3722.42,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.96, 5,   coast,   -9.81,  53641.00, 5052.64, 3722.84,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.97, 5,   coast,   -9.32,  53629.00, 5054.31, 3724.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.98, 5,   coast,   -9.81,  53640.00, 5052.78, 3722.98,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    22.99, 5,   coast,  -10.79,  53623.00, 5055.15, 3725.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.00, 5,   coast,  -12.26,  53634.00, 5053.61, 3723.81,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.01, 5,   coast,   -9.81,  53624.00, 5055.01, 3725.21,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.02, 5,   coast,   -8.83,  53613.00, 5056.54, 3726.74,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.03, 5,   coast,  -11.28,  53612.00, 5056.68, 3726.88,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.04, 5,   coast,   -8.83,  53608.00, 5057.24, 3727.44,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.05, 5,   coast,  -10.79,  53595.00, 5059.05, 3729.25,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.06, 5,   coast,  -10.79,  53597.00, 5058.77, 3728.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.06, 5,   coast,  -10.79,  53597.00, 5058.77, 3728.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.07, 5,   coast,  -11.77,  53593.00, 5059.33, 3729.53,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.08, 5,   coast,   -9.81,  53597.00, 5058.77, 3728.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.09, 5,   coast,   -8.83,  53586.00, 5060.30, 3730.50,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.10, 5,   coast,  -11.28,  53586.00, 5060.30, 3730.50,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.11, 5,   coast,  -11.77,  53573.00, 5062.12, 3732.32,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.12, 5,   coast,   -9.81,  53592.00, 5059.47, 3729.67,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.13, 5,   coast,  -10.30,  53568.00, 5062.81, 3733.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.14, 5,   coast,  -10.30,  53563.00, 5063.51, 3733.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.15, 5,   coast,  -12.75,  53562.00, 5063.65, 3733.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.16, 5,   coast,  -12.26,  53548.00, 5065.60, 3735.80,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.17, 5,   coast,  -11.77,  53559.00, 5064.07, 3734.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.18, 5,   coast,  -11.77,  53535.00, 5067.42, 3737.62,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.19, 5,   coast,   -8.34,  53558.00, 5064.21, 3734.41,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.20, 5,   coast,  -11.28,  53544.00, 5066.16, 3736.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.21, 5,   coast,  -13.24,  53548.00, 5065.60, 3735.80,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.22, 5,   coast,  -10.30,  53516.00, 5070.07, 3740.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.23, 5,   coast,  -12.75,  53517.00, 5069.93, 3740.13,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.24, 5,   coast,  -10.79,  53516.00, 5070.07, 3740.27,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.25, 5,   coast,   -8.83,  53521.00, 5069.37, 3739.57,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.26, 5,   coast,  -12.26,  53519.00, 5069.65, 3739.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.27, 5,   coast,   -9.32,  53498.00, 5072.58, 3742.78,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.28, 5,   coast,   -9.32,  53510.00, 5070.91, 3741.11,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.29, 5,   coast,  -10.79,  53512.00, 5070.63, 3740.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.30, 5,   coast,  -13.73,  53506.00, 5071.47, 3741.66,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9415781,-106.9153472,  5276.0, 2022,  6, 24, 15, 17, 39,      432,     3906, 302,  84,   1.4,   0.8,   1.1,  0, 32, 20,  0,  0, 35,  0,  0,  0,  0, 30, 34, 25, 29,  0,  0, 38,  0, 34, 27,  0,  0,  0, 32,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,    23.31, 5,   coast,  -10.30,  53491.00, 5073.56, 3743.76,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.31, 5,   coast,  -10.30,  53491.00, 5073.56, 3743.76,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.31, 5,   coast,  -10.30,  53491.00, 5073.56, 3743.76,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.32, 5,   coast,  -10.79,  53483.00, 5074.68, 3744.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.33, 5,   coast,  -11.28,  53492.00, 5073.42, 3743.62,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.34, 5,   coast,   -9.81,  53488.00, 5073.98, 3744.18,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.35, 5,   coast,   -8.34,  53477.00, 5075.51, 3745.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.36, 5,   coast,  -10.30,  53472.00, 5076.21, 3746.41,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.37, 5,   coast,   -8.34,  53482.00, 5074.82, 3745.02,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.38, 5,   coast,  -12.26,  53466.00, 5077.05, 3747.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.38, 5,   coast,  -12.26,  53466.00, 5077.05, 3747.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.39, 5,   coast,  -10.79,  53466.00, 5077.05, 3747.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.40, 5,   coast,   -9.81,  53454.00, 5078.73, 3748.93,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.41, 5,   coast,  -10.30,  53451.00, 5079.15, 3749.35,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.42, 5,   coast,  -11.28,  53463.00, 5077.47, 3747.67,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.43, 5,   coast,  -12.75,  53448.00, 5079.57, 3749.76,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.44, 5,   coast,  -12.75,  53446.00, 5079.85, 3750.04,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.45, 5,   coast,  -10.79,  53436.00, 5081.24, 3751.44,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.46, 5,   coast,  -10.79,  53450.00, 5079.29, 3749.49,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.47, 5,   coast,  -13.73,  53439.00, 5080.82, 3751.02,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.48, 5,   coast,   -9.81,  53435.00, 5081.38, 3751.58,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.49, 5,   coast,  -11.28,  53434.00, 5081.52, 3751.72,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.50, 5,   coast,  -10.30,  53440.00, 5080.68, 3750.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.51, 5,   coast,  -10.79,  53429.00, 5082.22, 3752.42,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.52, 5,   coast,   -8.83,  53415.00, 5084.18, 3754.38,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.53, 5,   coast,  -11.77,  53406.00, 5085.44, 3755.64,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.54, 5,   coast,   -7.85,  53402.00, 5086.00, 3756.19,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.55, 5,   coast,  -14.71,  53402.00, 5086.00, 3756.19,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.56, 5,   coast,  -11.28,  53397.00, 5086.69, 3756.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.57, 5,   coast,   -9.32,  53392.00, 5087.39, 3757.59,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.58, 5,   coast,  -10.79,  53408.00, 5085.16, 3755.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.59, 5,   coast,  -10.30,  53395.00, 5086.97, 3757.17,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.60, 5,   coast,  -12.26,  53381.00, 5088.93, 3759.13,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.61, 5,   coast,  -10.79,  53385.00, 5088.37, 3758.57,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.62, 5,   coast,  -10.79,  53384.00, 5088.51, 3758.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.63, 5,   coast,   -7.35,  53372.00, 5090.19, 3760.39,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.64, 5,   coast,  -10.30,  53383.00, 5088.65, 3758.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.65, 5,   coast,   -9.81,  53379.00, 5089.21, 3759.41,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.66, 5,   coast,   -7.85,  53359.00, 5092.01, 3762.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.67, 5,   coast,  -11.28,  53352.00, 5092.99, 3763.19,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.68, 5,   coast,  -12.26,  53359.00, 5092.01, 3762.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.69, 5,   coast,  -10.79,  53343.00, 5094.25, 3764.45,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.70, 5,   coast,   -8.34,  53359.00, 5092.01, 3762.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.70, 5,   coast,   -8.34,  53359.00, 5092.01, 3762.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.71, 5,   coast,   -9.32,  53347.00, 5093.69, 3763.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.72, 5,   coast,  -12.26,  53345.00, 5093.97, 3764.17,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.73, 5,   coast,   -8.34,  53333.00, 5095.65, 3765.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.74, 5,   coast,  -11.28,  53326.00, 5096.63, 3766.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.75, 5,   coast,  -12.26,  53326.00, 5096.63, 3766.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.76, 5,   coast,  -11.28,  53336.00, 5095.23, 3765.43,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.77, 5,   coast,   -9.81,  53325.00, 5096.77, 3766.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.78, 5,   coast,  -11.77,  53321.00, 5097.33, 3767.53,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.79, 5,   coast,  -10.79,  53319.00, 5097.61, 3767.81,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.80, 5,   coast,   -9.32,  53314.00, 5098.31, 3768.51,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.81, 5,   coast,  -12.75,  53303.00, 5099.85, 3770.05,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.82, 5,   coast,  -11.28,  53315.00, 5098.17, 3768.37,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.83, 5,   coast,  -11.77,  53298.00, 5100.55, 3770.75,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.84, 5,   coast,   -9.81,  53314.00, 5098.31, 3768.51,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.85, 5,   coast,  -13.24,  53294.00, 5101.11, 3771.31,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.86, 5,   coast,  -10.79,  53287.00, 5102.09, 3772.29,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.87, 5,   coast,   -9.32,  53286.00, 5102.23, 3772.43,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.88, 5,   coast,   -9.32,  53290.00, 5101.67, 3771.87,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.89, 5,   coast,   -8.83,  53275.00, 5103.77, 3773.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.90, 5,   coast,   -9.32,  53286.00, 5102.23, 3772.43,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.91, 5,   coast,   -8.83,  53270.00, 5104.47, 3774.67,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.92, 5,   coast,  -10.79,  53283.00, 5102.65, 3772.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.93, 5,   coast,   -9.81,  53274.00, 5103.91, 3774.11,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.94, 5,   coast,  -11.77,  53269.00, 5104.61, 3774.81,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.95, 5,   coast,  -10.30,  53263.00, 5105.45, 3775.65,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.96, 5,   coast,  -10.79,  53256.00, 5106.43, 3776.63,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.97, 5,   coast,   -9.32,  53259.00, 5106.01, 3776.21,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.98, 5,   coast,  -10.79,  53249.00, 5107.41, 3777.61,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    23.99, 5,   coast,  -14.22,  53239.00, 5108.81, 3779.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.00, 5,   coast,  -10.79,  53253.00, 5106.85, 3777.05,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.01, 5,   coast,  -11.28,  53247.00, 5107.69, 3777.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.02, 5,   coast,  -10.79,  53235.00, 5109.38, 3779.57,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.02, 5,   coast,  -10.79,  53235.00, 5109.38, 3779.57,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.03, 5,   coast,   -9.81,  53240.00, 5108.67, 3778.87,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.04, 5,   coast,  -10.79,  53229.00, 5110.22, 3780.42,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.05, 5,   coast,   -9.81,  53224.00, 5110.92, 3781.12,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.06, 5,   coast,  -11.28,  53226.00, 5110.64, 3780.84,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.07, 5,   coast,  -11.77,  53229.00, 5110.22, 3780.42,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.08, 5,   coast,  -13.24,  53212.00, 5112.60, 3782.80,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.09, 5,   coast,  -10.30,  53210.00, 5112.88, 3783.08,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.10, 5,   coast,   -9.32,  53209.00, 5113.02, 3783.22,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.11, 5,   coast,   -6.86,  53214.00, 5112.32, 3782.52,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.12, 5,   coast,   -8.83,  53202.00, 5114.00, 3784.20,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.13, 5,   coast,  -12.26,  53184.00, 5116.53, 3786.73,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.14, 5,   coast,  -10.30,  53204.00, 5113.72, 3783.92,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.15, 5,   coast,  -10.79,  53191.00, 5115.55, 3785.74,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.16, 5,   coast,  -11.77,  53187.00, 5116.11, 3786.31,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.17, 5,   coast,  -11.77,  53183.00, 5116.67, 3786.87,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.18, 5,   coast,   -9.32,  53184.00, 5116.53, 3786.73,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.19, 5,   coast,  -10.79,  53170.00, 5118.49, 3788.69,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.20, 5,   coast,  -12.26,  53173.00, 5118.07, 3788.27,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.21, 5,   coast,  -10.30,  53164.00, 5119.33, 3789.53,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.22, 5,   coast,  -11.28,  53173.00, 5118.07, 3788.27,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.23, 5,   coast,  -12.75,  53177.00, 5117.51, 3787.71,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.24, 5,   coast,  -10.79,  53148.00, 5121.58, 3791.78,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.25, 5,   coast,   -9.81,  53164.00, 5119.33, 3789.53,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.26, 5,   coast,  -11.28,  53164.00, 5119.33, 3789.53,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.27, 5,   coast,  -13.73,  53138.00, 5122.98, 3793.18,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.28, 5,   coast,   -9.81,  53145.00, 5122.00, 3792.20,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.29, 5,   coast,   -8.34,  53144.00, 5122.14, 3792.34,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.30, 5,   coast,   -9.81,  53132.00, 5123.83, 3794.02,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9416765,-106.9155211,  5341.0, 2022,  6, 24, 15, 17, 40,      451,     3973, 302,  83,   1.4,   0.8,   1.1,  0, 26, 33,  0,  0, 31,  0,  0,  0,  0, 24, 21, 31, 37,  0,  0, 25,  0, 30, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    24.31, 5,   coast,   -9.32,  53143.00, 5122.28, 3792.48,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.31, 5,   coast,   -9.32,  53143.00, 5122.28, 3792.48,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.31, 5,   coast,   -9.32,  53143.00, 5122.28, 3792.48,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.32, 5,   coast,  -13.24,  53138.00, 5122.98, 3793.18,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.33, 5,   coast,   -9.32,  53130.00, 5124.11, 3794.30,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.34, 5,   coast,   -9.81,  53113.00, 5126.49, 3796.69,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.34, 5,   coast,   -9.81,  53113.00, 5126.49, 3796.69,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.35, 5,   coast,  -11.28,  53130.00, 5124.11, 3794.30,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.36, 5,   coast,  -10.79,  53122.00, 5125.23, 3795.43,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.37, 5,   coast,  -10.79,  53120.00, 5125.51, 3795.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.38, 5,   coast,   -9.32,  53125.00, 5124.81, 3795.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.39, 5,   coast,  -10.30,  53114.00, 5126.35, 3796.55,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.40, 5,   coast,   -9.81,  53110.00, 5126.91, 3797.11,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.41, 5,   coast,  -12.75,  53099.00, 5128.46, 3798.66,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.42, 5,   coast,  -11.77,  53109.00, 5127.05, 3797.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.43, 5,   coast,  -11.28,  53093.00, 5129.30, 3799.50,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.44, 5,   coast,  -10.79,  53092.00, 5129.44, 3799.64,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.45, 5,   coast,  -12.75,  53095.00, 5129.02, 3799.22,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.46, 5,   coast,  -11.77,  53088.00, 5130.00, 3800.20,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.47, 5,   coast,  -12.26,  53098.00, 5128.60, 3798.80,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.48, 5,   coast,  -12.26,  53094.00, 5129.16, 3799.36,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.49, 5,   coast,   -9.81,  53077.00, 5131.55, 3801.75,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.50, 5,   coast,  -10.30,  53076.00, 5131.69, 3801.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.51, 5,   coast,  -11.28,  53083.00, 5130.71, 3800.91,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.52, 5,   coast,   -8.34,  53076.00, 5131.69, 3801.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.53, 5,   coast,  -10.30,  53073.00, 5132.11, 3802.31,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.54, 5,   coast,  -11.77,  53069.00, 5132.67, 3802.87,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.55, 5,   coast,  -11.28,  53072.00, 5132.25, 3802.45,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.56, 5,   coast,  -10.79,  53065.00, 5133.24, 3803.44,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.57, 5,   coast,   -9.81,  53062.00, 5133.66, 3803.86,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.58, 5,   coast,  -11.28,  53053.00, 5134.92, 3805.12,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.59, 5,   coast,  -13.73,  53056.00, 5134.50, 3804.70,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.60, 5,   coast,   -8.83,  53050.00, 5135.34, 3805.54,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.61, 5,   coast,  -12.26,  53043.00, 5136.33, 3806.53,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.62, 5,   coast,   -6.86,  53044.00, 5136.19, 3806.39,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.63, 5,   coast,  -10.30,  53038.00, 5137.03, 3807.23,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.64, 5,   coast,  -10.79,  53045.00, 5136.05, 3806.25,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.65, 5,   coast,  -12.26,  53032.00, 5137.88, 3808.07,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.66, 5,   coast,   -9.81,  53031.00, 5138.02, 3808.22,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.66, 5,   coast,   -9.81,  53031.00, 5138.02, 3808.22,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.67, 5,   coast,  -11.28,  53027.00, 5138.58, 3808.78,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.68, 5,   coast,   -9.81,  53041.00, 5136.61, 3806.81,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.69, 5,   coast,   -8.34,  53029.00, 5138.30, 3808.50,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.70, 5,   coast,  -10.30,  53021.00, 5139.42, 3809.62,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.71, 5,   coast,  -10.30,  53012.00, 5140.69, 3810.89,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.72, 5,   coast,  -11.77,  53011.00, 5140.83, 3811.03,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.73, 5,   coast,  -11.28,  53016.00, 5140.13, 3810.32,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.74, 5,   coast,  -11.28,  53006.00, 5141.53, 3811.73,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.75, 5,   coast,  -12.26,  53011.00, 5140.83, 3811.03,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.76, 5,   coast,  -10.79,  53006.00, 5141.53, 3811.73,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.77, 5,   coast,  -10.30,  53002.00, 5142.09, 3812.29,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.78, 5,   coast,   -7.85,  53011.00, 5140.83, 3811.03,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.79, 5,   coast,   -9.81,  52996.00, 5142.94, 3813.14,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.80, 5,   coast,   -8.34,  52990.00, 5143.78, 3813.98,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.81, 5,   coast,  -10.79,  53001.00, 5142.24, 3812.43,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.82, 5,   coast,   -8.83,  52973.00, 5146.18, 3816.37,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.83, 5,   coast,   -8.83,  52987.00, 5144.21, 3814.40,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.84, 5,   coast,   -8.34,  52986.00, 5144.35, 3814.55,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.85, 5,   coast,   -8.83,  52975.00, 5145.89, 3816.09,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.86, 5,   coast,  -12.75,  52978.00, 5145.47, 3815.67,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.87, 5,   coast,  -11.77,  52974.00, 5146.03, 3816.23,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.88, 5,   coast,  -10.30,  52966.00, 5147.16, 3817.36,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.89, 5,   coast,  -11.77,  52972.00, 5146.32, 3816.52,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.90, 5,   coast,  -10.30,  52959.00, 5148.15, 3818.35,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.91, 5,   coast,  -11.28,  52953.00, 5148.99, 3819.19,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.92, 5,   coast,   -7.85,  52970.00, 5146.60, 3816.80,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.93, 5,   coast,  -10.79,  52952.00, 5149.13, 3819.33,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.94, 5,   coast,   -8.83,  52955.00, 5148.71, 3818.91,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.95, 5,   coast,   -8.34,  52951.00, 5149.27, 3819.47,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.96, 5,   coast,   -9.32,  52953.00, 5148.99, 3819.19,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.97, 5,   coast,  -10.30,  52956.00, 5148.57, 3818.77,     NaN, 33.9, 4.00, 3.98, 3.98,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.98, 5,   coast,  -10.79,  52940.00, 5150.82, 3821.02,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.98, 5,   coast,  -10.79,  52940.00, 5150.82, 3821.02,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.01,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    24.99, 5,   coast,  -11.28,  52932.00, 5151.95, 3822.15,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.00, 5,   coast,  -10.30,  52941.00, 5150.68, 3820.88,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.01, 5,   coast,  -11.77,  52934.00, 5151.67, 3821.87,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.02, 5,   coast,   -8.83,  52936.00, 5151.38, 3821.58,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.03, 5,   coast,  -11.77,  52917.00, 5154.06, 3824.26,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.04, 5,   coast,   -9.32,  52919.00, 5153.78, 3823.98,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.05, 5,   coast,   -8.83,  52926.00, 5152.79, 3822.99,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.06, 5,   coast,   -8.34,  52921.00, 5153.50, 3823.70,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.07, 5,   coast,  -10.30,  52923.00, 5153.22, 3823.41,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.08, 5,   coast,   -8.83,  52920.00, 5153.64, 3823.84,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.09, 5,   coast,   -8.34,  52920.00, 5153.64, 3823.84,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.10, 5,   coast,  -12.26,  52911.00, 5154.91, 3825.10,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.11, 5,   coast,   -9.81,  52914.00, 5154.48, 3824.68,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.12, 5,   coast,  -11.77,  52912.00, 5154.76, 3824.96,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.13, 5,   coast,  -11.28,  52915.00, 5154.34, 3824.54,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.14, 5,   coast,  -10.79,  52898.00, 5156.74, 3826.94,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.15, 5,   coast,   -9.32,  52897.00, 5156.88, 3827.08,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.16, 5,   coast,  -10.30,  52898.00, 5156.74, 3826.94,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.17, 5,   coast,   -8.34,  52891.00, 5157.72, 3827.92,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.18, 5,   coast,  -10.79,  52892.00, 5157.58, 3827.78,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.19, 5,   coast,   -8.34,  52887.00, 5158.29, 3828.49,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.20, 5,   coast,   -8.34,  52888.00, 5158.15, 3828.35,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.21, 5,   coast,   -9.81,  52877.00, 5159.70, 3829.90,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.22, 5,   coast,  -10.30,  52875.00, 5159.98, 3830.18,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.23, 5,   coast,   -9.81,  52873.00, 5160.26, 3830.46,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.24, 5,   coast,   -9.32,  52882.00, 5158.99, 3829.19,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.25, 5,   coast,  -13.24,  52880.00, 5159.27, 3829.47,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.26, 5,   coast,  -13.24,  52879.00, 5159.41, 3829.61,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.27, 5,   coast,   -9.81,  52873.00, 5160.26, 3830.46,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.28, 5,   coast,  -14.71,  52865.00, 5161.39, 3831.59,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.29, 5,   coast,  -11.28,  52859.00, 5162.23, 3832.43,     NaN, 33.9, 3.98, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.30, 5,   coast,  -10.30,  52859.00, 5162.23, 3832.43,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.30, 5,   coast,  -10.30,  52859.00, 5162.23, 3832.43,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  63.72,  64.15,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.31, 5,   coast,  -10.30,  52859.00, 5162.23, 3832.43,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.31, 5,   coast,  -10.30,  52859.00, 5162.23, 3832.43,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.31, 5,   coast,  -10.30,  52859.00, 5162.23, 3832.43,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9417745,-106.9156941,  5397.0, 2022,  6, 24, 15, 17, 41,      471,     4031, 302,  83,   1.4,   0.8,   1.1,  0, 36, 32,  0,  0, 34,  0,  0,  0,  0, 37, 30, 28, 29,  0,  0, 30,  0, 31, 25,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    25.32, 5,   coast,   -8.34,  52853.00, 5163.08, 3833.28,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.33, 5,   coast,   -6.37,  52855.00, 5162.80, 3833.00,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.34, 5,   coast,   -9.81,  52847.00, 5163.93, 3834.12,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.35, 5,   coast,  -11.28,  52844.00, 5164.35, 3834.55,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.36, 5,   coast,  -12.26,  52838.00, 5165.19, 3835.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.37, 5,   coast,   -8.34,  52837.00, 5165.34, 3835.54,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.38, 5,   coast,   -9.81,  52841.00, 5164.77, 3834.97,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.39, 5,   coast,   -7.85,  52846.00, 5164.07, 3834.27,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.40, 5,   coast,  -10.30,  52829.00, 5166.46, 3836.66,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.41, 5,   coast,  -11.77,  52844.00, 5164.35, 3834.55,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.42, 5,   coast,   -9.81,  52822.00, 5167.45, 3837.65,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.43, 5,   coast,   -6.86,  52842.00, 5164.63, 3834.83,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.44, 5,   coast,  -11.77,  52826.00, 5166.89, 3837.09,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.45, 5,   coast,  -11.77,  52813.00, 5168.72, 3838.92,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.46, 5,   coast,   -9.81,  52816.00, 5168.30, 3838.50,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.47, 5,   coast,  -10.79,  52807.00, 5169.57, 3839.77,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.48, 5,   coast,  -11.28,  52822.00, 5167.45, 3837.65,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.49, 5,   coast,   -7.85,  52809.00, 5169.29, 3839.48,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.50, 5,   coast,  -10.79,  52818.00, 5168.02, 3838.22,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.51, 5,   coast,   -9.81,  52810.00, 5169.14, 3839.34,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.52, 5,   coast,  -12.26,  52799.00, 5170.70, 3840.90,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.53, 5,   coast,   -9.81,  52806.00, 5169.71, 3839.91,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.54, 5,   coast,   -8.34,  52800.00, 5170.56, 3840.75,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.55, 5,   coast,   -9.81,  52795.00, 5171.26, 3841.46,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.56, 5,   coast,   -9.81,  52795.00, 5171.26, 3841.46,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.57, 5,   coast,  -12.75,  52790.00, 5171.97, 3842.17,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.58, 5,   coast,  -11.28,  52791.00, 5171.83, 3842.02,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.59, 5,   coast,  -11.28,  52788.00, 5172.25, 3842.45,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.60, 5,   coast,  -12.26,  52791.00, 5171.83, 3842.02,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.61, 5,   coast,  -12.26,  52794.00, 5171.40, 3841.60,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.62, 5,   coast,   -9.32,  52785.00, 5172.67, 3842.87,     NaN, 33.9, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.62, 5,   coast,   -9.32,  52785.00, 5172.67, 3842.87,     NaN, 33.9, 4.00, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.63, 5,   coast,  -11.28,  52782.00, 5173.10, 3843.30,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.64, 5,   coast,  -11.28,  52790.00, 5171.97, 3842.17,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.65, 5,   coast,   -9.32,  52778.00, 5173.66, 3843.86,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.66, 5,   coast,   -9.32,  52777.00, 5173.80, 3844.00,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.67, 5,   coast,  -11.28,  52774.00, 5174.23, 3844.42,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.68, 5,   coast,  -12.75,  52770.00, 5174.79, 3844.99,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.69, 5,   coast,  -11.77,  52771.00, 5174.65, 3844.85,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.70, 5,   coast,  -11.77,  52772.00, 5174.51, 3844.71,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.71, 5,   coast,   -8.83,  52763.00, 5175.78, 3845.98,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.72, 5,   coast,  -10.30,  52774.00, 5174.23, 3844.42,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.73, 5,   coast,  -11.77,  52766.00, 5175.35, 3845.55,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.74, 5,   coast,  -10.79,  52753.00, 5177.19, 3847.39,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.75, 5,   coast,  -10.30,  52767.00, 5175.21, 3845.41,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.76, 5,   coast,  -10.30,  52752.00, 5177.33, 3847.53,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.77, 5,   coast,   -9.81,  52759.00, 5176.34, 3846.54,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.78, 5,   coast,   -7.85,  52745.00, 5178.32, 3848.52,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.79, 5,   coast,   -9.81,  52751.00, 5177.47, 3847.67,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.80, 5,   coast,  -10.79,  52746.00, 5178.18, 3848.38,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.81, 5,   coast,   -9.32,  52744.00, 5178.46, 3848.66,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.82, 5,   coast,  -12.75,  52746.00, 5178.18, 3848.38,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.83, 5,   coast,  -10.79,  52730.00, 5180.44, 3850.64,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.84, 5,   coast,  -10.30,  52745.00, 5178.32, 3848.52,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.85, 5,   coast,  -10.79,  52739.00, 5179.17, 3849.37,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.86, 5,   coast,  -11.77,  52728.00, 5180.72, 3850.92,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.87, 5,   coast,  -12.75,  52734.00, 5179.87, 3850.07,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.88, 5,   coast,  -11.28,  52746.00, 5178.18, 3848.38,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.89, 5,   coast,   -9.32,  52712.00, 5182.98, 3853.18,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.90, 5,   coast,  -12.26,  52726.00, 5181.00, 3851.20,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.91, 5,   coast,   -9.32,  52719.00, 5181.99, 3852.19,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.92, 5,   coast,  -12.26,  52722.00, 5181.57, 3851.77,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.93, 5,   coast,   -8.83,  52724.00, 5181.29, 3851.49,     NaN, 33.9, 4.00, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.94, 5,   coast,  -11.28,  52717.00, 5182.28, 3852.47,     NaN, 33.9, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.94, 5,   coast,  -11.28,  52717.00, 5182.28, 3852.47,     NaN, 33.9, 4.00, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.95, 5,   coast,  -11.28,  52719.00, 5181.99, 3852.19,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.96, 5,   coast,  -11.77,  52724.00, 5181.29, 3851.49,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.97, 5,   coast,  -10.30,  52704.00, 5184.11, 3854.31,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.98, 5,   coast,   -9.32,  52709.00, 5183.41, 3853.60,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    25.99, 5,   coast,  -10.79,  52712.00, 5182.98, 3853.18,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.00, 5,   coast,   -8.83,  52720.00, 5181.85, 3852.05,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.01, 5,   coast,   -7.85,  52702.00, 5184.40, 3854.59,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.02, 5,   coast,  -10.30,  52708.00, 5183.55, 3853.75,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.03, 5,   coast,   -6.37,  52695.00, 5185.38, 3855.58,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.04, 5,   coast,  -12.26,  52691.00, 5185.95, 3856.15,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.05, 5,   coast,  -11.28,  52692.00, 5185.81, 3856.01,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.06, 5,   coast,  -10.79,  52687.00, 5186.52, 3856.71,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.07, 5,   coast,  -10.30,  52686.00, 5186.66, 3856.86,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.08, 5,   coast,  -11.28,  52685.00, 5186.80, 3857.00,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.09, 5,   coast,   -8.83,  52693.00, 5185.67, 3855.87,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.10, 5,   coast,  -10.79,  52682.00, 5187.22, 3857.42,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.11, 5,   coast,   -9.32,  52695.00, 5185.38, 3855.58,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.12, 5,   coast,   -9.32,  52681.00, 5187.36, 3857.56,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.13, 5,   coast,  -10.79,  52676.00, 5188.07, 3858.27,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.14, 5,   coast,  -11.28,  52679.00, 5187.65, 3857.85,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.15, 5,   coast,  -10.30,  52684.00, 5186.94, 3857.14,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.16, 5,   coast,  -10.30,  52686.00, 5186.66, 3856.86,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.17, 5,   coast,  -10.79,  52676.00, 5188.07, 3858.27,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.18, 5,   coast,  -10.79,  52666.00, 5189.48, 3859.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.19, 5,   coast,  -10.79,  52661.00, 5190.19, 3860.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.20, 5,   coast,  -10.79,  52667.00, 5189.34, 3859.54,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.21, 5,   coast,  -11.77,  52666.00, 5189.48, 3859.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.22, 5,   coast,  -12.75,  52664.00, 5189.77, 3859.97,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.23, 5,   coast,   -9.81,  52653.00, 5191.32, 3861.52,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.24, 5,   coast,   -9.32,  52651.00, 5191.61, 3861.80,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.25, 5,   coast,  -10.30,  52649.00, 5191.89, 3862.09,     NaN, 33.9, 4.00, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.26, 5,   coast,   -7.85,  52655.00, 5191.04, 3861.24,     NaN, 33.9, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.26, 5,   coast,   -7.85,  52655.00, 5191.04, 3861.24,     NaN, 33.9, 3.99, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.27, 5,   coast,  -12.26,  52651.00, 5191.61, 3861.80,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.28, 5,   coast,  -10.30,  52665.00, 5189.63, 3859.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.29, 5,   coast,  -12.75,  52661.00, 5190.19, 3860.39,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.30, 5,   coast,  -12.75,  52645.00, 5192.45, 3862.65,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9418522,-106.9158721,  5442.0, 2022,  6, 24, 15, 17, 42,      489,     4077, 302,  83,   1.4,   0.8,   1.1,  0, 39, 32,  0,  0, 32,  0,  0,  0,  0, 39, 23, 28, 31,  0,  0, 28,  0, 33, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.31, 5,   coast,  -12.26,  52646.00, 5192.31, 3862.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.31, 5,   coast,  -12.26,  52646.00, 5192.31, 3862.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.31, 5,   coast,  -12.26,  52646.00, 5192.31, 3862.51,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.32, 5,   coast,  -10.79,  52661.00, 5190.19, 3860.39,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.33, 5,   coast,   -9.81,  52645.00, 5192.45, 3862.65,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.34, 5,   coast,   -7.85,  52643.00, 5192.74, 3862.94,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.35, 5,   coast,   -9.81,  52633.00, 5194.15, 3864.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.36, 5,   coast,   -8.34,  52644.00, 5192.60, 3862.79,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.37, 5,   coast,  -11.28,  52635.00, 5193.87, 3864.07,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.38, 5,   coast,   -7.85,  52634.00, 5194.01, 3864.21,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.39, 5,   coast,  -13.73,  52632.00, 5194.29, 3864.49,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.40, 5,   coast,  -10.30,  52632.00, 5194.29, 3864.49,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.41, 5,   coast,  -13.24,  52637.00, 5193.59, 3863.78,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.42, 5,   coast,  -11.77,  52622.00, 5195.71, 3865.91,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.43, 5,   coast,   -6.86,  52616.00, 5196.56, 3866.76,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.44, 5,   coast,   -9.32,  52623.00, 5195.57, 3865.77,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.45, 5,   coast,  -11.77,  52633.00, 5194.15, 3864.35,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.46, 5,   coast,  -10.79,  52618.00, 5196.27, 3866.47,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.47, 5,   coast,   -9.81,  52604.00, 5198.26, 3868.45,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.48, 5,   coast,  -10.79,  52615.00, 5196.70, 3866.90,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.49, 5,   coast,   -9.32,  52604.00, 5198.26, 3868.45,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.50, 5,   coast,   -8.34,  52618.00, 5196.27, 3866.47,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.51, 5,   coast,  -12.26,  52615.00, 5196.70, 3866.90,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.52, 5,   coast,  -11.77,  52612.00, 5197.12, 3867.32,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.53, 5,   coast,  -11.28,  52615.00, 5196.70, 3866.90,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.54, 5,   coast,   -9.32,  52605.00, 5198.11, 3868.31,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.55, 5,   coast,  -13.24,  52604.00, 5198.26, 3868.45,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.56, 5,   coast,   -9.32,  52594.00, 5199.67, 3869.87,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.57, 5,   coast,  -11.77,  52606.00, 5197.97, 3868.17,     NaN, 33.9, 3.99, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.58, 5,   coast,  -10.30,  52601.00, 5198.68, 3868.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.58, 5,   coast,  -10.30,  52601.00, 5198.68, 3868.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.59, 5,   coast,  -10.30,  52596.00, 5199.39, 3869.59,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.60, 5,   coast,   -7.35,  52603.00, 5198.40, 3868.60,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.61, 5,   coast,  -11.28,  52587.00, 5200.66, 3870.86,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.62, 5,   coast,  -10.30,  52594.00, 5199.67, 3869.87,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.63, 5,   coast,  -10.30,  52593.00, 5199.81, 3870.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.64, 5,   coast,  -10.79,  52599.00, 5198.96, 3869.16,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.65, 5,   coast,   -8.34,  52587.00, 5200.66, 3870.86,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.66, 5,   coast,  -10.30,  52595.00, 5199.53, 3869.73,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.67, 5,   coast,  -10.79,  52595.00, 5199.53, 3869.73,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.68, 5,   coast,  -10.79,  52593.00, 5199.81, 3870.01,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.69, 5,   coast,   -9.32,  52583.00, 5201.23, 3871.43,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.70, 5,   coast,  -10.79,  52580.00, 5201.65, 3871.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.71, 5,   coast,   -7.85,  52580.00, 5201.65, 3871.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.72, 5,   coast,  -10.30,  52574.00, 5202.50, 3872.70,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.73, 5,   coast,  -10.79,  52581.00, 5201.51, 3871.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.74, 5,   coast,  -10.79,  52573.00, 5202.64, 3872.84,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.75, 5,   coast,  -10.30,  52581.00, 5201.51, 3871.71,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.76, 5,   coast,  -10.79,  52580.00, 5201.65, 3871.85,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.77, 5,   coast,   -9.81,  52573.00, 5202.64, 3872.84,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.78, 5,   coast,   -9.81,  52566.00, 5203.64, 3873.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.79, 5,   coast,  -10.30,  52577.00, 5202.08, 3872.28,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.80, 5,   coast,   -9.32,  52567.00, 5203.49, 3873.69,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.81, 5,   coast,  -12.26,  52558.00, 5204.77, 3874.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.82, 5,   coast,  -10.79,  52567.00, 5203.49, 3873.69,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.83, 5,   coast,   -9.81,  52566.00, 5203.64, 3873.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.84, 5,   coast,  -11.28,  52566.00, 5203.64, 3873.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.85, 5,   coast,  -10.79,  52558.00, 5204.77, 3874.97,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.86, 5,   coast,  -12.26,  52568.00, 5203.35, 3873.55,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.87, 5,   coast,  -10.30,  52559.00, 5204.63, 3874.83,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.88, 5,   coast,  -10.30,  52544.00, 5206.75, 3876.95,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.89, 5,   coast,  -12.26,  52552.00, 5205.62, 3875.82,     NaN, 33.9, 4.00, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.90, 5,   coast,  -10.79,  52542.00, 5207.03, 3877.23,     NaN, 33.9, 3.99, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.90, 5,   coast,  -10.79,  52542.00, 5207.03, 3877.23,     NaN, 33.9, 3.99, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.91, 5,   coast,   -8.83,  52546.00, 5206.47, 3876.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.92, 5,   coast,  -12.26,  52540.00, 5207.32, 3877.52,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.93, 5,   coast,  -12.26,  52556.00, 5205.05, 3875.25,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.94, 5,   coast,   -8.83,  52546.00, 5206.47, 3876.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.95, 5,   coast,   -9.81,  52537.00, 5207.74, 3877.94,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.96, 5,   coast,  -11.28,  52548.00, 5206.18, 3876.38,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.97, 5,   coast,  -11.28,  52541.00, 5207.18, 3877.38,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.98, 5,   coast,  -10.79,  52546.00, 5206.47, 3876.67,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    26.99, 5,   coast,  -11.28,  52540.00, 5207.32, 3877.52,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.00, 5,   coast,  -11.77,  52540.00, 5207.32, 3877.52,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.01, 5,   coast,  -10.30,  52548.00, 5206.18, 3876.38,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.02, 5,   coast,  -11.28,  52538.00, 5207.60, 3877.80,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.03, 5,   coast,  -11.28,  52535.00, 5208.03, 3878.23,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.04, 5,   coast,   -9.32,  52538.00, 5207.60, 3877.80,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.05, 5,   coast,   -8.83,  52523.00, 5209.73, 3879.93,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.06, 5,   coast,  -10.30,  52531.00, 5208.59, 3878.79,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.07, 5,   coast,  -13.73,  52531.00, 5208.59, 3878.79,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.08, 5,   coast,  -11.77,  52528.00, 5209.02, 3879.22,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.09, 5,   coast,   -8.83,  52534.00, 5208.17, 3878.37,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.10, 5,   coast,   -8.83,  52523.00, 5209.73, 3879.93,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.11, 5,   coast,   -9.81,  52522.00, 5209.87, 3880.07,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.12, 5,   coast,  -11.28,  52517.00, 5210.58, 3880.78,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.13, 5,   coast,   -9.32,  52526.00, 5209.30, 3879.50,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.14, 5,   coast,   -9.32,  52529.00, 5208.88, 3879.08,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.15, 5,   coast,   -8.83,  52531.00, 5208.59, 3878.79,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.16, 5,   coast,  -10.30,  52515.00, 5210.86, 3881.06,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.17, 5,   coast,  -10.30,  52520.00, 5210.15, 3880.35,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.18, 5,   coast,   -8.34,  52516.00, 5210.72, 3880.92,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.19, 5,   coast,  -12.26,  52515.00, 5210.86, 3881.06,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.20, 5,   coast,  -10.30,  52515.00, 5210.86, 3881.06,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.21, 5,   coast,  -10.30,  52505.00, 5212.28, 3882.48,     NaN, 33.9, 3.99, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.22, 5,   coast,   -9.81,  52517.00, 5210.58, 3880.78,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.22, 5,   coast,   -9.81,  52517.00, 5210.58, 3880.78,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  64.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.23, 5,   coast,  -11.77,  52522.00, 5209.87, 3880.07,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.24, 5,   coast,   -7.35,  52501.00, 5212.85, 3883.04,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.25, 5,   coast,   -8.83,  52513.00, 5211.14, 3881.34,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.26, 5,   coast,   -9.32,  52510.00, 5211.57, 3881.77,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.27, 5,   coast,  -10.79,  52505.00, 5212.28, 3882.48,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.28, 5,   coast,   -7.35,  52515.00, 5210.86, 3881.06,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.29, 5,   coast,  -12.75,  52504.00, 5212.42, 3882.62,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.30, 5,   coast,  -10.30,  52497.00, 5213.41, 3883.61,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9419529,-106.9160455,  5478.0, 2022,  6, 24, 15, 17, 43,      509,     4116, 302,  83,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 33,  0,  0,  0,  0, 35, 23, 33, 36,  0,  0, 24,  0, 34, 33,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.31, 5,   coast,  -11.28,  52506.00, 5212.14, 3882.34,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.31, 5,   coast,  -11.28,  52506.00, 5212.14, 3882.34,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.31, 5,   coast,  -11.28,  52506.00, 5212.14, 3882.34,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.32, 5,   coast,  -11.28,  52508.00, 5211.85, 3882.05,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.33, 5,   coast,  -10.30,  52512.00, 5211.29, 3881.49,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.34, 5,   coast,   -7.85,  52502.00, 5212.70, 3882.90,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.35, 5,   coast,  -11.77,  52497.00, 5213.41, 3883.61,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.36, 5,   coast,  -11.77,  52500.00, 5212.99, 3883.19,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.37, 5,   coast,  -11.77,  52486.00, 5214.97, 3885.17,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.38, 5,   coast,   -9.32,  52498.00, 5213.27, 3883.47,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.39, 5,   coast,  -11.77,  52497.00, 5213.41, 3883.61,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.40, 5,   coast,  -10.30,  52495.00, 5213.70, 3883.90,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.41, 5,   coast,   -7.85,  52483.00, 5215.40, 3885.60,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.42, 5,   coast,   -9.81,  52487.00, 5214.83, 3885.03,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.43, 5,   coast,  -11.77,  52489.00, 5214.55, 3884.75,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.44, 5,   coast,   -9.81,  52485.00, 5215.11, 3885.31,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.45, 5,   coast,  -10.30,  52495.00, 5213.70, 3883.90,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.46, 5,   coast,   -7.35,  52489.00, 5214.55, 3884.75,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.47, 5,   coast,   -9.32,  52489.00, 5214.55, 3884.75,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.48, 5,   coast,   -9.32,  52479.00, 5215.96, 3886.16,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.49, 5,   coast,  -10.30,  52488.00, 5214.69, 3884.89,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.50, 5,   coast,  -10.30,  52483.00, 5215.40, 3885.60,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.51, 5,   coast,   -8.34,  52483.00, 5215.40, 3885.60,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.52, 5,   coast,   -7.85,  52484.00, 5215.26, 3885.45,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.53, 5,   coast,  -10.79,  52481.00, 5215.68, 3885.88,     NaN, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.54, 5,   coast,  -11.28,  52471.00, 5217.10, 3887.30,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.54, 5,   coast,  -11.28,  52471.00, 5217.10, 3887.30,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  64.09,  64.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.55, 5,   coast,   -8.34,  52481.00, 5215.68, 3885.88,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.56, 5,   coast,   -9.32,  52484.00, 5215.26, 3885.45,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.57, 5,   coast,   -8.83,  52477.00, 5216.25, 3886.45,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.58, 5,   coast,   -8.83,  52478.00, 5216.11, 3886.31,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.59, 5,   coast,   -8.34,  52476.00, 5216.39, 3886.59,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.60, 5,   coast,  -10.30,  52469.00, 5217.38, 3887.58,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.61, 5,   coast,  -11.28,  52483.00, 5215.40, 3885.60,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.62, 5,   coast,   -8.83,  52483.00, 5215.40, 3885.60,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.63, 5,   coast,  -11.77,  52473.00, 5216.82, 3887.01,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.64, 5,   coast,   -9.81,  52477.00, 5216.25, 3886.45,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.65, 5,   coast,  -10.30,  52480.00, 5215.82, 3886.02,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.66, 5,   coast,  -11.28,  52479.00, 5215.96, 3886.16,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.67, 5,   coast,  -10.79,  52465.00, 5217.95, 3888.15,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.68, 5,   coast,  -10.79,  52457.00, 5219.09, 3889.28,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.69, 5,   coast,  -10.30,  52476.00, 5216.39, 3886.59,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.70, 5,   coast,  -11.77,  52467.00, 5217.67, 3887.87,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.71, 5,   coast,  -13.73,  52462.00, 5218.38, 3888.57,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.72, 5,   coast,   -9.32,  52459.00, 5218.80, 3889.00,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.73, 5,   coast,   -9.32,  52463.00, 5218.23, 3888.43,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.74, 5,   coast,   -8.83,  52460.00, 5218.66, 3888.86,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.75, 5,   coast,  -11.77,  52464.00, 5218.09, 3888.29,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.76, 5,   coast,   -8.34,  52451.00, 5219.94, 3890.14,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.77, 5,   coast,   -8.34,  52450.00, 5220.08, 3890.28,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.78, 5,   coast,   -8.34,  52450.00, 5220.08, 3890.28,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.79, 5,   coast,   -9.81,  52453.00, 5219.65, 3889.85,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.80, 5,   coast,  -11.28,  52461.00, 5218.52, 3888.72,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.81, 5,   coast,  -11.28,  52449.00, 5220.22, 3890.42,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.82, 5,   coast,  -10.30,  52453.00, 5219.65, 3889.85,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.83, 5,   coast,  -11.28,  52454.00, 5219.51, 3889.71,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.84, 5,   coast,  -11.77,  52463.00, 5218.23, 3888.43,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.85, 5,   coast,  -10.79,  52462.00, 5218.38, 3888.57,     NaN, 33.9, 3.98, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.86, 5,   coast,  -10.30,  52447.00, 5220.50, 3890.70,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.86, 5,   coast,  -10.30,  52447.00, 5220.50, 3890.70,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  63.97,  64.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.87, 5,   coast,  -12.26,  52455.00, 5219.37, 3889.57,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.88, 5,   coast,   -9.81,  52452.00, 5219.79, 3889.99,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.89, 5,   coast,   -9.81,  52450.00, 5220.08, 3890.28,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.90, 5,   coast,   -9.32,  52449.00, 5220.22, 3890.42,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.91, 5,   coast,  -11.28,  52451.00, 5219.94, 3890.14,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.92, 5,   coast,   -8.83,  52456.00, 5219.23, 3889.43,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.93, 5,   coast,   -8.83,  52450.00, 5220.08, 3890.28,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.94, 5,   coast,   -8.34,  52442.00, 5221.21, 3891.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.95, 5,   coast,  -10.79,  52433.00, 5222.49, 3892.69,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.96, 5,   coast,   -9.81,  52452.00, 5219.79, 3889.99,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.97, 5,   coast,  -11.28,  52441.00, 5221.36, 3891.55,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.98, 5,   coast,   -9.81,  52452.00, 5219.79, 3889.99,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    27.99, 5,   coast,   -9.32,  52450.00, 5220.08, 3890.28,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.00, 5,   coast,   -8.83,  52454.00, 5219.51, 3889.71,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.01, 5,   coast,   -9.32,  52450.00, 5220.08, 3890.28,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.02, 5,   coast,   -9.81,  52448.00, 5220.36, 3890.56,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.03, 5,   coast,   -8.83,  52442.00, 5221.21, 3891.41,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.04, 5,   coast,  -10.79,  52439.00, 5221.64, 3891.84,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.05, 5,   coast,  -10.79,  52440.00, 5221.50, 3891.70,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.06, 5,   coast,  -10.30,  52438.00, 5221.78, 3891.98,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.07, 5,   coast,  -11.28,  52443.00, 5221.07, 3891.27,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.08, 5,   coast,  -11.77,  52444.00, 5220.93, 3891.13,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.09, 5,   coast,  -10.79,  52436.00, 5222.06, 3892.26,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.10, 5,   coast,  -11.28,  52428.00, 5223.20, 3893.40,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.11, 5,   coast,  -12.75,  52439.00, 5221.64, 3891.84,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.12, 5,   coast,   -9.81,  52425.00, 5223.63, 3893.82,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.13, 5,   coast,  -10.79,  52437.00, 5221.92, 3892.12,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.14, 5,   coast,   -9.81,  52438.00, 5221.78, 3891.98,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.15, 5,   coast,  -10.30,  52429.00, 5223.06, 3893.26,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.16, 5,   coast,   -9.81,  52416.00, 5224.90, 3895.10,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.17, 5,   coast,  -12.75,  52423.00, 5223.91, 3894.11,     NaN, 33.9, 3.99, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.18, 5,   coast,  -11.28,  52432.00, 5222.63, 3892.83,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.18, 5,   coast,  -11.28,  52432.00, 5222.63, 3892.83,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.09,  64.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.19, 5,   coast,   -9.32,  52423.00, 5223.91, 3894.11,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.20, 5,   coast,   -8.34,  52423.00, 5223.91, 3894.11,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.21, 5,   coast,  -10.30,  52438.00, 5221.78, 3891.98,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.22, 5,   coast,  -10.30,  52417.00, 5224.76, 3894.96,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.23, 5,   coast,   -8.34,  52429.00, 5223.06, 3893.26,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.24, 5,   coast,   -8.83,  52431.00, 5222.77, 3892.97,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.25, 5,   coast,   -9.32,  52415.00, 5225.05, 3895.24,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.26, 5,   coast,  -10.79,  52423.00, 5223.91, 3894.11,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.27, 5,   coast,   -9.81,  52427.00, 5223.34, 3893.54,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.28, 5,   coast,  -12.26,  52423.00, 5223.91, 3894.11,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.29, 5,   coast,   -9.81,  52433.00, 5222.49, 3892.69,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.30, 5,   coast,   -9.32,  52427.00, 5223.34, 3893.54,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9420543,-106.9162164,  5503.0, 2022,  6, 24, 15, 17, 44,      529,     4143, 302,  83,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 34, 22, 34, 35,  0,  0, 23,  0, 33, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.31, 5,   coast,   -8.83,  52421.00, 5224.19, 3894.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.31, 5,   coast,   -8.83,  52421.00, 5224.19, 3894.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.31, 5,   coast,   -8.83,  52421.00, 5224.19, 3894.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.32, 5,   coast,   -9.81,  52430.00, 5222.92, 3893.12,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.33, 5,   coast,   -9.81,  52425.00, 5223.63, 3893.82,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.34, 5,   coast,  -10.79,  52426.00, 5223.48, 3893.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.35, 5,   coast,   -9.32,  52421.00, 5224.19, 3894.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.36, 5,   coast,   -8.34,  52413.00, 5225.33, 3895.53,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.37, 5,   coast,  -11.77,  52408.00, 5226.04, 3896.24,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.38, 5,   coast,  -10.30,  52415.00, 5225.05, 3895.24,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.39, 5,   coast,  -10.79,  52422.00, 5224.05, 3894.25,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.40, 5,   coast,  -10.30,  52419.00, 5224.48, 3894.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.41, 5,   coast,  -10.30,  52424.00, 5223.77, 3893.97,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.42, 5,   coast,  -11.28,  52424.00, 5223.77, 3893.97,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.43, 5,   coast,  -11.28,  52418.00, 5224.62, 3894.82,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.44, 5,   coast,   -9.32,  52414.00, 5225.19, 3895.39,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.45, 5,   coast,   -8.83,  52412.00, 5225.47, 3895.67,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.46, 5,   coast,   -8.83,  52417.00, 5224.76, 3894.96,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.47, 5,   coast,   -9.81,  52419.00, 5224.48, 3894.68,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.48, 5,   coast,  -10.30,  52427.00, 5223.34, 3893.54,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.49, 5,   coast,  -12.26,  52423.00, 5223.91, 3894.11,     NaN, 33.9, 4.00, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.50, 6,  drogue,  -12.75,  52419.00, 5224.48, 3894.68,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.50, 6,  drogue,  -12.75,  52419.00, 5224.48, 3894.68,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.50, 6,  drogue,  -12.75,  52419.00, 5224.48, 3894.68,     NaN, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  64.27,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.51, 6,  drogue,  -10.79,  52407.00, 5226.18, 3896.38,    4.77, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.61, 6,  drogue,   -7.35,  52416.00, 5224.90, 3895.10,    3.96, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.71, 6,  drogue,  -12.26,  52398.00, 5227.46, 3897.66,    3.18, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.81, 6,  drogue,  -11.28,  52393.00, 5228.17, 3898.37,    2.41, 33.9, 3.98, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.82, 6,  drogue,  -11.28,  52393.00, 5228.17, 3898.37,    2.41, 33.9, 4.00, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  64.09,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    28.91, 6,  drogue,   -9.81,  52418.00, 5224.62, 3894.82,    1.66, 33.9, 4.00, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    29.01, 6,  drogue,  -12.26,  52419.00, 5224.48, 3894.68,    0.90, 33.9, 4.00, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    29.11, 6,  drogue,   -9.81,  52409.00, 5225.90, 3896.10,    0.16, 33.9, 4.00, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    29.14, 6,  drogue,   -9.81,  52409.00, 5225.90, 3896.10,    0.16, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  63.97,  64.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    29.21, 6,  drogue,  -10.30,  52414.00, 5225.19, 3895.39,   -0.57, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9421547,-106.9163845,  5519.0, 2022,  6, 24, 15, 17, 45,      548,     4161, 302,  82,   1.4,   0.8,   1.1,  0, 27, 33,  0,  0, 34,  0,  0,  0,  0, 28, 31, 35, 36,  0,  0, 27,  0, 32, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    29.31, 6,  drogue,   -9.81,  52405.00, 5226.46, 3896.66,   -1.30, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.31, 6,  drogue,   -9.81,  52405.00, 5226.46, 3896.66,   -1.30, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.31, 6,  drogue,   -9.81,  52405.00, 5226.46, 3896.66,   -1.30, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.41, 6,  drogue,  -11.28,  52402.00, 5226.89, 3897.09,   -2.02, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.46, 6,  drogue,  -11.28,  52402.00, 5226.89, 3897.09,   -2.02, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.51, 6,  drogue,   -8.83,  52424.00, 5223.77, 3893.97,   -2.74, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.61, 6,  drogue,   -8.83,  52419.00, 5224.48, 3894.68,   -3.50, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.71, 6,  drogue,  -12.26,  52420.00, 5224.34, 3894.53,   -4.28, 33.9, 4.00, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.78, 6,  drogue,  -12.26,  52420.00, 5224.34, 3894.53,   -4.28, 33.9, 2.18, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  64.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.81, 6,  drogue,  -12.26,  52424.00, 5223.77, 3893.97,   -5.03, 33.9, 2.18, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  35.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    29.91, 6,  drogue,  -11.28,  52414.00, 5225.19, 3895.39,   -5.79, 33.9, 2.18, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  35.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.01, 6,  drogue,   -8.83,  52424.00, 5223.77, 3893.97,   -6.56, 33.9, 2.18, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  35.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.10, 6,  drogue,   -8.83,  52424.00, 5223.77, 3893.97,   -6.56, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  35.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.11, 6,  drogue,  -11.77,  52414.00, 5225.19, 3895.39,   -7.35, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.21, 6,  drogue,  -13.24,  52417.00, 5224.76, 3894.96,   -8.15, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9422600,-106.9165553,  5524.0, 2022,  6, 24, 15, 17, 46,      568,     4169, 303,  82,   1.4,   0.8,   1.1,  0, 26, 31,  0,  0, 34,  0,  0,  0,  0, 28, 38, 30, 36,  0,  0, 33,  0, 25, 32,  0,  0,  0, 36,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.31, 6,  drogue,  -14.22,  52424.00, 5223.77, 3893.97,   -8.94, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.31, 6,  drogue,  -14.22,  52424.00, 5223.77, 3893.97,   -8.94, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.31, 6,  drogue,  -14.22,  52424.00, 5223.77, 3893.97,   -8.94, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.41, 6,  drogue,  -19.61,  52437.00, 5221.92, 3892.12,   -9.73, 33.9, 2.03, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.42, 6,  drogue,  -19.61,  52437.00, 5221.92, 3892.12,   -9.73, 33.9, 1.94, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  32.65,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.51, 6,  drogue,  -51.98,  52472.00, 5216.96, 3887.16,  -10.50, 33.9, 1.94, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  31.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.61, 6,  drogue,  -10.30,  52474.00, 5216.67, 3886.87,  -11.27, 33.9, 1.94, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  31.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.71, 6,  drogue,  -11.77,  52455.00, 5219.37, 3889.57,  -11.94, 33.9, 1.94, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  31.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.74, 6,  drogue,  -11.77,  52455.00, 5219.37, 3889.57,  -11.94, 33.9, 1.89, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  31.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.81, 6,  drogue,  -13.73,  52473.00, 5216.82, 3887.01,  -12.54, 33.9, 1.89, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  30.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    30.91, 6,  drogue,  -14.22,  52478.00, 5216.11, 3886.31,  -13.13, 33.9, 1.89, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  30.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    31.01, 6,  drogue,  -13.24,  52502.00, 5212.70, 3882.90,  -13.63, 33.9, 1.89, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  30.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    31.06, 6,  drogue,  -13.24,  52502.00, 5212.70, 3882.90,  -13.63, 33.9, 1.85, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  30.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    31.11, 6,  drogue,  -10.79,  52511.00, 5211.43, 3881.63,  -14.05, 33.9, 1.85, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  29.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    31.21, 6,  drogue,  -12.26,  52513.00, 5211.14, 3881.34,  -14.47, 33.9, 1.85, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  29.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9423657,-106.9167329,  5520.0, 2022,  6, 24, 15, 17, 47,      588,     4168, 303,  82,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 37,  0,  0,  0,  0, 36, 38, 30, 38,  0,  0, 33,  0, 25, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    31.31, 6,  drogue,  -12.75,  52520.00, 5210.15, 3880.35,  -14.83, 33.9, 1.85, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  29.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.31, 6,  drogue,  -12.75,  52520.00, 5210.15, 3880.35,  -14.83, 33.9, 1.85, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  29.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.31, 6,  drogue,  -12.75,  52520.00, 5210.15, 3880.35,  -14.83, 33.9, 1.85, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  29.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.38, 6,  drogue,  -12.75,  52520.00, 5210.15, 3880.35,  -14.83, 33.9, 1.83, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  29.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.41, 6,  drogue,  -14.22,  52534.00, 5208.17, 3878.37,  -15.11, 33.9, 1.83, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  29.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.51, 6,  drogue,  -17.16,  52549.00, 5206.04, 3876.24,  -15.30, 33.9, 1.83, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  29.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.61, 6,  drogue,  -13.73,  52593.00, 5199.81, 3870.01,  -15.55, 33.9, 1.83, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  29.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.70, 6,  drogue,  -13.73,  52593.00, 5199.81, 3870.01,  -15.55, 33.9, 1.81, 3.97, 3.98,   0.00,   0.00,   0.00,  64.09,  29.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.71, 6,  drogue,  -14.71,  52607.00, 5197.83, 3868.03,  -15.76, 33.9, 1.81, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  29.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.81, 6,  drogue,  -16.18,  52582.00, 5201.37, 3871.57,  -15.91, 33.9, 1.81, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  29.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    31.91, 6,  drogue,  -16.67,  52590.00, 5200.24, 3870.44,  -16.08, 33.9, 1.81, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  29.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    32.01, 6,  drogue,  -14.71,  52616.00, 5196.56, 3866.76,  -16.30, 33.9, 1.81, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  29.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    32.02, 6,  drogue,  -14.71,  52616.00, 5196.56, 3866.76,  -16.30, 33.9, 1.80, 3.98, 3.99,   0.00,   0.00,   0.00,  63.97,  29.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    32.11, 6,  drogue,  -13.24,  52640.00, 5193.16, 3863.36,  -16.58, 33.9, 1.80, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  28.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    32.21, 6,  drogue,  -16.67,  52658.00, 5190.62, 3860.81,  -16.93, 33.9, 1.80, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  28.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9424671,-106.9168927,  5508.0, 2022,  6, 24, 15, 17, 48,      606,     4158, 303,  82,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 35,  0,  0,  0,  0, 29, 29, 29, 33,  0,  0, 37,  0, 30, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    32.31, 6,  drogue,  -14.71,  52658.00, 5190.62, 3860.81,  -17.36, 33.9, 1.80, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  28.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.31, 6,  drogue,  -14.71,  52658.00, 5190.62, 3860.81,  -17.36, 33.9, 1.80, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  28.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.31, 6,  drogue,  -14.71,  52658.00, 5190.62, 3860.81,  -17.36, 33.9, 1.80, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  28.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.34, 6,  drogue,  -14.71,  52658.00, 5190.62, 3860.81,  -17.36, 33.9, 1.79, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  28.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.41, 6,  drogue,  -11.77,  52676.00, 5188.07, 3858.27,  -17.85, 33.9, 1.79, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.51, 6,  drogue,   -8.83,  52674.00, 5188.35, 3858.55,  -18.45, 33.9, 1.79, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.61, 6,  drogue,  -11.77,  52702.00, 5184.40, 3854.59,  -19.12, 33.9, 1.79, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.66, 6,  drogue,  -11.77,  52702.00, 5184.40, 3854.59,  -19.12, 33.9, 1.77, 3.96, 3.98,   0.08,   0.00,   0.00,  64.09,  28.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.71, 6,  drogue,   -9.32,  52652.00, 5191.46, 3861.66,  -19.88, 33.9, 1.77, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  28.50,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.81, 6,  drogue,   -9.32,  52653.00, 5191.32, 3861.52,  -20.78, 33.9, 1.77, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  28.50,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.91, 6,  drogue,   -5.39,  52700.00, 5184.68, 3854.88,  -21.75, 33.9, 1.77, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  28.50,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    32.98, 6,  drogue,   -5.39,  52700.00, 5184.68, 3854.88,  -21.75, 33.9, 1.78, 3.98, 3.98,   0.00,   0.00,   0.00,  63.84,  28.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    33.01, 6,  drogue,   -1.96,  52685.00, 5186.80, 3857.00,  -22.78, 33.9, 1.78, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  28.63,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    33.11, 6,  drogue,    0.49,  52721.00, 5181.71, 3851.91,  -23.79, 33.9, 1.78, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  28.63,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    33.21, 6,  drogue,   -2.94,  52792.00, 5171.68, 3841.88,  -24.76, 33.9, 1.78, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  28.63,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    33.30, 6,  drogue,   -2.94,  52792.00, 5171.68, 3841.88,  -24.76, 33.9, 1.77, 3.99, 3.98,   0.02,   0.00,   0.00,  64.03,  28.63,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9425473,-106.9170015,  5491.0, 2022,  6, 24, 15, 17, 49,      620,     4144, 303,  81,   1.4,   0.8,   1.1,  0, 35, 23,  0,  0, 39,  0,  0,  0,  0, 36, 24, 30, 33,  0,  0, 37,  0, 37, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    33.31, 6,  drogue,    0.49,  52810.00, 5169.14, 3839.34,  -25.73, 33.9, 1.77, 3.99, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.31, 6,  drogue,    0.49,  52810.00, 5169.14, 3839.34,  -25.73, 33.9, 1.77, 3.99, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.31, 6,  drogue,    0.49,  52810.00, 5169.14, 3839.34,  -25.73, 33.9, 1.77, 3.99, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.41, 6,  drogue,   10.79,  52775.00, 5174.08, 3844.28,  -26.65, 33.9, 1.77, 3.99, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.51, 6,  drogue,   16.18,  52750.00, 5177.61, 3847.81,  -27.49, 33.9, 1.77, 3.99, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.61, 6,  drogue,   20.59,  52882.00, 5158.99, 3829.19,  -28.25, 33.9, 1.77, 3.99, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.62, 6,  drogue,   20.59,  52882.00, 5158.99, 3829.19,  -28.25, 33.9, 1.76, 3.96, 3.98,   0.08,   0.00,   0.00,  64.27,  28.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.71, 6,  drogue,    2.45,  52863.00, 5161.67, 3831.87,  -28.96, 33.9, 1.76, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  28.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.81, 6,  drogue,   -9.32,  52831.00, 5166.18, 3836.38,  -29.59, 33.9, 1.76, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  28.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.91, 6,  drogue,  -12.75,  52882.00, 5158.99, 3829.19,  -30.08, 33.9, 1.76, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  28.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    33.94, 6,  drogue,  -12.75,  52882.00, 5158.99, 3829.19,  -30.08, 33.9, 1.74, 3.97, 3.97,   0.00,   0.00,   0.00,  63.84,  28.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    34.01, 6,  drogue,   -9.32,  52937.00, 5151.24, 3821.44,  -30.46, 33.9, 1.74, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  28.08,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    34.11, 6,  drogue,   -0.49,  52974.00, 5146.03, 3816.23,  -30.72, 33.9, 1.74, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  28.08,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    34.21, 6,  drogue,   -0.98,  52994.00, 5143.22, 3813.42,  -30.85, 33.9, 1.74, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  28.08,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    34.26, 6,  drogue,   -0.98,  52994.00, 5143.22, 3813.42,  -30.85, 33.9, 1.75, 3.98, 3.98,   0.00,   0.00,   0.00,  63.91,  28.08,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426253,-106.9170810,  5466.0, 2022,  6, 24, 15, 17, 50,      631,     4121, 303,  81,   1.4,   0.8,   1.1,  0, 35, 35,  0,  0, 35,  0,  0,  0,  0, 33, 26, 31, 35,  0,  0, 40,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    34.31, 6,  drogue,    2.94,  53013.00, 5140.55, 3810.75,  -30.84, 33.9, 1.75, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.14,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.31, 6,  drogue,    2.94,  53013.00, 5140.55, 3810.75,  -30.84, 33.9, 1.75, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.14,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.31, 6,  drogue,    2.94,  53013.00, 5140.55, 3810.75,  -30.84, 33.9, 1.75, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.14,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.41, 6,  drogue,   -6.86,  53014.00, 5140.41, 3810.61,  -30.74, 33.9, 1.75, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.14,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.51, 6,  drogue,  -11.28,  53046.00, 5135.91, 3806.11,  -30.56, 33.9, 1.75, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  28.14,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.58, 6,  drogue,  -11.28,  53046.00, 5135.91, 3806.11,  -30.56, 33.9, 1.74, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  28.14,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.61, 6,  drogue,  -17.16,  53067.00, 5132.96, 3803.15,  -30.37, 33.9, 1.74, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.71, 6,  drogue,  -14.22,  53129.00, 5124.25, 3794.45,  -30.14, 33.9, 1.74, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.81, 6,  drogue,  -12.26,  53187.00, 5116.11, 3786.31,  -29.91, 33.9, 1.74, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.90, 6,  drogue,  -12.26,  53187.00, 5116.11, 3786.31,  -29.91, 33.9, 1.74, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    34.91, 6,  drogue,  -13.24,  53196.00, 5114.84, 3785.04,  -29.70, 33.9, 1.74, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    35.01, 6,  drogue,  -15.20,  53183.00, 5116.67, 3786.87,  -29.45, 33.9, 1.74, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    35.11, 6,  drogue,  -14.22,  53139.00, 5122.84, 3793.04,  -29.25, 33.9, 1.74, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    35.21, 6,  drogue,   -6.37,  53134.00, 5123.54, 3793.74,  -29.06, 33.9, 1.74, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    35.22, 6,  drogue,   -6.37,  53134.00, 5123.54, 3793.74,  -29.06, 33.9, 1.73, 3.99, 3.99,   0.09,   0.00,   0.00,  64.09,  28.02,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9426961,-106.9171514,  5437.0, 2022,  6, 24, 15, 17, 51,      641,     4093, 304,  81,   1.4,   0.8,   1.1,  0, 39, 25,  0,  0, 37,  0,  0,  0,  0, 39, 31, 32, 32,  0,  0, 31,  0, 34, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    35.31, 6,  drogue,   -6.86,  53182.00, 5116.81, 3787.01,  -28.90, 33.9, 1.73, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  27.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.31, 6,  drogue,   -6.86,  53182.00, 5116.81, 3787.01,  -28.90, 33.9, 1.73, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  27.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.31, 6,  drogue,   -6.86,  53182.00, 5116.81, 3787.01,  -28.90, 33.9, 1.73, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  27.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.41, 6,  drogue,   -6.37,  53206.00, 5113.44, 3783.64,  -28.69, 33.9, 1.73, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  27.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.51, 6,  drogue,  -13.24,  53212.00, 5112.60, 3782.80,  -28.46, 33.9, 1.73, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  27.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.54, 6,  drogue,  -13.24,  53212.00, 5112.60, 3782.80,  -28.46, 33.9, 1.72, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  27.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.61, 6,  drogue,  -15.20,  53247.00, 5107.69, 3777.89,  -28.30, 33.9, 1.72, 3.99, 3.99,   0.00,   0.00,   0.04,  64.21,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.71, 6,  drogue,  -14.22,  53328.00, 5096.35, 3766.55,  -28.09, 33.9, 1.72, 3.99, 3.99,   0.00,   0.00,   0.04,  64.21,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.81, 6,  drogue,  -11.77,  53400.00, 5086.27, 3756.47,  -27.82, 33.9, 1.72, 3.99, 3.99,   0.00,   0.00,   0.04,  64.21,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.86, 6,  drogue,  -11.77,  53400.00, 5086.27, 3756.47,  -27.82, 33.9, 1.72, 3.98, 3.99,   0.00,   0.00,   0.04,  64.21,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    35.91, 6,  drogue,   -3.92,  53365.00, 5091.17, 3761.37,  -27.55, 33.9, 1.72, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.01, 6,  drogue,   -4.90,  53366.00, 5091.03, 3761.23,  -27.26, 33.9, 1.72, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.11, 6,  drogue,  -12.26,  53368.00, 5090.75, 3760.95,  -26.98, 33.9, 1.72, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.18, 6,  drogue,  -12.26,  53368.00, 5090.75, 3760.95,  -26.98, 33.9, 1.71, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  27.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.21, 6,  drogue,  -11.77,  53366.00, 5091.03, 3761.23,  -26.73, 33.9, 1.71, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.31, 6,  drogue,   -9.32,  53370.00, 5090.47, 3760.67,  -26.48, 33.9, 1.71, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.31, 6,  drogue,   -9.32,  53370.00, 5090.47, 3760.67,  -26.48, 33.9, 1.71, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.31, 6,  drogue,   -9.32,  53370.00, 5090.47, 3760.67,  -26.48, 33.9, 1.71, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9427484,-106.9172066,  5408.0, 2022,  6, 24, 15, 17, 52,      648,     4066, 304,  81,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 34,  0,  0,  0,  0, 32, 30, 30, 35,  0,  0, 35,  0, 31, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    36.41, 6,  drogue,  -15.20,  53416.00, 5084.04, 3754.24,  -26.26, 33.9, 1.71, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.50, 6,  drogue,  -15.20,  53416.00, 5084.04, 3754.24,  -26.26, 33.9, 1.71, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.51, 6,  drogue,  -20.10,  53442.00, 5080.40, 3750.60,  -26.06, 33.9, 1.71, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.61, 6,  drogue,  -20.59,  53510.00, 5070.91, 3741.11,  -25.96, 33.9, 1.71, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.71, 6,  drogue,  -18.14,  53569.00, 5062.67, 3732.87,  -25.92, 33.9, 1.71, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.81, 6,  drogue,  -19.12,  53565.00, 5063.23, 3733.43,  -25.98, 33.9, 1.71, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.82, 6,  drogue,  -19.12,  53565.00, 5063.23, 3733.43,  -25.98, 33.9, 1.72, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.59,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    36.91, 6,  drogue,  -20.10,  53564.00, 5063.37, 3733.57,  -26.11, 33.9, 1.72, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    37.01, 6,  drogue,  -11.77,  53535.00, 5067.42, 3737.62,  -26.32, 33.9, 1.72, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    37.11, 6,  drogue,  -21.08,  53567.00, 5062.95, 3733.15,  -26.62, 33.9, 1.72, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.65,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    37.14, 6,  drogue,  -21.08,  53567.00, 5062.95, 3733.15,  -26.62, 33.9, 1.70, 3.96, 3.98,   0.03,   0.00,   0.00,  64.03,  27.65,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    37.21, 6,  drogue,  -16.67,  53549.00, 5065.46, 3735.66,  -26.98, 33.9, 1.70, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428010,-106.9172271,  5379.0, 2022,  6, 24, 15, 17, 53,      653,     4038, 304,  81,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 31, 29, 35,  0,  0, 38,  0, 35, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    37.31, 6,  drogue,  -17.65,  53596.00, 5058.91, 3729.11,  -27.42, 33.9, 1.70, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.31, 6,  drogue,  -17.65,  53596.00, 5058.91, 3729.11,  -27.42, 33.9, 1.70, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.31, 6,  drogue,  -17.65,  53596.00, 5058.91, 3729.11,  -27.42, 33.9, 1.70, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.41, 6,  drogue,  -11.77,  53594.00, 5059.19, 3729.39,  -27.94, 33.9, 1.70, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.46, 6,  drogue,  -11.77,  53594.00, 5059.19, 3729.39,  -27.94, 33.9, 1.70, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.51, 6,  drogue,  -13.24,  53615.00, 5056.26, 3726.46,  -28.51, 33.9, 1.70, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.61, 6,  drogue,   -8.83,  53614.00, 5056.40, 3726.60,  -29.11, 33.9, 1.70, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.71, 6,  drogue,   -9.32,  53635.00, 5053.47, 3723.67,  -29.76, 33.9, 1.70, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.78, 6,  drogue,   -9.32,  53635.00, 5053.47, 3723.67,  -29.76, 33.9, 1.70, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.81, 6,  drogue,  -11.28,  53659.00, 5050.13, 3720.33,  -30.43, 33.9, 1.70, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    37.91, 6,  drogue,  -14.22,  53660.00, 5049.99, 3720.19,  -31.00, 33.9, 1.70, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    38.01, 6,  drogue,  -11.77,  53676.00, 5047.76, 3717.96,  -31.50, 33.9, 1.70, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    38.10, 6,  drogue,  -11.77,  53676.00, 5047.76, 3717.96,  -31.50, 33.9, 1.70, 3.97, 3.99,   0.02,   0.00,   0.00,  64.15,  27.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    38.11, 6,  drogue,  -10.79,  53742.00, 5038.58, 3708.78,  -31.91, 33.9, 1.70, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    38.21, 6,  drogue,  -12.26,  53826.00, 5026.90, 3697.10,  -32.24, 33.9, 1.70, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9428638,-106.9172127,  5348.0, 2022,  6, 24, 15, 17, 54,      656,     4008, 305,  81,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 38,  0,  0,  0,  0, 36, 31, 28, 32,  0,  0, 32,  0, 31, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    38.31, 6,  drogue,  -16.18,  53841.00, 5024.82, 3695.02,  -32.47, 33.9, 1.70, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.31, 6,  drogue,  -16.18,  53841.00, 5024.82, 3695.02,  -32.47, 33.9, 1.70, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.31, 6,  drogue,  -16.18,  53841.00, 5024.82, 3695.02,  -32.47, 33.9, 1.70, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.41, 6,  drogue,  -19.61,  53884.00, 5018.85, 3689.04,  -32.58, 33.9, 1.70, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.42, 6,  drogue,  -19.61,  53884.00, 5018.85, 3689.04,  -32.58, 33.9, 1.69, 3.99, 3.98,   0.00,   0.00,   0.00,  63.97,  27.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.51, 6,  drogue,  -15.69,  53872.00, 5020.51, 3690.71,  -32.62, 33.9, 1.69, 3.99, 3.98,   0.09,   0.00,   0.00,  64.21,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.61, 6,  drogue,  -12.26,  53950.00, 5009.69, 3679.89,  -32.60, 33.9, 1.69, 3.99, 3.98,   0.09,   0.00,   0.00,  64.21,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.71, 6,  drogue,  -10.30,  53915.00, 5014.54, 3684.74,  -32.45, 33.9, 1.69, 3.99, 3.98,   0.09,   0.00,   0.00,  64.21,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.74, 6,  drogue,  -10.30,  53915.00, 5014.54, 3684.74,  -32.45, 33.9, 1.69, 3.96, 3.98,   0.09,   0.00,   0.00,  64.21,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.81, 6,  drogue,  -10.30,  53949.00, 5009.83, 3680.03,  -32.16, 33.9, 1.69, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    38.91, 6,  drogue,  -12.75,  53977.00, 5005.95, 3676.14,  -31.84, 33.9, 1.69, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    39.01, 6,  drogue,  -11.28,  54013.00, 5000.96, 3671.16,  -31.45, 33.9, 1.69, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    39.06, 6,  drogue,  -11.28,  54013.00, 5000.96, 3671.16,  -31.45, 33.9, 1.68, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  27.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    39.11, 6,  drogue,   -9.81,  54061.00, 4994.31, 3664.51,  -31.02, 33.9, 1.68, 3.98, 3.98,   0.00,   0.00,   0.04,  64.15,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    39.21, 6,  drogue,  -12.75,  54027.00, 4999.02, 3669.22,  -30.57, 33.9, 1.68, 3.98, 3.98,   0.00,   0.00,   0.04,  64.15,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9429285,-106.9171842,  5315.0, 2022,  6, 24, 15, 17, 55,      658,     3976, 305,  80,   1.4,   0.8,   1.1,  0, 32, 26,  0,  0, 34,  0,  0,  0,  0, 33, 26, 34, 35,  0,  0, 40,  0, 37, 29,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    39.31, 6,  drogue,  -17.65,  54002.00, 5002.48, 3672.68,  -30.16, 33.9, 1.68, 3.98, 3.98,   0.00,   0.00,   0.04,  64.15,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.31, 6,  drogue,  -17.65,  54002.00, 5002.48, 3672.68,  -30.16, 33.9, 1.68, 3.98, 3.98,   0.00,   0.00,   0.04,  64.15,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.31, 6,  drogue,  -17.65,  54002.00, 5002.48, 3672.68,  -30.16, 33.9, 1.68, 3.98, 3.98,   0.00,   0.00,   0.04,  64.15,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.38, 6,  drogue,  -17.65,  54002.00, 5002.48, 3672.68,  -30.16, 33.9, 1.68, 3.98, 3.99,   0.00,   0.00,   0.04,  64.15,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.41, 6,  drogue,  -16.18,  54031.00, 4998.46, 3668.66,  -29.73, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.51, 6,  drogue,  -15.20,  54078.00, 4991.96, 3662.15,  -29.39, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.61, 6,  drogue,  -22.56,  54086.00, 4990.85, 3661.05,  -29.14, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.70, 6,  drogue,  -22.56,  54086.00, 4990.85, 3661.05,  -29.14, 33.9, 1.67, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  27.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.71, 6,  drogue,  -21.57,  54130.00, 4984.76, 3654.96,  -28.97, 33.9, 1.67, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  26.92,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.81, 6,  drogue,  -20.10,  54182.00, 4977.57, 3647.77,  -28.87, 33.9, 1.67, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  26.92,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    39.91, 6,  drogue,  -19.12,  54210.00, 4973.70, 3643.90,  -28.85, 33.9, 1.67, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  26.92,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    40.01, 6,  drogue,  -18.63,  54224.00, 4971.77, 3641.97,  -28.86, 33.9, 1.67, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  26.92,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    40.02, 6,  drogue,  -18.63,  54224.00, 4971.77, 3641.97,  -28.86, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  26.92,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    40.11, 6,  drogue,  -19.61,  54229.00, 4971.08, 3641.28,  -28.97, 33.9, 1.68, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    40.21, 6,  drogue,  -20.10,  54262.00, 4966.52, 3636.72,  -29.14, 33.9, 1.68, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9429976,-106.9171641,  5281.0, 2022,  6, 24, 15, 17, 56,      661,     3943, 306,  80,   1.4,   0.8,   1.1,  0, 33, 35,  0,  0, 24,  0,  0,  0,  0, 33, 31, 36, 33,  0,  0, 33,  0, 28, 29,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    40.31, 6,  drogue,  -16.67,  54269.00, 4965.56, 3635.76,  -29.28, 33.9, 1.68, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.31, 6,  drogue,  -16.67,  54269.00, 4965.56, 3635.76,  -29.28, 33.9, 1.68, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.31, 6,  drogue,  -16.67,  54269.00, 4965.56, 3635.76,  -29.28, 33.9, 1.68, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.34, 6,  drogue,  -16.67,  54269.00, 4965.56, 3635.76,  -29.28, 33.9, 1.68, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.41, 6,  drogue,  -17.65,  54229.00, 4971.08, 3641.28,  -29.42, 33.9, 1.68, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  26.98,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.51, 6,  drogue,  -12.75,  54293.00, 4962.25, 3632.45,  -29.48, 33.9, 1.68, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  26.98,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.61, 6,  drogue,  -15.20,  54324.00, 4957.97, 3628.17,  -29.52, 33.9, 1.68, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  26.98,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.66, 6,  drogue,  -15.20,  54324.00, 4957.97, 3628.17,  -29.52, 33.9, 1.67, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  26.98,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.71, 6,  drogue,  -16.18,  54283.00, 4963.63, 3633.82,  -29.56, 33.9, 1.67, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.81, 6,  drogue,  -12.75,  54316.00, 4959.07, 3629.27,  -29.68, 33.9, 1.67, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.91, 6,  drogue,   -7.35,  54421.00, 4944.60, 3614.80,  -29.74, 33.9, 1.67, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    40.98, 6,  drogue,   -7.35,  54421.00, 4944.60, 3614.80,  -29.74, 33.9, 1.66, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    41.01, 6,  drogue,   -8.34,  54430.00, 4943.36, 3613.56,  -29.79, 33.9, 1.66, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    41.11, 6,  drogue,  -10.30,  54417.00, 4945.15, 3615.35,  -29.85, 33.9, 1.66, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    41.21, 6,  drogue,  -17.65,  54444.00, 4941.44, 3611.64,  -29.87, 33.9, 1.66, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    41.30, 6,  drogue,  -17.65,  54444.00, 4941.44, 3611.64,  -29.87, 33.9, 1.68, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9430741,-106.9171623,  5249.0, 2022,  6, 24, 15, 17, 57,      666,     3912, 307,  80,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 37,  0,  0,  0,  0, 38, 31, 28, 32,  0,  0, 33,  0, 35, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    41.31, 6,  drogue,  -18.14,  54467.00, 4938.27, 3608.47,  -29.95, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.31, 6,  drogue,  -18.14,  54467.00, 4938.27, 3608.47,  -29.95, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.31, 6,  drogue,  -18.14,  54467.00, 4938.27, 3608.47,  -29.95, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.41, 6,  drogue,  -17.16,  54454.00, 4940.06, 3610.26,  -30.04, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.51, 6,  drogue,  -15.69,  54540.00, 4928.23, 3598.43,  -30.12, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.61, 6,  drogue,  -17.16,  54603.00, 4919.58, 3589.78,  -30.25, 33.9, 1.68, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.62, 6,  drogue,  -17.16,  54603.00, 4919.58, 3589.78,  -30.25, 33.9, 1.67, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  27.04,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.71, 6,  drogue,  -14.22,  54609.00, 4918.75, 3588.95,  -30.43, 33.9, 1.67, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.81, 6,  drogue,  -18.14,  54617.00, 4917.65, 3587.85,  -30.70, 33.9, 1.67, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.91, 6,  drogue,  -14.71,  54644.00, 4913.95, 3584.15,  -31.08, 33.9, 1.67, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    41.94, 6,  drogue,  -14.71,  54644.00, 4913.95, 3584.15,  -31.08, 33.9, 1.66, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.86,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    42.01, 6,  drogue,  -10.79,  54615.00, 4917.93, 3588.13,  -31.53, 33.9, 1.66, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    42.11, 6,  drogue,   -4.90,  54639.00, 4914.63, 3584.83,  -31.97, 33.9, 1.66, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    42.21, 6,  drogue,   -8.34,  54653.00, 4912.71, 3582.91,  -32.40, 33.9, 1.66, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    42.26, 6,  drogue,   -8.34,  54653.00, 4912.71, 3582.91,  -32.40, 33.9, 1.65, 3.99, 4.00,   0.02,   0.00,   0.00,  64.15,  26.80,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9431434,-106.9171572,  5217.0, 2022,  6, 24, 15, 17, 58,      670,     3881, 307,  80,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 38, 31, 32, 35,  0,  0, 38,  0, 35, 33,  0,  0,  0, 24,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    42.31, 6,  drogue,   -7.35,  54635.00, 4915.18, 3585.38,  -32.88, 33.9, 1.65, 3.99, 4.00,   0.03,   0.00,   0.00,  64.21,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.31, 6,  drogue,   -7.35,  54635.00, 4915.18, 3585.38,  -32.88, 33.9, 1.65, 3.99, 4.00,   0.03,   0.00,   0.00,  64.21,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.31, 6,  drogue,   -7.35,  54635.00, 4915.18, 3585.38,  -32.88, 33.9, 1.65, 3.99, 4.00,   0.03,   0.00,   0.00,  64.21,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.41, 6,  drogue,   -8.34,  54673.00, 4909.97, 3580.17,  -33.37, 33.9, 1.65, 3.99, 4.00,   0.03,   0.00,   0.00,  64.21,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.51, 6,  drogue,   -5.88,  54661.00, 4911.61, 3581.81,  -33.95, 33.9, 1.65, 3.99, 4.00,   0.03,   0.00,   0.00,  64.21,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.58, 6,  drogue,   -5.88,  54661.00, 4911.61, 3581.81,  -33.95, 33.9, 1.66, 3.98, 3.98,   0.03,   0.00,   0.00,  64.21,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.61, 6,  drogue,    1.47,  54662.00, 4911.48, 3581.68,  -34.57, 33.9, 1.66, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.71, 6,  drogue,   18.63,  54802.00, 4892.29, 3562.49,  -35.17, 33.9, 1.66, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.81, 6,  drogue,   19.12,  54910.00, 4877.51, 3547.71,  -35.80, 33.9, 1.66, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.90, 6,  drogue,   19.12,  54910.00, 4877.51, 3547.71,  -35.80, 33.9, 1.65, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    42.91, 6,  drogue,   -9.81,  54850.00, 4885.72, 3555.92,  -36.43, 33.9, 1.65, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    43.01, 6,  drogue,   -9.81,  54856.00, 4884.90, 3555.10,  -36.95, 33.9, 1.65, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    43.11, 6,  drogue,    4.90,  54889.00, 4880.38, 3550.58,  -37.34, 33.9, 1.65, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    43.21, 6,  drogue,    2.45,  54935.00, 4874.10, 3544.29,  -37.65, 33.9, 1.65, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    43.22, 6,  drogue,    2.45,  54935.00, 4874.10, 3544.29,  -37.65, 33.9, 1.66, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9432222,-106.9171401,  5184.0, 2022,  6, 24, 15, 17, 59,      674,     3849, 308,  80,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 37,  0,  0,  0,  0, 31, 26, 29, 33,  0,  0, 36,  0, 38, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    43.31, 6,  drogue,    2.45,  55014.00, 4863.31, 3533.50,  -37.85, 33.9, 1.66, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.31, 6,  drogue,    2.45,  55014.00, 4863.31, 3533.50,  -37.85, 33.9, 1.66, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.31, 6,  drogue,    2.45,  55014.00, 4863.31, 3533.50,  -37.85, 33.9, 1.66, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.41, 6,  drogue,    4.41,  54988.00, 4866.86, 3537.05,  -37.90, 33.9, 1.66, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.51, 6,  drogue,   11.28,  54939.00, 4873.55, 3543.75,  -37.87, 33.9, 1.66, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.54, 6,  drogue,   11.28,  54939.00, 4873.55, 3543.75,  -37.87, 33.9, 1.64, 3.96, 3.97,   0.00,   0.00,   0.00,  64.09,  26.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.61, 6,  drogue,    8.34,  55017.00, 4862.90, 3533.10,  -37.73, 33.9, 1.64, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.71, 6,  drogue,   -3.92,  55029.00, 4861.26, 3531.46,  -37.43, 33.9, 1.64, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.81, 6,  drogue,   -5.88,  55115.00, 4849.53, 3519.73,  -36.99, 33.9, 1.64, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.86, 6,  drogue,   -5.88,  55115.00, 4849.53, 3519.73,  -36.99, 33.9, 1.64, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    43.91, 6,  drogue,  -12.75,  55203.00, 4837.54, 3507.74,  -36.52, 33.9, 1.64, 3.96, 3.97,   0.00,   0.01,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    44.01, 6,  drogue,   -9.32,  55232.00, 4833.60, 3503.80,  -35.97, 33.9, 1.64, 3.96, 3.97,   0.00,   0.01,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    44.11, 6,  drogue,    1.47,  55186.00, 4839.86, 3510.06,  -35.38, 33.9, 1.64, 3.96, 3.97,   0.00,   0.01,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    44.18, 6,  drogue,    1.47,  55186.00, 4839.86, 3510.06,  -35.38, 33.9, 1.63, 3.96, 3.97,   0.00,   0.01,   0.00,  63.78,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    44.21, 6,  drogue,   -9.32,  55129.00, 4847.62, 3517.82,  -34.78, 33.9, 1.63, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433104,-106.9171325,  5149.0, 2022,  6, 24, 15, 18,  0,      679,     3816, 308,  80,   1.4,   0.8,   1.1,  0, 28, 30,  0,  0, 34,  0,  0,  0,  0, 31, 31, 30, 32,  0,  0, 39,  0, 38, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    44.31, 6,  drogue,  -12.26,  55216.00, 4835.77, 3505.97,  -34.19, 33.9, 1.63, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.31, 6,  drogue,  -12.26,  55216.00, 4835.77, 3505.97,  -34.19, 33.9, 1.63, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.31, 6,  drogue,  -12.26,  55216.00, 4835.77, 3505.97,  -34.19, 33.9, 1.63, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.41, 6,  drogue,  -11.77,  55258.00, 4830.06, 3500.26,  -33.62, 33.9, 1.63, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.50, 6,  drogue,  -11.77,  55258.00, 4830.06, 3500.26,  -33.62, 33.9, 1.63, 3.98, 3.99,   0.00,   0.00,   0.00,  63.84,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.51, 6,  drogue,  -10.30,  55314.00, 4822.45, 3492.65,  -32.95, 33.9, 1.63, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.61, 6,  drogue,  -12.75,  55362.00, 4815.93, 3486.13,  -32.33, 33.9, 1.63, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.71, 6,  drogue,  -15.20,  55393.00, 4811.72, 3481.92,  -31.83, 33.9, 1.63, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.81, 6,  drogue,  -15.20,  55421.00, 4807.92, 3478.12,  -31.43, 33.9, 1.63, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.82, 6,  drogue,  -15.20,  55421.00, 4807.92, 3478.12,  -31.43, 33.9, 1.63, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    44.91, 6,  drogue,  -11.28,  55385.00, 4812.80, 3483.00,  -30.99, 33.9, 1.63, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    45.01, 6,  drogue,  -11.28,  55382.00, 4813.21, 3483.41,  -30.54, 33.9, 1.63, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    45.11, 6,  drogue,  -13.73,  55384.00, 4812.94, 3483.14,  -30.12, 33.9, 1.63, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    45.14, 6,  drogue,  -13.73,  55384.00, 4812.94, 3483.14,  -30.12, 33.9, 1.62, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    45.21, 6,  drogue,  -12.75,  55423.00, 4807.65, 3477.85,  -29.78, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9433848,-106.9171192,  5115.0, 2022,  6, 24, 15, 18,  1,      684,     3783, 309,  80,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 34, 29, 33, 35,  0,  0, 33,  0, 36, 26,  0,  0,  0, 26,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    45.31, 6,  drogue,   -5.88,  55437.00, 4805.75, 3475.95,  -29.51, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.31, 6,  drogue,   -5.88,  55437.00, 4805.75, 3475.95,  -29.51, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.31, 6,  drogue,   -5.88,  55437.00, 4805.75, 3475.95,  -29.51, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.41, 6,  drogue,   -2.94,  55457.00, 4803.03, 3473.23,  -29.24, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.46, 6,  drogue,   -2.94,  55457.00, 4803.03, 3473.23,  -29.24, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.51, 6,  drogue,  -13.24,  55469.00, 4801.41, 3471.61,  -28.94, 33.9, 1.62, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.61, 6,  drogue,  -15.20,  55500.00, 4797.20, 3467.40,  -28.76, 33.9, 1.62, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.71, 6,  drogue,  -13.24,  55527.00, 4793.55, 3463.75,  -28.62, 33.8, 1.62, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.78, 6,  drogue,  -13.24,  55527.00, 4793.55, 3463.75,  -28.62, 33.8, 1.62, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.81, 6,  drogue,   -7.35,  55536.00, 4792.33, 3462.53,  -28.51, 33.9, 1.62, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    45.91, 6,  drogue,  -14.22,  55643.00, 4777.84, 3448.04,  -28.40, 33.9, 1.62, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.01, 6,  drogue,  -14.71,  55682.00, 4772.57, 3442.77,  -28.30, 33.9, 1.62, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.10, 6,  drogue,  -14.71,  55682.00, 4772.57, 3442.77,  -28.30, 33.9, 1.62, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.11, 6,  drogue,  -14.22,  55676.00, 4773.38, 3443.58,  -28.18, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.21, 6,  drogue,  -15.20,  55704.00, 4769.60, 3439.80,  -28.08, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.31, 6,  drogue,  -12.26,  55747.00, 4763.79, 3433.99,  -28.09, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.32, 6,  drogue,  -12.26,  55747.00, 4763.79, 3433.99,  -28.09, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.32, 6,  drogue,  -12.26,  55747.00, 4763.79, 3433.99,  -28.09, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9434746,-106.9170926,  5084.0, 2022,  6, 24, 15, 18,  2,      688,     3754, 310,  79,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 34,  0,  0,  0,  0, 34, 33, 22, 39,  0,  0, 38,  0, 33, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.41, 6,  drogue,   -7.35,  55714.00, 4768.25, 3438.45,  -28.17, 33.9, 1.62, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.42, 6,  drogue,   -7.35,  55714.00, 4768.25, 3438.45,  -28.17, 33.9, 1.61, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.51, 6,  drogue,  -10.79,  55613.00, 4781.90, 3452.10,  -28.29, 33.9, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.61, 6,  drogue,  -13.24,  55694.00, 4770.95, 3441.15,  -28.44, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.71, 6,  drogue,   -9.81,  55711.00, 4768.65, 3438.85,  -28.58, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.74, 6,  drogue,   -9.81,  55711.00, 4768.65, 3438.85,  -28.58, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.81, 6,  drogue,   -9.32,  55783.00, 4758.93, 3429.13,  -28.75, 33.9, 1.61, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    46.91, 6,  drogue,   -7.35,  55818.00, 4754.21, 3424.41,  -28.90, 33.8, 1.61, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.01, 6,  drogue,  -14.71,  55792.00, 4757.71, 3427.91,  -29.10, 33.8, 1.61, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.06, 6,  drogue,  -14.71,  55792.00, 4757.71, 3427.91,  -29.10, 33.8, 1.61, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.11, 6,  drogue,  -13.24,  55802.00, 4756.37, 3426.56,  -29.34, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.21, 6,  drogue,  -13.24,  55867.00, 4747.60, 3417.80,  -29.63, 33.9, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.31, 6,  drogue,  -10.30,  55889.00, 4744.63, 3414.83,  -29.95, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.31, 6,  drogue,  -10.30,  55889.00, 4744.63, 3414.83,  -29.95, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.31, 6,  drogue,  -10.30,  55889.00, 4744.63, 3414.83,  -29.95, 33.8, 1.61, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9435897,-106.9170848,  5055.0, 2022,  6, 24, 15, 18,  3,      696,     3727, 311,  79,   1.4,   0.8,   1.1,  0, 29, 25,  0,  0, 38,  0,  0,  0,  0, 30, 36, 24, 31,  0,  0, 30,  0, 33, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    47.38, 6,  drogue,  -10.30,  55889.00, 4744.63, 3414.83,  -29.95, 33.8, 1.61, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.41, 6,  drogue,  -14.71,  55930.00, 4739.11, 3409.31,  -30.28, 33.8, 1.61, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.51, 6,  drogue,  -15.69,  55911.00, 4741.67, 3411.87,  -30.60, 33.8, 1.61, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.61, 6,  drogue,  -15.69,  55971.00, 4733.59, 3403.79,  -30.86, 33.8, 1.61, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.70, 6,  drogue,  -15.69,  55971.00, 4733.59, 3403.79,  -30.86, 33.8, 1.60, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.71, 6,  drogue,  -15.69,  56004.00, 4729.15, 3399.35,  -31.14, 33.9, 1.60, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.81, 6,  drogue,  -17.16,  55969.00, 4733.86, 3404.06,  -31.35, 33.8, 1.60, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    47.91, 6,  drogue,  -15.69,  55941.00, 4737.63, 3407.83,  -31.56, 33.8, 1.60, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    48.01, 6,  drogue,  -15.69,  56000.00, 4729.69, 3399.89,  -31.69, 33.8, 1.60, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    48.02, 6,  drogue,  -15.69,  56000.00, 4729.69, 3399.89,  -31.69, 33.8, 1.60, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    48.11, 6,  drogue,  -11.28,  56075.00, 4719.60, 3389.80,  -31.75, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    48.21, 6,  drogue,  -11.77,  56143.00, 4710.47, 3380.67,  -31.78, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9437054,-106.9170802,  5024.0, 2022,  6, 24, 15, 18,  4,      704,     3698, 312,  79,   1.4,   0.8,   1.1,  0, 37, 31,  0,  0, 38,  0,  0,  0,  0, 39, 34, 31, 31,  0,  0, 35,  0, 29, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    48.31, 6,  drogue,  -12.26,  56160.00, 4708.18, 3378.38,  -31.81, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.31, 6,  drogue,  -12.26,  56160.00, 4708.18, 3378.38,  -31.81, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.31, 6,  drogue,  -12.26,  56160.00, 4708.18, 3378.38,  -31.81, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.34, 6,  drogue,  -12.26,  56160.00, 4708.18, 3378.38,  -31.81, 33.8, 1.61, 3.99, 3.99,   0.00,   0.00,   0.00,  64.03,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.41, 6,  drogue,  -12.75,  56186.00, 4704.69, 3374.89,  -31.75, 33.8, 1.61, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.51, 6,  drogue,   -7.85,  56177.00, 4705.90, 3376.10,  -31.59, 33.8, 1.61, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.61, 6,  drogue,   -9.81,  56181.00, 4705.37, 3375.56,  -31.47, 33.8, 1.61, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.66, 6,  drogue,   -9.81,  56181.00, 4705.37, 3375.56,  -31.47, 33.8, 1.60, 3.96, 3.97,   0.09,   0.00,   0.00,  64.21,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.71, 6,  drogue,  -17.65,  56165.00, 4707.51, 3377.71,  -31.34, 33.8, 1.60, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.81, 6,  drogue,  -15.69,  56209.00, 4701.61, 3371.81,  -31.28, 33.8, 1.60, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.91, 6,  drogue,  -18.63,  56250.00, 4696.11, 3366.31,  -31.22, 33.8, 1.60, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    48.98, 6,  drogue,  -18.63,  56250.00, 4696.11, 3366.31,  -31.22, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.00,  63.78,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    49.01, 6,  drogue,  -15.69,  56296.00, 4689.95, 3360.14,  -31.10, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    49.11, 6,  drogue,  -16.67,  56338.00, 4684.32, 3354.52,  -30.98, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    49.21, 6,  drogue,  -19.61,  56342.00, 4683.79, 3353.98,  -30.87, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    49.30, 6,  drogue,  -19.61,  56342.00, 4683.79, 3353.98,  -30.87, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  63.91,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9438112,-106.9171268,  4993.0, 2022,  6, 24, 15, 18,  5,      715,     3669, 312,  79,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 38,  0,  0,  0,  0, 33, 29, 30, 35,  0,  0, 34,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    49.31, 6,  drogue,  -16.67,  56384.00, 4678.16, 3348.36,  -30.79, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.31, 6,  drogue,  -16.67,  56384.00, 4678.16, 3348.36,  -30.79, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.31, 6,  drogue,  -16.67,  56384.00, 4678.16, 3348.36,  -30.79, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.41, 6,  drogue,  -14.71,  56387.00, 4677.76, 3347.96,  -30.76, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.51, 6,  drogue,  -11.77,  56400.00, 4676.02, 3346.22,  -30.71, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.61, 6,  drogue,  -15.69,  56370.00, 4680.04, 3350.24,  -30.66, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.62, 6,  drogue,  -15.69,  56370.00, 4680.04, 3350.24,  -30.66, 33.8, 1.60, 3.97, 3.99,   0.00,   0.00,   0.00,  64.15,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.71, 6,  drogue,  -15.69,  56446.00, 4669.87, 3340.07,  -30.58, 33.8, 1.60, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.81, 6,  drogue,  -17.16,  56446.00, 4669.87, 3340.07,  -30.50, 33.8, 1.60, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.91, 6,  drogue,  -17.16,  56452.00, 4669.07, 3339.27,  -30.44, 33.8, 1.60, 3.97, 3.99,   0.00,   0.00,   0.00,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    49.94, 6,  drogue,  -17.16,  56452.00, 4669.07, 3339.27,  -30.44, 33.8, 1.60, 3.98, 3.98,   0.00,   0.00,   0.00,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    50.01, 6,  drogue,  -14.71,  56475.00, 4666.00, 3336.19,  -30.31, 33.8, 1.60, 3.98, 3.98,   0.01,   0.00,   0.00,  64.03,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    50.11, 6,  drogue,  -15.69,  56542.00, 4657.05, 3327.25,  -30.17, 33.8, 1.60, 3.98, 3.98,   0.01,   0.00,   0.00,  64.03,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    50.21, 6,  drogue,  -14.22,  56578.00, 4652.24, 3322.44,  -29.92, 33.8, 1.60, 3.98, 3.98,   0.01,   0.00,   0.00,  64.03,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    50.26, 6,  drogue,  -14.22,  56578.00, 4652.24, 3322.44,  -29.92, 33.8, 1.60, 3.97, 3.98,   0.01,   0.00,   0.00,  64.03,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9439137,-106.9171816,  4962.0, 2022,  6, 24, 15, 18,  6,      726,     3641, 312,  78,   1.4,   0.8,   1.1,  0, 29, 34,  0,  0, 23,  0,  0,  0,  0, 33, 34, 31, 36,  0,  0, 31,  0, 30, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    50.31, 6,  drogue,  -16.18,  56639.00, 4644.11, 3314.30,  -29.60, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.31, 6,  drogue,  -16.18,  56639.00, 4644.11, 3314.30,  -29.60, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.31, 6,  drogue,  -16.18,  56639.00, 4644.11, 3314.30,  -29.60, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.41, 6,  drogue,  -17.16,  56627.00, 4645.71, 3315.90,  -29.31, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.51, 6,  drogue,  -17.16,  56641.00, 4643.84, 3314.04,  -28.99, 33.8, 1.60, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.01, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.58, 6,  drogue,  -17.16,  56641.00, 4643.84, 3314.04,  -28.99, 33.8, 1.59, 3.98, 3.99,   0.00,   0.00,   0.01,  63.97,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.61, 6,  drogue,  -17.16,  56634.00, 4644.77, 3314.97,  -28.68, 33.8, 1.59, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.71, 6,  drogue,  -20.10,  56647.00, 4643.04, 3313.24,  -28.35, 33.8, 1.59, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.81, 6,  drogue,  -15.69,  56710.00, 4634.65, 3304.84,  -28.01, 33.8, 1.59, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.90, 6,  drogue,  -15.69,  56710.00, 4634.65, 3304.84,  -28.01, 33.8, 1.58, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    50.91, 6,  drogue,  -16.18,  56724.00, 4632.78, 3302.98,  -27.65, 33.8, 1.58, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    51.01, 6,  drogue,  -17.65,  56722.00, 4633.05, 3303.25,  -27.24, 33.8, 1.58, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    51.11, 6,  drogue,  -19.12,  56746.00, 4629.85, 3300.05,  -26.83, 33.8, 1.58, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    51.21, 6,  drogue,  -13.73,  56746.00, 4629.85, 3300.05,  -26.40, 33.8, 1.58, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    51.22, 6,  drogue,  -13.73,  56746.00, 4629.85, 3300.05,  -26.40, 33.8, 1.58, 3.96, 3.97,   0.08,   0.00,   0.00,  64.03,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9439925,-106.9172153,  4930.0, 2022,  6, 24, 15, 18,  7,      735,     3612, 313,  78,   1.4,   0.8,   1.1,  0, 33, 36,  0,  0, 35,  0,  0,  0,  0, 32, 33, 30, 36,  0,  0, 39,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    51.31, 6,  drogue,  -18.14,  56802.00, 4622.40, 3292.60,  -26.08, 33.8, 1.58, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.31, 6,  drogue,  -18.14,  56802.00, 4622.40, 3292.60,  -26.08, 33.8, 1.58, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.31, 6,  drogue,  -18.14,  56802.00, 4622.40, 3292.60,  -26.08, 33.8, 1.58, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.41, 6,  drogue,  -10.79,  56876.00, 4612.56, 3282.76,  -25.79, 33.8, 1.58, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.51, 6,  drogue,   -7.85,  56882.00, 4611.77, 3281.97,  -25.58, 33.8, 1.58, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.54, 6,  drogue,   -7.85,  56882.00, 4611.77, 3281.97,  -25.58, 33.8, 1.58, 3.98, 3.98,   0.00,   0.00,   0.00,  63.84,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.61, 6,  drogue,  -11.77,  56852.00, 4615.75, 3285.95,  -25.42, 33.8, 1.58, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.71, 6,  drogue,  -16.18,  56845.00, 4616.68, 3286.88,  -25.36, 33.8, 1.58, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.81, 6,  drogue,   -9.32,  56932.00, 4605.13, 3275.32,  -25.33, 33.8, 1.58, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.86, 6,  drogue,   -9.32,  56932.00, 4605.13, 3275.32,  -25.33, 33.8, 1.58, 3.99, 3.99,   0.09,   0.00,   0.00,  64.03,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    51.91, 6,  drogue,   10.79,  56978.00, 4599.02, 3269.22,  -25.30, 33.8, 1.58, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    52.01, 6,  drogue,    4.41,  56875.00, 4612.70, 3282.90,  -25.31, 33.8, 1.58, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    52.11, 6,  drogue,  -16.67,  56875.00, 4612.70, 3282.90,  -25.37, 33.8, 1.58, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    52.18, 6,  drogue,  -16.67,  56875.00, 4612.70, 3282.90,  -25.37, 33.8, 1.57, 3.98, 3.99,   0.08,   0.00,   0.00,  64.27,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    52.21, 6,  drogue,  -12.75,  56825.00, 4619.34, 3289.54,  -25.44, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9440689,-106.9172401,  4899.0, 2022,  6, 24, 15, 18,  8,      742,     3583, 313,  78,   1.4,   0.8,   1.1,  0, 38, 28,  0,  0, 40,  0,  0,  0,  0, 38, 32, 29, 32,  0,  0, 28,  0, 30, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    52.31, 6,  drogue,   -7.85,  56884.00, 4611.50, 3281.70,  -25.58, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.31, 6,  drogue,   -7.85,  56884.00, 4611.50, 3281.70,  -25.58, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.31, 6,  drogue,   -7.85,  56884.00, 4611.50, 3281.70,  -25.58, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.41, 6,  drogue,   -4.90,  57032.00, 4591.86, 3262.06,  -25.67, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.50, 6,  drogue,   -4.90,  57032.00, 4591.86, 3262.06,  -25.67, 33.8, 1.58, 3.99, 4.00,   0.03,   0.00,   0.00,  64.15,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.51, 6,  drogue,  -13.24,  57098.00, 4583.11, 3253.31,  -25.74, 33.8, 1.58, 3.99, 4.00,   0.02,   0.00,   0.00,  64.21,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.61, 6,  drogue,  -17.65,  57134.00, 4578.35, 3248.55,  -25.78, 33.8, 1.58, 3.99, 4.00,   0.02,   0.00,   0.00,  64.21,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.71, 6,  drogue,  -15.69,  57135.00, 4578.21, 3248.41,  -25.81, 33.8, 1.58, 3.99, 4.00,   0.02,   0.00,   0.00,  64.21,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.81, 6,  drogue,   -7.35,  57104.00, 4582.32, 3252.52,  -25.91, 33.8, 1.58, 3.99, 4.00,   0.02,   0.00,   0.00,  64.21,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.82, 6,  drogue,   -7.35,  57104.00, 4582.32, 3252.52,  -25.91, 33.8, 1.58, 3.98, 3.98,   0.02,   0.00,   0.00,  64.21,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    52.91, 6,  drogue,  -16.67,  57054.00, 4588.94, 3259.14,  -26.00, 33.8, 1.58, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.01, 6,  drogue,  -15.69,  57026.00, 4592.65, 3262.85,  -26.06, 33.8, 1.58, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.11, 6,  drogue,  -16.18,  57051.00, 4589.34, 3259.54,  -26.07, 33.8, 1.58, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.14, 6,  drogue,  -16.18,  57051.00, 4589.34, 3259.54,  -26.07, 33.8, 1.58, 3.99, 3.98,   0.03,   0.00,   0.00,  64.15,  25.45,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.21, 6,  drogue,  -11.28,  57095.00, 4583.51, 3253.71,  -26.07, 33.8, 1.58, 3.99, 3.98,   0.00,   0.00,   0.04,  64.27,  25.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9441416,-106.9172531,  4871.0, 2022,  6, 24, 15, 18,  9,      749,     3557, 313,  78,   1.4,   0.8,   1.1,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 31, 38, 33, 28,  0,  0, 34,  0, 34, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.31, 6,  drogue,   -9.81,  57212.00, 4568.03, 3238.23,  -26.13, 33.8, 1.58, 3.99, 3.98,   0.00,   0.00,   0.04,  64.27,  25.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.31, 6,  drogue,   -9.81,  57212.00, 4568.03, 3238.23,  -26.13, 33.8, 1.58, 3.99, 3.98,   0.00,   0.00,   0.04,  64.27,  25.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.31, 6,  drogue,   -9.81,  57212.00, 4568.03, 3238.23,  -26.13, 33.8, 1.58, 3.99, 3.98,   0.00,   0.00,   0.04,  64.27,  25.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.41, 6,  drogue,  -13.73,  57254.00, 4562.47, 3232.67,  -26.24, 33.8, 1.58, 3.99, 3.98,   0.00,   0.00,   0.04,  64.27,  25.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.46, 6,  drogue,  -13.73,  57254.00, 4562.47, 3232.67,  -26.24, 33.8, 1.57, 3.98, 3.99,   0.00,   0.00,   0.04,  64.27,  25.39,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.51, 6,  drogue,  -15.69,  57296.00, 4556.93, 3227.12,  -26.32, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.61, 6,  drogue,  -16.18,  57314.00, 4554.55, 3224.75,  -26.36, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.71, 6,  drogue,  -12.75,  57305.00, 4555.74, 3225.94,  -26.39, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.78, 6,  drogue,  -12.75,  57305.00, 4555.74, 3225.94,  -26.39, 33.8, 1.57, 3.96, 3.97,   0.03,   0.00,   0.00,  64.15,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.81, 6,  drogue,  -15.69,  57274.00, 4559.83, 3230.03,  -26.50, 33.8, 1.57, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    53.91, 6,  drogue,  -15.69,  57248.00, 4563.27, 3233.47,  -26.62, 33.8, 1.57, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    54.01, 6,  drogue,  -14.71,  57270.00, 4560.36, 3230.56,  -26.67, 33.8, 1.57, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    54.10, 6,  drogue,  -14.71,  57270.00, 4560.36, 3230.56,  -26.67, 33.8, 1.57, 3.99, 3.99,   0.00,   0.00,   0.00,  63.78,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    54.11, 6,  drogue,  -12.75,  57277.00, 4559.44, 3229.63,  -26.73, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    54.21, 6,  drogue,   -7.85,  57306.00, 4555.60, 3225.80,  -26.81, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9442246,-106.9172341,  4839.0, 2022,  6, 24, 15, 18, 10,      754,     3526, 314,  78,   1.4,   0.8,   1.1,  0, 31, 34,  0,  0, 30,  0,  0,  0,  0, 27, 28, 25, 36,  0,  0, 38,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    54.31, 6,  drogue,   -2.45,  57376.00, 4546.37, 3216.56,  -26.96, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.31, 6,  drogue,   -2.45,  57376.00, 4546.37, 3216.56,  -26.96, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.31, 6,  drogue,   -2.45,  57376.00, 4546.37, 3216.56,  -26.96, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.41, 6,  drogue,   -0.98,  57389.00, 4544.65, 3214.85,  -27.22, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.42, 6,  drogue,   -0.98,  57389.00, 4544.65, 3214.85,  -27.22, 33.8, 1.57, 3.98, 3.99,   0.03,   0.00,   0.00,  64.21,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.51, 6,  drogue,   -6.37,  57410.00, 4541.88, 3212.08,  -27.50, 33.8, 1.57, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.61, 6,  drogue,  -13.24,  57418.00, 4540.83, 3211.02,  -27.74, 33.8, 1.57, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.71, 6,  drogue,  -11.28,  57454.00, 4536.08, 3206.28,  -27.93, 33.8, 1.57, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.74, 6,  drogue,  -11.28,  57454.00, 4536.08, 3206.28,  -27.93, 33.8, 1.57, 3.99, 3.99,   0.09,   0.00,   0.00,  64.09,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.81, 6,  drogue,   -7.85,  57531.00, 4525.94, 3196.14,  -28.00, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    54.91, 6,  drogue,  -11.28,  57554.00, 4522.91, 3193.11,  -27.98, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    55.01, 6,  drogue,  -16.18,  57539.00, 4524.89, 3195.08,  -27.99, 33.8, 1.57, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    55.06, 6,  drogue,  -16.18,  57539.00, 4524.89, 3195.08,  -27.99, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.27,  25.27,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    55.11, 6,  drogue,  -15.20,  57505.00, 4529.36, 3199.56,  -28.02, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    55.21, 6,  drogue,  -13.24,  57545.00, 4524.10, 3194.29,  -28.11, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9443244,-106.9171895,  4808.0, 2022,  6, 24, 15, 18, 11,      758,     3497, 315,  77,   1.4,   0.8,   1.1,  0, 24, 35,  0,  0, 30,  0,  0,  0,  0, 20, 29, 35, 38,  0,  0, 36,  0, 29, 21,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    55.31, 6,  drogue,  -16.18,  57610.00, 4515.54, 3185.74,  -28.22, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.31, 6,  drogue,  -16.18,  57610.00, 4515.54, 3185.74,  -28.22, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.31, 6,  drogue,  -16.18,  57610.00, 4515.54, 3185.74,  -28.22, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.38, 6,  drogue,  -16.18,  57610.00, 4515.54, 3185.74,  -28.22, 33.8, 1.57, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.41, 6,  drogue,  -12.75,  57640.00, 4511.60, 3181.80,  -28.28, 33.8, 1.57, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.51, 6,  drogue,  -12.26,  57639.00, 4511.73, 3181.93,  -28.31, 33.8, 1.57, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.61, 6,  drogue,  -13.73,  57644.00, 4511.08, 3181.27,  -28.29, 33.8, 1.57, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.70, 6,  drogue,  -13.73,  57644.00, 4511.08, 3181.27,  -28.29, 33.8, 1.56, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  25.21,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.71, 6,  drogue,  -13.73,  57651.00, 4510.16, 3180.35,  -28.21, 33.8, 1.56, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.81, 6,  drogue,  -12.75,  57687.00, 4505.43, 3175.62,  -28.13, 33.8, 1.56, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    55.91, 6,  drogue,  -11.77,  57695.00, 4504.37, 3174.57,  -28.05, 33.8, 1.56, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.01, 6,  drogue,  -17.16,  57728.00, 4500.04, 3170.24,  -28.05, 33.8, 1.56, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.02, 6,  drogue,  -17.16,  57728.00, 4500.04, 3170.24,  -28.05, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.11, 6,  drogue,  -18.14,  57745.00, 4497.81, 3168.01,  -28.09, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.21, 6,  drogue,  -22.06,  57791.00, 4491.77, 3161.97,  -28.21, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9444363,-106.9171610,  4778.0, 2022,  6, 24, 15, 18, 12,      765,     3469, 316,  77,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 36, 35, 30, 29,  0,  0, 23,  0, 28, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.31, 6,  drogue,  -19.61,  57818.00, 4488.23, 3158.43,  -28.42, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.31, 6,  drogue,  -19.61,  57818.00, 4488.23, 3158.43,  -28.42, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.31, 6,  drogue,  -19.61,  57818.00, 4488.23, 3158.43,  -28.42, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.34, 6,  drogue,  -19.61,  57818.00, 4488.23, 3158.43,  -28.42, 33.8, 1.55, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.41, 6,  drogue,  -15.20,  57854.00, 4483.52, 3153.71,  -28.70, 33.8, 1.55, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.51, 6,  drogue,  -14.22,  57876.00, 4480.63, 3150.83,  -29.02, 33.8, 1.55, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.61, 6,  drogue,  -10.30,  57875.00, 4480.76, 3150.96,  -29.35, 33.8, 1.55, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.66, 6,  drogue,  -10.30,  57875.00, 4480.76, 3150.96,  -29.35, 33.8, 1.56, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.71, 6,  drogue,  -18.14,  57893.00, 4478.41, 3148.60,  -29.71, 33.8, 1.56, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.81, 6,  drogue,  -17.16,  57857.00, 4483.12, 3153.32,  -30.11, 33.8, 1.56, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.91, 6,  drogue,  -15.20,  57859.00, 4482.86, 3153.06,  -30.45, 33.8, 1.56, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    56.98, 6,  drogue,  -15.20,  57859.00, 4482.86, 3153.06,  -30.45, 33.8, 1.55, 3.99, 3.99,   0.00,   0.00,   0.00,  64.03,  25.09,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    57.01, 6,  drogue,  -13.73,  57986.00, 4466.23, 3136.43,  -30.77, 33.8, 1.55, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    57.11, 6,  drogue,  -17.65,  57992.00, 4465.45, 3135.65,  -31.03, 33.8, 1.55, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    57.21, 6,  drogue,  -15.69,  58052.00, 4457.60, 3127.80,  -31.27, 33.8, 1.55, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    57.30, 6,  drogue,  -15.69,  58052.00, 4457.60, 3127.80,  -31.27, 33.8, 1.54, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  25.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9445555,-106.9171823,  4748.0, 2022,  6, 24, 15, 18, 13,      776,     3443, 316,  77,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 37,  0,  0,  0,  0, 35, 23, 31, 31,  0,  0, 34,  0, 32, 25,  0,  0,  0, 24,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    57.31, 6,  drogue,  -12.75,  58019.00, 4461.92, 3132.12,  -31.52, 33.8, 1.54, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.31, 6,  drogue,  -12.75,  58019.00, 4461.92, 3132.12,  -31.52, 33.8, 1.54, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.31, 6,  drogue,  -12.75,  58019.00, 4461.92, 3132.12,  -31.52, 33.8, 1.54, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.41, 6,  drogue,  -11.28,  58009.00, 4463.23, 3133.42,  -31.74, 33.8, 1.54, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.51, 6,  drogue,  -10.30,  58040.00, 4459.17, 3129.37,  -31.94, 33.8, 1.54, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.61, 6,  drogue,   -5.88,  58045.00, 4458.52, 3128.72,  -32.09, 33.8, 1.54, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.62, 6,  drogue,   -5.88,  58045.00, 4458.52, 3128.72,  -32.09, 33.8, 1.54, 3.98, 3.99,   0.00,   0.00,   0.00,  64.27,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.71, 6,  drogue,   -0.00,  58077.00, 4454.34, 3124.54,  -32.16, 33.8, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.81, 6,  drogue,   -4.90,  58152.00, 4444.54, 3114.74,  -32.20, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.91, 6,  drogue,   -4.90,  58182.00, 4440.63, 3110.83,  -32.17, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    57.94, 6,  drogue,   -4.90,  58182.00, 4440.63, 3110.83,  -32.17, 33.7, 1.54, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  24.84,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.01, 6,  drogue,  -14.71,  58240.00, 4433.07, 3103.27,  -32.09, 33.7, 1.54, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.11, 6,  drogue,  -20.10,  58264.00, 4429.94, 3100.14,  -31.94, 33.7, 1.54, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.21, 6,  drogue,  -17.65,  58295.00, 4425.90, 3096.10,  -31.77, 33.7, 1.54, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.26, 6,  drogue,  -17.65,  58295.00, 4425.90, 3096.10,  -31.77, 33.7, 1.54, 3.97, 3.98,   0.08,   0.00,   0.00,  64.15,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.31, 6,  drogue,  -20.10,  58314.00, 4423.43, 3093.63,  -31.57, 33.8, 1.54, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.31, 6,  drogue,  -20.10,  58314.00, 4423.43, 3093.63,  -31.57, 33.8, 1.54, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.31, 6,  drogue,  -20.10,  58314.00, 4423.43, 3093.63,  -31.57, 33.8, 1.54, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9446787,-106.9172181,  4717.0, 2022,  6, 24, 15, 18, 14,      789,     3415, 317,  77,   1.4,   0.8,   1.1,  0, 31, 31,  0,  0, 36,  0,  0,  0,  0, 26, 30, 30, 34,  0,  0, 39,  0, 36, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    58.41, 6,  drogue,  -18.14,  58376.00, 4415.36, 3085.56,  -31.30, 33.7, 1.54, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.51, 6,  drogue,  -16.18,  58370.00, 4416.14, 3086.34,  -30.99, 33.7, 1.54, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.58, 6,  drogue,  -16.18,  58370.00, 4416.14, 3086.34,  -30.99, 33.7, 1.54, 3.96, 3.97,   0.00,   0.00,   0.00,  63.91,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.61, 6,  drogue,  -19.61,  58345.00, 4419.39, 3089.59,  -30.65, 33.7, 1.54, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.71, 6,  drogue,  -18.14,  58367.00, 4416.53, 3086.73,  -30.32, 33.7, 1.54, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.81, 6,  drogue,  -18.14,  58373.00, 4415.75, 3085.95,  -29.97, 33.7, 1.54, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.90, 6,  drogue,  -18.14,  58373.00, 4415.75, 3085.95,  -29.97, 33.7, 1.53, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    58.91, 6,  drogue,  -12.26,  58341.00, 4419.91, 3090.11,  -29.67, 33.7, 1.53, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    59.01, 6,  drogue,   -9.32,  58410.00, 4410.94, 3081.14,  -29.52, 33.7, 1.53, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    59.11, 6,  drogue,  -11.77,  58440.00, 4407.04, 3077.23,  -29.43, 33.7, 1.53, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    59.21, 6,  drogue,  -10.30,  58458.00, 4404.70, 3074.90,  -29.38, 33.7, 1.53, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    59.22, 6,  drogue,  -10.30,  58458.00, 4404.70, 3074.90,  -29.38, 33.7, 1.54, 3.98, 3.98,   0.00,   0.00,   0.00,  63.72,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9447887,-106.9172483,  4687.0, 2022,  6, 24, 15, 18, 15,      799,     3389, 317,  76,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 37, 24, 30, 30,  0,  0, 36,  0, 36, 30,  0,  0,  0, 24,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    59.31, 6,  drogue,   -5.88,  58498.00, 4399.50, 3069.70,  -29.30, 33.7, 1.54, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.31, 6,  drogue,   -5.88,  58498.00, 4399.50, 3069.70,  -29.30, 33.7, 1.54, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.31, 6,  drogue,   -5.88,  58498.00, 4399.50, 3069.70,  -29.30, 33.7, 1.54, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.41, 6,  drogue,   -7.35,  58556.00, 4391.97, 3062.17,  -29.20, 33.7, 1.54, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.51, 6,  drogue,  -10.30,  58619.00, 4383.80, 3054.00,  -29.19, 33.7, 1.54, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.54, 6,  drogue,  -10.30,  58619.00, 4383.80, 3054.00,  -29.19, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  24.78,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.61, 6,  drogue,  -12.26,  58644.00, 4380.56, 3050.76,  -29.18, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.71, 6,  drogue,   -7.35,  58619.00, 4383.80, 3054.00,  -29.19, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.81, 6,  drogue,  -15.20,  58627.00, 4382.76, 3052.96,  -29.28, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.86, 6,  drogue,  -15.20,  58627.00, 4382.76, 3052.96,  -29.28, 33.7, 1.55, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    59.91, 6,  drogue,  -12.75,  58643.00, 4380.69, 3050.89,  -29.42, 33.7, 1.55, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  24.96,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    60.01, 6,  drogue,  -14.71,  58649.00, 4379.91, 3050.11,  -29.54, 33.7, 1.55, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  24.96,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    60.11, 6,  drogue,  -15.20,  58653.00, 4379.39, 3049.59,  -29.64, 33.7, 1.55, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  24.96,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    60.18, 6,  drogue,  -15.20,  58653.00, 4379.39, 3049.59,  -29.64, 33.7, 1.54, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  24.96,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    60.21, 6,  drogue,  -17.65,  58692.00, 4374.34, 3044.54,  -29.68, 33.7, 1.54, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9448738,-106.9172739,  4657.0, 2022,  6, 24, 15, 18, 16,      808,     3362, 318,  76,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 32, 37, 30, 30,  0,  0, 28,  0, 35, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,    60.31, 6,  drogue,  -12.26,  58732.00, 4369.16, 3039.36,  -29.66, 33.7, 1.54, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.31, 6,  drogue,  -12.26,  58732.00, 4369.16, 3039.36,  -29.66, 33.7, 1.54, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.31, 6,  drogue,  -12.26,  58732.00, 4369.16, 3039.36,  -29.66, 33.7, 1.54, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.41, 6,  drogue,  -12.75,  58706.00, 4372.52, 3042.72,  -29.64, 33.7, 1.54, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.50, 6,  drogue,  -12.75,  58706.00, 4372.52, 3042.72,  -29.64, 33.7, 1.54, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.51, 6,  drogue,  -15.69,  58737.00, 4368.51, 3038.71,  -29.56, 33.7, 1.54, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.61, 6,  drogue,  -17.65,  58776.00, 4363.46, 3033.66,  -29.47, 33.7, 1.54, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.71, 6,  drogue,  -15.20,  58821.00, 4357.64, 3027.84,  -29.40, 33.7, 1.54, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.81, 6,  drogue,  -13.24,  58857.00, 4352.99, 3023.19,  -29.33, 33.7, 1.54, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.82, 6,  drogue,  -13.24,  58857.00, 4352.99, 3023.19,  -29.33, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    60.91, 6,  drogue,  -15.69,  58911.00, 4346.01, 3016.21,  -29.23, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.01, 6,  drogue,  -11.28,  58969.00, 4338.53, 3008.73,  -29.13, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.11, 6,  drogue,   -9.81,  59002.00, 4334.27, 3004.47,  -29.04, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.14, 6,  drogue,   -9.81,  59002.00, 4334.27, 3004.47,  -29.04, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.21, 6,  drogue,   -9.81,  58975.00, 4337.75, 3007.95,  -28.95, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.30, 6,  drogue,   -9.81,  58975.00, 4337.75, 3007.95,  -28.95, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.30, 6,  drogue,   -9.81,  58975.00, 4337.75, 3007.95,  -28.95, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449341,-106.9172831,  4626.0, 2022,  6, 24, 15, 18, 17,      814,     3333, 318,  76,   1.4,   0.8,   1.1,  0, 36, 27,  0,  0, 33,  0,  0,  0,  0, 34, 30, 29, 37,  0,  0, 28,  0, 28, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.31, 6,  drogue,  -10.30,  58963.00, 4339.30, 3009.50,  -28.86, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.41, 6,  drogue,  -11.28,  58931.00, 4343.43, 3013.63,  -28.79, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.46, 6,  drogue,  -11.28,  58931.00, 4343.43, 3013.63,  -28.79, 33.7, 1.52, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.51, 6,  drogue,   -8.34,  58999.00, 4334.66, 3004.86,  -28.71, 33.7, 1.52, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.61, 6,  drogue,   -4.41,  58990.00, 4335.82, 3006.02,  -28.67, 33.7, 1.52, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.71, 6,  drogue,   -9.81,  59020.00, 4331.95, 3002.15,  -28.65, 33.7, 1.52, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.78, 6,  drogue,   -9.81,  59020.00, 4331.95, 3002.15,  -28.65, 33.7, 1.54, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.81, 6,  drogue,  -15.20,  59074.00, 4324.99, 2995.19,  -28.65, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    61.91, 6,  drogue,  -13.73,  59145.00, 4315.84, 2986.04,  -28.66, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.01, 6,  drogue,  -14.22,  59116.00, 4319.58, 2989.78,  -28.65, 33.7, 1.54, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.10, 6,  drogue,  -14.22,  59116.00, 4319.58, 2989.78,  -28.65, 33.7, 1.52, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.11, 6,  drogue,  -13.73,  59157.00, 4314.30, 2984.50,  -28.65, 33.7, 1.52, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.21, 6,  drogue,  -16.18,  59117.00, 4319.45, 2989.65,  -28.75, 33.7, 1.52, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9449832,-106.9172784,  4595.0, 2022,  6, 24, 15, 18, 18,      817,     3304, 318,  76,   1.4,   0.8,   1.1,  0, 27, 27,  0,  0, 38,  0,  0,  0,  0, 33, 31, 28, 37,  0,  0, 30,  0, 29, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.31, 6,  drogue,  -15.20,  59127.00, 4318.16, 2988.36,  -28.90, 33.7, 1.52, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.31, 6,  drogue,  -15.20,  59127.00, 4318.16, 2988.36,  -28.90, 33.7, 1.52, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.31, 6,  drogue,  -15.20,  59127.00, 4318.16, 2988.36,  -28.90, 33.7, 1.52, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.41, 6,  drogue,  -12.75,  59182.00, 4311.08, 2981.28,  -29.08, 33.7, 1.52, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.42, 6,  drogue,  -12.75,  59182.00, 4311.08, 2981.28,  -29.08, 33.7, 1.51, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.51, 6,  drogue,  -13.24,  59213.00, 4307.10, 2977.29,  -29.31, 33.7, 1.51, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.61, 6,  drogue,  -14.22,  59295.00, 4296.56, 2966.75,  -29.56, 33.7, 1.51, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.71, 6,  drogue,  -16.67,  59344.00, 4290.26, 2960.46,  -29.78, 33.7, 1.51, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.74, 6,  drogue,  -16.67,  59344.00, 4290.26, 2960.46,  -29.78, 33.7, 1.53, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.81, 6,  drogue,  -14.71,  59339.00, 4290.91, 2961.10,  -29.93, 33.7, 1.53, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    62.91, 6,  drogue,  -15.69,  59345.00, 4290.13, 2960.33,  -30.04, 33.7, 1.53, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    63.01, 6,  drogue,  -11.28,  59301.00, 4295.78, 2965.98,  -30.18, 33.7, 1.53, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    63.06, 6,  drogue,  -11.28,  59301.00, 4295.78, 2965.98,  -30.18, 33.7, 1.52, 3.99, 3.98,   0.09,   0.00,   0.00,  64.15,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    63.11, 6,  drogue,  -10.30,  59346.00, 4290.01, 2960.21,  -30.31, 33.7, 1.52, 3.99, 3.98,   0.02,   0.00,   0.00,  64.27,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    63.21, 6,  drogue,  -13.24,  59361.00, 4288.08, 2958.28,  -30.39, 33.7, 1.52, 3.99, 3.98,   0.02,   0.00,   0.00,  64.27,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9450449,-106.9172713,  4565.0, 2022,  6, 24, 15, 18, 19,      822,     3276, 318,  75,   1.4,   0.8,   1.1,  0, 37, 33,  0,  0, 34,  0,  0,  0,  0, 33, 27, 29, 25,  0,  0, 38,  0, 37, 27,  0,  0,  0, 31,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    63.31, 6,  drogue,   -9.81,  59381.00, 4285.51, 2955.71,  -30.41, 33.7, 1.52, 3.99, 3.98,   0.02,   0.00,   0.00,  64.27,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.31, 6,  drogue,   -9.81,  59381.00, 4285.51, 2955.71,  -30.41, 33.7, 1.52, 3.99, 3.98,   0.02,   0.00,   0.00,  64.27,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.31, 6,  drogue,   -9.81,  59381.00, 4285.51, 2955.71,  -30.41, 33.7, 1.52, 3.99, 3.98,   0.02,   0.00,   0.00,  64.27,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.38, 6,  drogue,   -9.81,  59381.00, 4285.51, 2955.71,  -30.41, 33.7, 1.52, 3.98, 3.98,   0.02,   0.00,   0.00,  64.27,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.41, 6,  drogue,  -14.22,  59407.00, 4282.18, 2952.38,  -30.35, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.51, 6,  drogue,  -13.73,  59421.00, 4280.38, 2950.58,  -30.29, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.61, 6,  drogue,  -13.24,  59504.00, 4269.75, 2939.94,  -30.13, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.70, 6,  drogue,  -13.24,  59504.00, 4269.75, 2939.94,  -30.13, 33.7, 1.51, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  24.48,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.71, 6,  drogue,  -10.30,  59570.00, 4261.30, 2931.49,  -29.93, 33.7, 1.51, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.81, 6,  drogue,  -12.26,  59585.00, 4259.38, 2929.57,  -29.72, 33.7, 1.51, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    63.91, 6,  drogue,  -10.30,  59570.00, 4261.30, 2931.49,  -29.54, 33.7, 1.51, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    64.01, 6,  drogue,  -14.71,  59536.00, 4265.65, 2935.85,  -29.33, 33.7, 1.51, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    64.02, 6,  drogue,  -14.71,  59536.00, 4265.65, 2935.85,  -29.33, 33.7, 1.50, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    64.11, 6,  drogue,  -18.14,  59568.00, 4261.55, 2931.75,  -29.13, 33.7, 1.50, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    64.21, 6,  drogue,  -10.79,  59651.00, 4250.93, 2921.13,  -28.87, 33.7, 1.50, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9451234,-106.9172674,  4536.0, 2022,  6, 24, 15, 18, 20,      828,     3249, 319,  75,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 38,  0,  0,  0,  0, 40, 28, 33, 35,  0,  0, 33,  0, 30, 25,  0,  0,  0, 29,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,    64.31, 6,  drogue,  -13.24,  59691.00, 4245.82, 2916.02,  -28.60, 33.7, 1.50, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.31, 6,  drogue,  -13.24,  59691.00, 4245.82, 2916.02,  -28.60, 33.7, 1.50, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.31, 6,  drogue,  -13.24,  59691.00, 4245.82, 2916.02,  -28.60, 33.7, 1.50, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.34, 6,  drogue,  -13.24,  59691.00, 4245.82, 2916.02,  -28.60, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  63.91,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.41, 6,  drogue,  -19.61,  59741.00, 4239.44, 2909.64,  -28.28, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.51, 6,  drogue,  -16.67,  59755.00, 4237.65, 2907.85,  -27.95, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.61, 6,  drogue,  -17.65,  59747.00, 4238.67, 2908.87,  -27.65, 33.7, 1.52, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.66, 6,  drogue,  -17.65,  59747.00, 4238.67, 2908.87,  -27.65, 33.7, 1.51, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.71, 6,  drogue,  -18.63,  59700.00, 4244.67, 2914.87,  -27.36, 33.7, 1.51, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.81, 6,  drogue,  -18.14,  59676.00, 4247.74, 2917.94,  -27.06, 33.7, 1.51, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.91, 6,  drogue,  -12.26,  59684.00, 4246.72, 2916.92,  -26.82, 33.7, 1.51, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    64.98, 6,  drogue,  -12.26,  59684.00, 4246.72, 2916.92,  -26.82, 33.7, 1.51, 3.99, 3.99,   0.08,   0.00,   0.00,  64.03,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.01, 6,  drogue,  -11.77,  59808.00, 4230.89, 2901.08,  -26.62, 33.7, 1.51, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.11, 6,  drogue,  -11.28,  59881.00, 4221.58, 2891.78,  -26.51, 33.7, 1.51, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.21, 6,  drogue,  -15.69,  59919.00, 4216.74, 2886.94,  -26.47, 33.7, 1.51, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.30, 6,  drogue,  -15.69,  59919.00, 4216.74, 2886.94,  -26.47, 33.7, 1.50, 3.98, 3.99,   0.09,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452032,-106.9172870,  4506.0, 2022,  6, 24, 15, 18, 21,      836,     3222, 319,  75,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 32, 35, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 33,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.31, 6,  drogue,  -12.75,  59908.00, 4218.14, 2888.34,  -26.53, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.31, 6,  drogue,  -12.75,  59908.00, 4218.14, 2888.34,  -26.53, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.31, 6,  drogue,  -12.75,  59908.00, 4218.14, 2888.34,  -26.53, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.41, 6,  drogue,  -11.77,  59886.00, 4220.94, 2891.14,  -26.64, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.51, 6,  drogue,  -10.30,  59887.00, 4220.81, 2891.01,  -26.83, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.61, 6,  drogue,  -13.24,  59862.00, 4224.00, 2894.20,  -27.09, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.62, 6,  drogue,  -13.24,  59862.00, 4224.00, 2894.20,  -27.09, 33.7, 1.51, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.71, 6,  drogue,  -16.18,  59886.00, 4220.94, 2891.14,  -27.39, 33.7, 1.51, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.81, 6,  drogue,  -13.73,  59929.00, 4215.46, 2885.66,  -27.70, 33.7, 1.51, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.91, 6,  drogue,  -15.69,  60014.00, 4204.64, 2874.84,  -28.03, 33.7, 1.51, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    65.94, 6,  drogue,  -15.69,  60014.00, 4204.64, 2874.84,  -28.03, 33.7, 1.51, 3.99, 3.98,   0.09,   0.00,   0.00,  64.15,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    66.01, 6,  drogue,  -16.67,  60074.00, 4197.01, 2867.21,  -28.35, 33.7, 1.51, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    66.11, 6,  drogue,  -13.24,  60106.00, 4192.95, 2863.15,  -28.72, 33.7, 1.51, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    66.21, 6,  drogue,  -15.69,  60081.00, 4196.12, 2866.32,  -29.14, 33.7, 1.51, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    66.26, 6,  drogue,  -15.69,  60081.00, 4196.12, 2866.32,  -29.14, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9452893,-106.9173296,  4476.0, 2022,  6, 24, 15, 18, 22,      846,     3196, 319,  75,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 34, 31,  0,  0, 34,  0, 29, 24,  0,  0,  0, 30,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    66.31, 6,  drogue,  -14.22,  60079.00, 4196.38, 2866.58,  -29.55, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.31, 6,  drogue,  -14.22,  60079.00, 4196.38, 2866.58,  -29.55, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.31, 6,  drogue,  -14.22,  60079.00, 4196.38, 2866.58,  -29.55, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.41, 6,  drogue,  -13.73,  60004.00, 4205.92, 2876.11,  -29.95, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.51, 6,  drogue,  -15.69,  60028.00, 4202.86, 2873.06,  -30.27, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.58, 6,  drogue,  -15.69,  60028.00, 4202.86, 2873.06,  -30.27, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.61, 6,  drogue,  -13.24,  60072.00, 4197.27, 2867.47,  -30.49, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.71, 6,  drogue,   -8.83,  60115.00, 4191.80, 2862.00,  -30.61, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.81, 6,  drogue,  -10.79,  60174.00, 4184.31, 2854.51,  -30.65, 33.7, 1.50, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.90, 6,  drogue,  -10.79,  60174.00, 4184.31, 2854.51,  -30.65, 33.7, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    66.91, 6,  drogue,  -12.26,  60269.00, 4172.26, 2842.46,  -30.68, 33.7, 1.49, 3.98, 3.99,   0.04,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.01, 6,  drogue,  -15.20,  60316.00, 4166.30, 2836.50,  -30.76, 33.7, 1.49, 3.98, 3.99,   0.04,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.11, 6,  drogue,  -17.65,  60324.00, 4165.29, 2835.49,  -30.82, 33.7, 1.49, 3.98, 3.99,   0.04,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.21, 6,  drogue,  -17.16,  60344.00, 4162.76, 2832.96,  -30.80, 33.7, 1.49, 3.98, 3.99,   0.04,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.22, 6,  drogue,  -17.16,  60344.00, 4162.76, 2832.96,  -30.80, 33.7, 1.49, 3.98, 3.99,   0.04,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9453747,-106.9173672,  4448.0, 2022,  6, 24, 15, 18, 23,      856,     3172, 320,  74,   1.4,   0.8,   1.1,  0, 36, 30,  0,  0, 40,  0,  0,  0,  0, 37, 31, 36, 28,  0,  0, 34,  0, 33, 26,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.31, 6,  drogue,  -16.18,  60377.00, 4158.58, 2828.78,  -30.70, 33.7, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.31, 6,  drogue,  -16.18,  60377.00, 4158.58, 2828.78,  -30.70, 33.7, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.31, 6,  drogue,  -16.18,  60377.00, 4158.58, 2828.78,  -30.70, 33.7, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.41, 6,  drogue,  -18.63,  60353.00, 4161.62, 2831.82,  -30.54, 33.6, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.51, 6,  drogue,  -17.65,  60381.00, 4158.07, 2828.27,  -30.36, 33.6, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.54, 6,  drogue,  -17.65,  60381.00, 4158.07, 2828.27,  -30.36, 33.6, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.61, 6,  drogue,  -18.14,  60364.00, 4160.22, 2830.42,  -30.17, 33.7, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.71, 6,  drogue,  -13.24,  60368.00, 4159.72, 2829.92,  -30.01, 33.7, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.81, 6,  drogue,  -21.57,  60410.00, 4154.40, 2824.60,  -29.86, 33.6, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.86, 6,  drogue,  -21.57,  60410.00, 4154.40, 2824.60,  -29.86, 33.6, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    67.91, 6,  drogue,  -22.06,  60461.00, 4147.95, 2818.15,  -29.75, 33.6, 1.49, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.01, 6,  drogue,  -17.65,  60505.00, 4142.39, 2812.59,  -29.62, 33.6, 1.49, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.11, 6,  drogue,  -17.65,  60533.00, 4138.85, 2809.05,  -29.49, 33.6, 1.49, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.18, 6,  drogue,  -17.65,  60533.00, 4138.85, 2809.05,  -29.49, 33.6, 1.49, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.21, 6,  drogue,  -22.06,  60564.00, 4134.93, 2805.13,  -29.32, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9454545,-106.9173964,  4419.0, 2022,  6, 24, 15, 18, 24,      864,     3146, 320,  74,   1.4,   0.8,   1.1,  0, 34, 30,  0,  0, 40,  0,  0,  0,  0, 36, 31, 33, 32,  0,  0, 35,  0, 34, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.31, 6,  drogue,  -21.08,  60571.00, 4134.05, 2804.25,  -29.15, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.31, 6,  drogue,  -21.08,  60571.00, 4134.05, 2804.25,  -29.15, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.31, 6,  drogue,  -21.08,  60571.00, 4134.05, 2804.25,  -29.15, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.41, 6,  drogue,  -19.61,  60602.00, 4130.14, 2800.34,  -28.95, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.50, 6,  drogue,  -19.61,  60602.00, 4130.14, 2800.34,  -28.95, 33.6, 1.49, 3.99, 3.98,   0.03,   0.00,   0.00,  64.03,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.51, 6,  drogue,  -19.61,  60583.00, 4132.54, 2802.73,  -28.78, 33.7, 1.49, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.61, 6,  drogue,  -17.65,  60584.00, 4132.41, 2802.61,  -28.66, 33.7, 1.49, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.71, 6,  drogue,  -17.16,  60613.00, 4128.75, 2798.95,  -28.57, 33.7, 1.49, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.81, 6,  drogue,  -15.69,  60630.00, 4126.60, 2796.80,  -28.50, 33.6, 1.49, 3.99, 3.98,   0.03,   0.00,   0.00,  64.27,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.82, 6,  drogue,  -15.69,  60630.00, 4126.60, 2796.80,  -28.50, 33.6, 1.48, 3.96, 3.98,   0.03,   0.00,   0.00,  64.27,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    68.91, 6,  drogue,  -17.16,  60699.00, 4117.90, 2788.10,  -28.45, 33.7, 1.48, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.01, 6,  drogue,  -19.61,  60749.00, 4111.60, 2781.80,  -28.39, 33.6, 1.48, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.11, 6,  drogue,  -20.10,  60768.00, 4109.21, 2779.41,  -28.32, 33.6, 1.48, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.14, 6,  drogue,  -20.10,  60768.00, 4109.21, 2779.41,  -28.32, 33.6, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.21, 6,  drogue,  -17.65,  60771.00, 4108.83, 2779.03,  -28.23, 33.6, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.31, 6,  drogue,  -19.61,  60796.00, 4105.68, 2775.88,  -28.15, 33.6, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.31, 6,  drogue,  -19.61,  60796.00, 4105.68, 2775.88,  -28.15, 33.6, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.31, 6,  drogue,  -19.61,  60796.00, 4105.68, 2775.88,  -28.15, 33.6, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9455288,-106.9174243,  4389.0, 2022,  6, 24, 15, 18, 25,      872,     3119, 320,  74,   1.4,   0.8,   1.1,  0, 38, 30,  0,  0, 37,  0,  0,  0,  0, 37, 25, 29, 29,  0,  0, 33,  0, 36, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    69.41, 6,  drogue,  -19.61,  60824.00, 4102.16, 2772.36,  -28.07, 33.7, 1.49, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.46, 6,  drogue,  -19.61,  60824.00, 4102.16, 2772.36,  -28.07, 33.7, 1.48, 3.97, 3.97,   0.02,   0.00,   0.00,  64.03,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.51, 6,  drogue,  -18.63,  60855.00, 4098.26, 2768.46,  -28.01, 33.6, 1.48, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.61, 6,  drogue,  -18.63,  60890.00, 4093.86, 2764.06,  -27.97, 33.6, 1.48, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.71, 6,  drogue,  -18.63,  60912.00, 4091.09, 2761.29,  -27.97, 33.6, 1.48, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.78, 6,  drogue,  -18.63,  60912.00, 4091.09, 2761.29,  -27.97, 33.6, 1.49, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.81, 6,  drogue,  -20.59,  60888.00, 4094.11, 2764.31,  -28.00, 33.6, 1.49, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    69.91, 6,  drogue,  -17.65,  60896.00, 4093.10, 2763.30,  -28.06, 33.6, 1.49, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    70.01, 6,  drogue,  -17.65,  60878.00, 4095.37, 2765.57,  -28.13, 33.6, 1.49, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    70.10, 6,  drogue,  -17.65,  60878.00, 4095.37, 2765.57,  -28.13, 33.6, 1.49, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  24.05,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    70.11, 6,  drogue,  -20.59,  60929.00, 4088.96, 2759.15,  -28.16, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    70.21, 6,  drogue,  -18.63,  60955.00, 4085.69, 2755.89,  -28.18, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9455871,-106.9174426,  4359.0, 2022,  6, 24, 15, 18, 26,      878,     3092, 320,  74,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 37,  0,  0,  0,  0, 35, 25, 34, 28,  0,  0, 38,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    70.31, 6,  drogue,  -17.65,  60997.00, 4080.41, 2750.61,  -28.25, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.31, 6,  drogue,  -17.65,  60997.00, 4080.41, 2750.61,  -28.25, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.31, 6,  drogue,  -17.65,  60997.00, 4080.41, 2750.61,  -28.25, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.41, 6,  drogue,  -14.71,  61034.00, 4075.77, 2745.97,  -28.33, 33.6, 1.49, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.42, 6,  drogue,  -14.71,  61034.00, 4075.77, 2745.97,  -28.33, 33.6, 1.48, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.99,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.51, 6,  drogue,  -18.63,  61048.00, 4074.01, 2744.21,  -28.37, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.61, 6,  drogue,  -21.08,  61082.00, 4069.75, 2739.95,  -28.40, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.71, 6,  drogue,  -16.67,  61104.00, 4066.99, 2737.19,  -28.40, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.74, 6,  drogue,  -16.67,  61104.00, 4066.99, 2737.19,  -28.40, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.81, 6,  drogue,  -15.69,  61117.00, 4065.36, 2735.56,  -28.38, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    70.91, 6,  drogue,  -18.14,  61133.00, 4063.36, 2733.55,  -28.41, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    71.01, 6,  drogue,  -19.12,  61154.00, 4060.72, 2730.92,  -28.44, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    71.06, 6,  drogue,  -19.12,  61154.00, 4060.72, 2730.92,  -28.44, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    71.11, 6,  drogue,  -18.14,  61215.00, 4053.08, 2723.28,  -28.47, 33.6, 1.48, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    71.21, 6,  drogue,  -15.20,  61228.00, 4051.46, 2721.66,  -28.50, 33.6, 1.48, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9456358,-106.9174372,  4328.0, 2022,  6, 24, 15, 18, 27,      882,     3064, 321,  73,   1.4,   0.8,   1.1,  0, 39, 30,  0,  0, 35,  0,  0,  0,  0, 37, 31, 31, 28,  0,  0, 35,  0, 38, 31,  0,  0,  0, 33,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    71.31, 6,  drogue,  -16.18,  61252.00, 4048.45, 2718.65,  -28.56, 33.6, 1.48, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.31, 6,  drogue,  -16.18,  61252.00, 4048.45, 2718.65,  -28.56, 33.6, 1.48, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.31, 6,  drogue,  -16.18,  61252.00, 4048.45, 2718.65,  -28.56, 33.6, 1.48, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.38, 6,  drogue,  -16.18,  61252.00, 4048.45, 2718.65,  -28.56, 33.6, 1.47, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.41, 6,  drogue,  -19.12,  61293.00, 4043.32, 2713.52,  -28.63, 33.6, 1.47, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.51, 6,  drogue,  -18.14,  61295.00, 4043.07, 2713.27,  -28.74, 33.6, 1.47, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.61, 6,  drogue,  -16.18,  61325.00, 4039.32, 2709.52,  -28.90, 33.6, 1.47, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.70, 6,  drogue,  -16.18,  61325.00, 4039.32, 2709.52,  -28.90, 33.6, 1.48, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.71, 6,  drogue,  -16.18,  61348.00, 4036.45, 2706.65,  -29.08, 33.6, 1.48, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.81, 6,  drogue,  -13.73,  61333.00, 4038.32, 2708.52,  -29.25, 33.6, 1.48, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    71.91, 6,  drogue,  -16.67,  61339.00, 4037.57, 2707.77,  -29.44, 33.6, 1.48, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    72.01, 6,  drogue,  -20.59,  61351.00, 4036.07, 2706.27,  -29.65, 33.6, 1.48, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    72.02, 6,  drogue,  -20.59,  61351.00, 4036.07, 2706.27,  -29.65, 33.6, 1.47, 3.99, 3.99,   0.03,   0.00,   0.00,  64.15,  23.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    72.11, 6,  drogue,  -18.14,  61334.00, 4038.20, 2708.40,  -29.91, 33.6, 1.47, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    72.21, 6,  drogue,  -19.61,  61377.00, 4032.83, 2703.02,  -30.20, 33.6, 1.47, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457026,-106.9174020,  4297.0, 2022,  6, 24, 15, 18, 28,      886,     3035, 321,  73,   1.4,   0.8,   1.1,  0, 29, 32,  0,  0, 39,  0,  0,  0,  0, 32, 27, 24, 37,  0,  0, 37,  0, 35, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    72.31, 6,  drogue,  -18.14,  61492.00, 4018.47, 2688.67,  -30.49, 33.6, 1.47, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.31, 6,  drogue,  -18.14,  61492.00, 4018.47, 2688.67,  -30.49, 33.6, 1.47, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.31, 6,  drogue,  -18.14,  61492.00, 4018.47, 2688.67,  -30.49, 33.6, 1.47, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.34, 6,  drogue,  -18.14,  61492.00, 4018.47, 2688.67,  -30.49, 33.6, 1.47, 3.98, 3.99,   0.03,   0.00,   0.00,  64.27,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.41, 6,  drogue,  -22.06,  61530.00, 4013.73, 2683.93,  -30.79, 33.6, 1.47, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.51, 6,  drogue,  -15.69,  61534.00, 4013.23, 2683.43,  -31.05, 33.6, 1.47, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.61, 6,  drogue,  -19.61,  61561.00, 4009.87, 2680.07,  -31.25, 33.6, 1.47, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.66, 6,  drogue,  -19.61,  61561.00, 4009.87, 2680.07,  -31.25, 33.6, 1.47, 3.97, 3.98,   0.03,   0.00,   0.00,  64.15,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.71, 6,  drogue,  -18.14,  61527.00, 4014.11, 2684.31,  -31.39, 33.6, 1.47, 3.97, 3.98,   0.03,   0.00,   0.00,  63.97,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.81, 6,  drogue,  -16.67,  61542.00, 4012.24, 2682.44,  -31.45, 33.6, 1.47, 3.97, 3.98,   0.03,   0.00,   0.00,  63.97,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.91, 6,  drogue,  -17.16,  61618.00, 4002.77, 2672.97,  -31.47, 33.6, 1.47, 3.97, 3.98,   0.03,   0.00,   0.00,  63.97,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    72.98, 6,  drogue,  -17.16,  61618.00, 4002.77, 2672.97,  -31.47, 33.6, 1.47, 3.98, 3.99,   0.03,   0.00,   0.00,  63.97,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    73.01, 6,  drogue,  -18.63,  61636.00, 4000.53, 2670.73,  -31.43, 33.6, 1.47, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    73.11, 6,  drogue,  -16.67,  61692.00, 3993.56, 2663.76,  -31.35, 33.6, 1.47, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    73.21, 6,  drogue,  -17.16,  61720.00, 3990.07, 2660.27,  -31.19, 33.6, 1.47, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    73.30, 6,  drogue,  -17.16,  61720.00, 3990.07, 2660.27,  -31.19, 33.6, 1.47, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.68,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9457737,-106.9173709,  4266.0, 2022,  6, 24, 15, 18, 29,      890,     3007, 321,  73,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 39,  0,  0,  0,  0, 36, 28, 33, 35,  0,  0, 37,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    73.31, 6,  drogue,  -17.16,  61747.00, 3986.72, 2656.92,  -30.97, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.31, 6,  drogue,  -17.16,  61747.00, 3986.72, 2656.92,  -30.97, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.31, 6,  drogue,  -17.16,  61747.00, 3986.72, 2656.92,  -30.97, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.41, 6,  drogue,  -18.63,  61763.00, 3984.73, 2654.93,  -30.69, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.51, 6,  drogue,  -17.16,  61784.00, 3982.12, 2652.32,  -30.38, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.61, 6,  drogue,  -18.63,  61820.00, 3977.65, 2647.85,  -30.06, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.62, 6,  drogue,  -18.63,  61820.00, 3977.65, 2647.85,  -30.06, 33.6, 1.47, 3.97, 3.97,   0.00,   0.00,   0.00,  64.15,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.71, 6,  drogue,  -19.12,  61834.00, 3975.91, 2646.11,  -29.77, 33.6, 1.47, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.81, 6,  drogue,  -19.61,  61831.00, 3976.28, 2646.48,  -29.48, 33.6, 1.47, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.91, 6,  drogue,  -19.61,  61846.00, 3974.42, 2644.62,  -29.20, 33.6, 1.47, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    73.94, 6,  drogue,  -19.61,  61846.00, 3974.42, 2644.62,  -29.20, 33.6, 1.46, 3.96, 3.97,   0.00,   0.00,   0.00,  63.97,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    74.01, 6,  drogue,  -18.63,  61887.00, 3969.33, 2639.53,  -28.96, 33.6, 1.46, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    74.11, 6,  drogue,  -21.08,  61911.00, 3966.35, 2636.55,  -28.77, 33.6, 1.46, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    74.21, 6,  drogue,  -18.63,  61949.00, 3961.64, 2631.84,  -28.64, 33.6, 1.46, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    74.26, 6,  drogue,  -18.63,  61949.00, 3961.64, 2631.84,  -28.64, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  63.78,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9458482,-106.9173613,  4235.0, 2022,  6, 24, 15, 18, 30,      896,     2979, 322,  72,   1.4,   0.8,   1.1,  0, 36, 31,  0,  0, 37,  0,  0,  0,  0, 36, 29, 29, 33,  0,  0, 32,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    74.31, 6,  drogue,  -18.14,  61959.00, 3960.40, 2630.60,  -28.63, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.31, 6,  drogue,  -18.14,  61959.00, 3960.40, 2630.60,  -28.63, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.31, 6,  drogue,  -18.14,  61959.00, 3960.40, 2630.60,  -28.63, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.41, 6,  drogue,  -21.08,  62001.00, 3955.19, 2625.39,  -28.67, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.51, 6,  drogue,  -19.61,  62018.00, 3953.09, 2623.29,  -28.72, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.58, 6,  drogue,  -19.61,  62018.00, 3953.09, 2623.29,  -28.72, 33.6, 1.47, 3.98, 3.99,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.61, 6,  drogue,  -19.12,  62014.00, 3953.58, 2623.78,  -28.81, 33.6, 1.47, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.71, 6,  drogue,  -17.65,  62021.00, 3952.72, 2622.92,  -28.91, 33.6, 1.47, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.81, 6,  drogue,  -14.71,  62046.00, 3949.62, 2619.82,  -29.05, 33.6, 1.47, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.90, 6,  drogue,  -14.71,  62046.00, 3949.62, 2619.82,  -29.05, 33.6, 1.47, 3.99, 3.99,   0.09,   0.00,   0.00,  64.09,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    74.91, 6,  drogue,  -14.71,  62107.00, 3942.07, 2612.27,  -29.24, 33.6, 1.47, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    75.01, 6,  drogue,  -20.10,  62127.00, 3939.60, 2609.79,  -29.42, 33.6, 1.47, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    75.11, 6,  drogue,  -16.67,  62137.00, 3938.36, 2608.56,  -29.61, 33.6, 1.47, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    75.21, 6,  drogue,  -14.71,  62148.00, 3937.00, 2607.20,  -29.75, 33.6, 1.47, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    75.22, 6,  drogue,  -14.71,  62148.00, 3937.00, 2607.20,  -29.75, 33.6, 1.46, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  23.62,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9459316,-106.9173698,  4204.0, 2022,  6, 24, 15, 18, 31,      904,     2952, 322,  72,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 38, 31, 33, 36,  0,  0, 33,  0, 31, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    75.31, 6,  drogue,  -16.67,  62173.00, 3933.91, 2604.11,  -29.82, 33.6, 1.46, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.31, 6,  drogue,  -16.67,  62173.00, 3933.91, 2604.11,  -29.82, 33.6, 1.46, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.31, 6,  drogue,  -16.67,  62173.00, 3933.91, 2604.11,  -29.82, 33.6, 1.46, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.41, 6,  drogue,  -18.14,  62171.00, 3934.15, 2604.35,  -29.88, 33.6, 1.46, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.51, 6,  drogue,  -16.67,  62232.00, 3926.62, 2596.82,  -29.90, 33.6, 1.46, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.54, 6,  drogue,  -16.67,  62232.00, 3926.62, 2596.82,  -29.90, 33.6, 1.46, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.61, 6,  drogue,  -14.71,  62266.00, 3922.42, 2592.62,  -29.87, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.71, 6,  drogue,  -16.67,  62323.00, 3915.38, 2585.58,  -29.80, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.81, 6,  drogue,  -15.20,  62349.00, 3912.17, 2582.37,  -29.68, 33.6, 1.46, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.86, 6,  drogue,  -15.20,  62349.00, 3912.17, 2582.37,  -29.68, 33.6, 1.46, 3.98, 3.99,   0.00,   0.00,   0.00,  64.27,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    75.91, 6,  drogue,  -16.18,  62337.00, 3913.65, 2583.85,  -29.56, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    76.01, 6,  drogue,  -16.67,  62370.00, 3909.58, 2579.78,  -29.44, 33.6, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    76.11, 6,  drogue,  -19.61,  62398.00, 3906.13, 2576.33,  -29.32, 33.6, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    76.18, 6,  drogue,  -19.61,  62398.00, 3906.13, 2576.33,  -29.32, 33.6, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    76.21, 6,  drogue,  -19.61,  62404.00, 3905.39, 2575.59,  -29.19, 33.6, 1.45, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9460126,-106.9173806,  4174.0, 2022,  6, 24, 15, 18, 32,      912,     2926, 322,  72,   1.4,   0.8,   1.1,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 33, 26, 36, 33,  0,  0, 33,  0, 31, 33,  0,  0,  0, 25,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,    76.31, 6,  drogue,  -20.10,  62440.00, 3900.96, 2571.16,  -29.05, 33.6, 1.45, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.31, 6,  drogue,  -20.10,  62440.00, 3900.96, 2571.16,  -29.05, 33.6, 1.45, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.31, 6,  drogue,  -20.10,  62440.00, 3900.96, 2571.16,  -29.05, 33.6, 1.45, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.41, 6,  drogue,  -19.61,  62460.00, 3898.49, 2568.69,  -28.94, 33.5, 1.45, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.50, 6,  drogue,  -19.61,  62460.00, 3898.49, 2568.69,  -28.94, 33.5, 1.45, 3.96, 3.97,   0.08,   0.00,   0.00,  64.15,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.51, 6,  drogue,  -21.08,  62487.00, 3895.17, 2565.37,  -28.79, 33.6, 1.45, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.61, 6,  drogue,  -23.05,  62514.00, 3891.84, 2562.04,  -28.61, 33.6, 1.45, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.71, 6,  drogue,  -18.14,  62557.00, 3886.55, 2556.75,  -28.44, 33.6, 1.45, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.81, 6,  drogue,  -20.59,  62567.00, 3885.32, 2555.52,  -28.30, 33.6, 1.45, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.82, 6,  drogue,  -20.59,  62567.00, 3885.32, 2555.52,  -28.30, 33.6, 1.46, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    76.91, 6,  drogue,  -19.12,  62583.00, 3883.36, 2553.56,  -28.22, 33.6, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    77.01, 6,  drogue,  -18.63,  62584.00, 3883.23, 2553.43,  -28.19, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    77.11, 6,  drogue,  -16.67,  62604.00, 3880.77, 2550.97,  -28.17, 33.6, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    77.14, 6,  drogue,  -16.67,  62604.00, 3880.77, 2550.97,  -28.17, 33.6, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    77.21, 6,  drogue,  -20.59,  62603.00, 3880.90, 2551.10,  -28.17, 33.6, 1.46, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9460889,-106.9173796,  4143.0, 2022,  6, 24, 15, 18, 33,      918,     2898, 323,  72,   1.4,   0.8,   1.1,  0, 37, 34,  0,  0, 35,  0,  0,  0,  0, 37, 31, 28, 37,  0,  0, 35,  0, 32, 28,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,    77.31, 6,  drogue,  -16.18,  62599.00, 3881.39, 2551.59,  -28.20, 33.6, 1.46, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.31, 6,  drogue,  -16.18,  62599.00, 3881.39, 2551.59,  -28.20, 33.6, 1.46, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.31, 6,  drogue,  -16.18,  62599.00, 3881.39, 2551.59,  -28.20, 33.6, 1.46, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.41, 6,  drogue,  -15.69,  62691.00, 3870.09, 2540.28,  -28.25, 33.5, 1.46, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.46, 6,  drogue,  -15.69,  62691.00, 3870.09, 2540.28,  -28.25, 33.5, 1.46, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.51, 6,  drogue,  -21.08,  62707.00, 3868.12, 2538.32,  -28.32, 33.5, 1.46, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.61, 6,  drogue,  -21.08,  62718.00, 3866.77, 2536.97,  -28.43, 33.5, 1.46, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.71, 6,  drogue,  -16.67,  62762.00, 3861.37, 2531.57,  -28.55, 33.5, 1.46, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.78, 6,  drogue,  -16.67,  62762.00, 3861.37, 2531.57,  -28.55, 33.5, 1.46, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.56,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.81, 6,  drogue,  -16.67,  62797.00, 3857.08, 2527.28,  -28.67, 33.5, 1.46, 3.98, 3.99,   0.01,   0.00,   0.00,  64.15,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    77.91, 6,  drogue,  -17.65,  62835.00, 3852.42, 2522.62,  -28.73, 33.5, 1.46, 3.98, 3.99,   0.01,   0.00,   0.00,  64.15,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    78.01, 6,  drogue,  -14.22,  62855.00, 3849.97, 2520.17,  -28.78, 33.5, 1.46, 3.98, 3.99,   0.01,   0.00,   0.00,  64.15,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    78.10, 6,  drogue,  -14.22,  62855.00, 3849.97, 2520.17,  -28.78, 33.5, 1.46, 3.98, 3.99,   0.01,   0.00,   0.00,  64.15,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    78.11, 6,  drogue,  -19.12,  62890.00, 3845.68, 2515.88,  -28.82, 33.5, 1.46, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    78.21, 6,  drogue,  -19.61,  62882.00, 3846.66, 2516.86,  -28.85, 33.5, 1.46, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9461640,-106.9173644,  4112.0, 2022,  6, 24, 15, 18, 34,      924,     2871, 323,  71,   1.4,   0.8,   1.1,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 38, 35, 28, 35,  0,  0, 32,  0, 27, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    78.31, 6,  drogue,  -23.54,  62899.00, 3844.58, 2514.78,  -28.89, 33.5, 1.46, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.31, 6,  drogue,  -23.54,  62899.00, 3844.58, 2514.78,  -28.89, 33.5, 1.46, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.31, 6,  drogue,  -23.54,  62899.00, 3844.58, 2514.78,  -28.89, 33.5, 1.46, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.41, 6,  drogue,  -16.67,  62925.00, 3841.39, 2511.59,  -28.92, 33.5, 1.46, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.42, 6,  drogue,  -16.67,  62925.00, 3841.39, 2511.59,  -28.92, 33.5, 1.46, 3.99, 3.99,   0.03,   0.00,   0.00,  64.09,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.51, 6,  drogue,  -16.67,  62904.00, 3843.97, 2514.16,  -28.94, 33.5, 1.46, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.61, 6,  drogue,  -20.10,  62902.00, 3844.21, 2514.41,  -28.95, 33.5, 1.46, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.71, 6,  drogue,  -17.16,  62941.00, 3839.44, 2509.63,  -28.87, 33.5, 1.46, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.74, 6,  drogue,  -17.16,  62941.00, 3839.44, 2509.63,  -28.87, 33.5, 1.44, 3.97, 3.97,   0.09,   0.00,   0.00,  64.21,  23.50,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.81, 6,  drogue,  -17.16,  62986.00, 3833.93, 2504.13,  -28.72, 33.5, 1.44, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    78.91, 6,  drogue,  -16.67,  63047.00, 3826.47, 2496.67,  -28.51, 33.5, 1.44, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    79.01, 6,  drogue,  -14.71,  63093.00, 3820.85, 2491.05,  -28.25, 33.5, 1.44, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    79.06, 6,  drogue,  -14.71,  63093.00, 3820.85, 2491.05,  -28.25, 33.5, 1.44, 3.96, 3.97,   0.00,   0.00,   0.00,  63.91,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    79.11, 6,  drogue,  -14.71,  63121.00, 3817.43, 2487.63,  -27.96, 33.5, 1.44, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    79.21, 6,  drogue,  -15.69,  63136.00, 3815.60, 2485.80,  -27.63, 33.5, 1.44, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9462477,-106.9173375,  4081.0, 2022,  6, 24, 15, 18, 35,      930,     2843, 324,  71,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 36,  0,  0,  0,  0, 35, 29, 29, 36,  0,  0, 37,  0, 38, 23,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    79.31, 6,  drogue,  -18.63,  63160.00, 3812.67, 2482.87,  -27.28, 33.5, 1.44, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.31, 6,  drogue,  -18.63,  63160.00, 3812.67, 2482.87,  -27.28, 33.5, 1.44, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.31, 6,  drogue,  -18.63,  63160.00, 3812.67, 2482.87,  -27.28, 33.5, 1.44, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.38, 6,  drogue,  -18.63,  63160.00, 3812.67, 2482.87,  -27.28, 33.5, 1.44, 3.98, 3.98,   0.00,   0.00,   0.00,  63.72,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.41, 6,  drogue,  -17.16,  63176.00, 3810.72, 2480.91,  -27.00, 33.5, 1.44, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.51, 6,  drogue,  -19.12,  63175.00, 3810.84, 2481.04,  -26.71, 33.5, 1.44, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.61, 6,  drogue,  -19.61,  63219.00, 3805.47, 2475.67,  -26.42, 33.5, 1.44, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.70, 6,  drogue,  -19.61,  63219.00, 3805.47, 2475.67,  -26.42, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.71, 6,  drogue,  -18.63,  63230.00, 3804.13, 2474.33,  -26.19, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.81, 6,  drogue,  -22.06,  63257.00, 3800.84, 2471.03,  -26.03, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    79.91, 6,  drogue,  -19.61,  63242.00, 3802.66, 2472.86,  -25.88, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.01, 6,  drogue,  -17.65,  63262.00, 3800.23, 2470.43,  -25.73, 33.5, 1.46, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.02, 6,  drogue,  -17.65,  63262.00, 3800.23, 2470.43,  -25.73, 33.5, 1.45, 3.97, 3.99,   0.02,   0.00,   0.00,  64.15,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.11, 6,  drogue,  -15.20,  63293.00, 3796.45, 2466.65,  -25.62, 33.5, 1.45, 3.97, 3.99,   0.09,   0.00,   0.00,  63.97,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.21, 6,  drogue,  -18.63,  63341.00, 3790.60, 2460.80,  -25.51, 33.5, 1.45, 3.97, 3.99,   0.09,   0.00,   0.00,  63.97,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.31, 6,  drogue,  -22.06,  63380.00, 3785.85, 2456.05,  -25.44, 33.5, 1.45, 3.97, 3.99,   0.09,   0.00,   0.00,  63.97,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.31, 6,  drogue,  -22.06,  63380.00, 3785.85, 2456.05,  -25.44, 33.5, 1.45, 3.97, 3.99,   0.09,   0.00,   0.00,  63.97,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.31, 6,  drogue,  -22.06,  63380.00, 3785.85, 2456.05,  -25.44, 33.5, 1.45, 3.97, 3.99,   0.09,   0.00,   0.00,  63.97,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9463305,-106.9173102,  4052.0, 2022,  6, 24, 15, 18, 36,      936,     2818, 324,  71,   1.4,   0.8,   1.1,  0, 27, 30,  0,  0, 38,  0,  0,  0,  0, 31, 30, 27, 36,  0,  0, 37,  0, 37, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    80.34, 6,  drogue,  -22.06,  63380.00, 3785.85, 2456.05,  -25.44, 33.5, 1.45, 3.98, 3.99,   0.09,   0.00,   0.00,  63.97,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.41, 6,  drogue,  -20.10,  63409.00, 3782.32, 2452.52,  -25.43, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.51, 6,  drogue,  -18.14,  63424.00, 3780.50, 2450.70,  -25.48, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.61, 6,  drogue,  -18.63,  63446.00, 3777.82, 2448.02,  -25.61, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.66, 6,  drogue,  -18.63,  63446.00, 3777.82, 2448.02,  -25.61, 33.5, 1.45, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  23.38,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.71, 6,  drogue,  -21.57,  63360.00, 3788.29, 2458.49,  -25.81, 33.5, 1.45, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.81, 6,  drogue,  -16.67,  63380.00, 3785.85, 2456.05,  -26.05, 33.5, 1.45, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.91, 6,  drogue,  -13.24,  63401.00, 3783.30, 2453.50,  -26.36, 33.5, 1.45, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    80.98, 6,  drogue,  -13.24,  63401.00, 3783.30, 2453.50,  -26.36, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    81.01, 6,  drogue,   -8.34,  63441.00, 3778.43, 2448.63,  -26.68, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    81.11, 6,  drogue,  -11.77,  63477.00, 3774.05, 2444.25,  -26.97, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    81.21, 6,  drogue,  -11.77,  63523.00, 3768.46, 2438.66,  -27.17, 33.5, 1.45, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    81.30, 6,  drogue,  -11.77,  63523.00, 3768.46, 2438.66,  -27.17, 33.5, 1.44, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  23.32,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464055,-106.9172919,  4020.0, 2022,  6, 24, 15, 18, 37,      942,     2790, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 32,  0,  0,  0,  0, 30, 37, 28, 29,  0,  0, 38,  0, 35, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    81.31, 6,  drogue,   -8.83,  63564.00, 3763.48, 2433.68,  -27.35, 33.5, 1.44, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.31, 6,  drogue,   -8.83,  63564.00, 3763.48, 2433.68,  -27.35, 33.5, 1.44, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.31, 6,  drogue,   -8.83,  63564.00, 3763.48, 2433.68,  -27.35, 33.5, 1.44, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.41, 6,  drogue,  -13.73,  63624.00, 3756.20, 2426.40,  -27.53, 33.5, 1.44, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.51, 6,  drogue,  -13.24,  63641.00, 3754.14, 2424.34,  -27.67, 33.5, 1.44, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.61, 6,  drogue,  -14.71,  63654.00, 3752.56, 2422.76,  -27.77, 33.5, 1.44, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.62, 6,  drogue,  -14.71,  63654.00, 3752.56, 2422.76,  -27.77, 33.5, 1.44, 3.99, 3.99,   0.00,   0.00,   0.00,  64.15,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.71, 6,  drogue,  -16.18,  63707.00, 3746.14, 2416.33,  -27.82, 33.5, 1.44, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.81, 6,  drogue,  -10.79,  63746.00, 3741.41, 2411.61,  -27.77, 33.5, 1.44, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.91, 6,  drogue,  -13.73,  63703.00, 3746.62, 2416.82,  -27.64, 33.5, 1.44, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    81.94, 6,  drogue,  -13.73,  63703.00, 3746.62, 2416.82,  -27.64, 33.5, 1.43, 3.98, 3.99,   0.03,   0.00,   0.00,  64.21,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    82.01, 6,  drogue,  -10.30,  63686.00, 3748.68, 2418.88,  -27.55, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.07,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    82.11, 6,  drogue,  -10.30,  63685.00, 3748.80, 2419.00,  -27.50, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.07,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    82.21, 6,  drogue,   -8.83,  63706.00, 3746.26, 2416.46,  -27.49, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.07,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    82.26, 6,  drogue,   -8.83,  63706.00, 3746.26, 2416.46,  -27.49, 33.5, 1.43, 3.99, 3.99,   0.02,   0.00,   0.00,  64.15,  23.07,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9464625,-106.9172840,  3990.0, 2022,  6, 24, 15, 18, 38,      946,     2763, 325,  70,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 39,  0,  0,  0,  0, 36, 31, 30, 32,  0,  0, 35,  0, 36, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    82.31, 6,  drogue,   -6.86,  63734.00, 3742.86, 2413.06,  -27.47, 33.5, 1.43, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.31, 6,  drogue,   -6.86,  63734.00, 3742.86, 2413.06,  -27.47, 33.5, 1.43, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.31, 6,  drogue,   -6.86,  63734.00, 3742.86, 2413.06,  -27.47, 33.5, 1.43, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.41, 6,  drogue,   -6.86,  63775.00, 3737.90, 2408.10,  -27.34, 33.5, 1.43, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.51, 6,  drogue,   -7.85,  63866.00, 3726.88, 2397.08,  -27.19, 33.5, 1.43, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.58, 6,  drogue,   -7.85,  63866.00, 3726.88, 2397.08,  -27.19, 33.5, 1.43, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.61, 6,  drogue,  -12.75,  63914.00, 3721.08, 2391.28,  -27.01, 33.5, 1.43, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.71, 6,  drogue,  -14.71,  63924.00, 3719.87, 2390.07,  -26.73, 33.5, 1.43, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.81, 6,  drogue,  -13.73,  63929.00, 3719.27, 2389.46,  -26.44, 33.5, 1.43, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.90, 6,  drogue,  -13.73,  63929.00, 3719.27, 2389.46,  -26.44, 33.5, 1.42, 3.98, 4.00,   0.00,   0.00,   0.00,  64.21,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    82.91, 6,  drogue,  -12.75,  63968.00, 3714.55, 2384.75,  -26.23, 33.5, 1.42, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    83.01, 6,  drogue,   -6.37,  63967.00, 3714.67, 2384.87,  -26.07, 33.5, 1.42, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    83.11, 6,  drogue,   -6.37,  63964.00, 3715.04, 2385.24,  -25.92, 33.5, 1.42, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    83.21, 6,  drogue,   -7.35,  63917.00, 3720.72, 2390.92,  -25.83, 33.5, 1.42, 3.98, 4.00,   0.02,   0.00,   0.00,  64.03,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    83.22, 6,  drogue,   -7.35,  63917.00, 3720.72, 2390.92,  -25.83, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465084,-106.9172730,  3960.0, 2022,  6, 24, 15, 18, 39,      950,     2736, 325,  70,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 35,  0,  0,  0,  0, 32, 31, 30, 35,  0,  0, 37,  0, 36, 26,  0,  0,  0, 27,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,    83.31, 6,  drogue,   -3.43,  63961.00, 3715.40, 2385.60,  -25.76, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.31, 6,  drogue,   -3.43,  63961.00, 3715.40, 2385.60,  -25.76, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.31, 6,  drogue,   -3.43,  63961.00, 3715.40, 2385.60,  -25.76, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.41, 6,  drogue,    9.32,  64057.00, 3703.81, 2374.01,  -25.78, 33.5, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.51, 6,  drogue,   21.08,  64087.00, 3700.19, 2370.39,  -25.85, 33.4, 1.43, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.54, 6,  drogue,   21.08,  64087.00, 3700.19, 2370.39,  -25.85, 33.4, 1.42, 3.96, 3.98,   0.02,   0.00,   0.00,  64.15,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.61, 6,  drogue,    1.96,  64071.00, 3702.12, 2372.32,  -25.98, 33.5, 1.42, 3.96, 3.98,   0.01,   0.00,   0.00,  63.78,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.71, 6,  drogue,  -11.28,  64088.00, 3700.07, 2370.27,  -26.19, 33.4, 1.42, 3.96, 3.98,   0.01,   0.00,   0.00,  63.78,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.81, 6,  drogue,   -7.35,  64040.00, 3705.86, 2376.06,  -26.48, 33.5, 1.42, 3.96, 3.98,   0.01,   0.00,   0.00,  63.78,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.86, 6,  drogue,   -7.35,  64040.00, 3705.86, 2376.06,  -26.48, 33.5, 1.42, 3.96, 3.97,   0.01,   0.00,   0.00,  63.78,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    83.91, 6,  drogue,    0.49,  64070.00, 3702.24, 2372.44,  -26.81, 33.4, 1.42, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    84.01, 6,  drogue,   -6.86,  64197.00, 3686.93, 2357.13,  -27.19, 33.5, 1.42, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    84.11, 6,  drogue,  -16.18,  64282.00, 3676.69, 2346.89,  -27.63, 33.5, 1.42, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    84.18, 6,  drogue,  -16.18,  64282.00, 3676.69, 2346.89,  -27.63, 33.5, 1.41, 3.98, 3.99,   0.00,   0.00,   0.00,  63.78,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    84.21, 6,  drogue,  -17.16,  64312.00, 3673.09, 2343.28,  -28.17, 33.4, 1.41, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9465624,-106.9172535,  3929.0, 2022,  6, 24, 15, 18, 40,      954,     2709, 325,  69,   1.4,   0.8,   1.1,  0, 32, 30,  0,  0, 37,  0,  0,  0,  0, 28, 32, 30, 37,  0,  0, 37,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    84.31, 6,  drogue,  -16.18,  64281.00, 3676.81, 2347.01,  -28.78, 33.5, 1.41, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.31, 6,  drogue,  -16.18,  64281.00, 3676.81, 2347.01,  -28.78, 33.5, 1.41, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.31, 6,  drogue,  -16.18,  64281.00, 3676.81, 2347.01,  -28.78, 33.5, 1.41, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.41, 6,  drogue,   -4.90,  64175.00, 3689.58, 2359.78,  -29.45, 33.4, 1.41, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.50, 6,  drogue,   -4.90,  64175.00, 3689.58, 2359.78,  -29.45, 33.4, 1.43, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.51, 6,  drogue,  -11.28,  64204.00, 3686.08, 2356.28,  -30.16, 33.4, 1.43, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.61, 6,  drogue,  -13.24,  64227.00, 3683.31, 2353.51,  -30.86, 33.4, 1.43, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.71, 6,  drogue,   -9.32,  64222.00, 3683.92, 2354.12,  -31.53, 33.4, 1.43, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.81, 6,  drogue,   -5.39,  64242.00, 3681.51, 2351.71,  -32.13, 33.4, 1.43, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.82, 6,  drogue,   -5.39,  64242.00, 3681.51, 2351.71,  -32.13, 33.4, 1.41, 3.99, 3.98,   0.03,   0.00,   0.00,  64.15,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    84.91, 6,  drogue,   -2.94,  64375.00, 3665.51, 2335.71,  -32.68, 33.4, 1.41, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    85.01, 6,  drogue,   -8.83,  64402.00, 3662.27, 2332.47,  -33.14, 33.4, 1.41, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    85.11, 6,  drogue,  -12.26,  64418.00, 3660.34, 2330.54,  -33.50, 33.4, 1.41, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    85.14, 6,  drogue,  -12.26,  64418.00, 3660.34, 2330.54,  -33.50, 33.4, 1.41, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    85.21, 6,  drogue,  -13.24,  64469.00, 3654.22, 2324.42,  -33.69, 33.4, 1.41, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466186,-106.9172188,  3900.0, 2022,  6, 24, 15, 18, 41,      957,     2683, 326,  69,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 36,  0,  0,  0,  0, 33, 36, 29, 35,  0,  0, 30,  0, 23, 31,  0,  0,  0, 30,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    85.31, 6,  drogue,  -16.67,  64468.00, 3654.34, 2324.54,  -33.79, 33.4, 1.41, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.31, 6,  drogue,  -16.67,  64468.00, 3654.34, 2324.54,  -33.79, 33.4, 1.41, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.31, 6,  drogue,  -16.67,  64468.00, 3654.34, 2324.54,  -33.79, 33.4, 1.41, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.41, 6,  drogue,  -17.16,  64560.00, 3643.30, 2313.50,  -33.80, 33.4, 1.41, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.46, 6,  drogue,  -17.16,  64560.00, 3643.30, 2313.50,  -33.80, 33.4, 1.41, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.51, 6,  drogue,  -16.18,  64591.00, 3639.59, 2309.78,  -33.71, 33.4, 1.41, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.61, 6,  drogue,  -16.18,  64626.00, 3635.39, 2305.59,  -33.50, 33.4, 1.41, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.71, 6,  drogue,  -20.10,  64629.00, 3635.03, 2305.23,  -33.20, 33.4, 1.41, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.78, 6,  drogue,  -20.10,  64629.00, 3635.03, 2305.23,  -33.20, 33.4, 1.41, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.81, 6,  drogue,  -16.67,  64671.00, 3630.00, 2300.20,  -32.78, 33.4, 1.41, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    85.91, 6,  drogue,  -21.08,  64694.00, 3627.25, 2297.45,  -32.30, 33.4, 1.41, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    86.01, 6,  drogue,  -18.14,  64688.00, 3627.97, 2298.16,  -31.82, 33.4, 1.41, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    86.10, 6,  drogue,  -18.14,  64688.00, 3627.97, 2298.16,  -31.82, 33.4, 1.39, 3.99, 3.99,   0.02,   0.00,   0.00,  64.15,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    86.11, 6,  drogue,  -21.08,  64701.00, 3626.41, 2296.61,  -31.29, 33.4, 1.39, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    86.21, 6,  drogue,  -14.71,  64743.00, 3621.38, 2291.58,  -30.63, 33.4, 1.39, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9466783,-106.9171662,  3873.0, 2022,  6, 24, 15, 18, 42,      960,     2658, 326,  69,   1.4,   0.8,   1.1,  0, 33, 18,  0,  0, 33,  0,  0,  0,  0, 34, 35, 33, 34,  0,  0, 34,  0, 33, 31,  0,  0,  0, 32,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,    86.31, 6,  drogue,  -17.16,  64787.00, 3616.12, 2286.32,  -29.90, 33.4, 1.39, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.31, 6,  drogue,  -17.16,  64787.00, 3616.12, 2286.32,  -29.90, 33.4, 1.39, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.31, 6,  drogue,  -17.16,  64787.00, 3616.12, 2286.32,  -29.90, 33.4, 1.39, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.41, 6,  drogue,  -16.18,  64795.00, 3615.16, 2285.36,  -29.07, 33.4, 1.39, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.42, 6,  drogue,  -16.18,  64795.00, 3615.16, 2285.36,  -29.07, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.21,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.51, 6,  drogue,  -20.10,  64808.00, 3613.61, 2283.81,  -28.30, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.61, 6,  drogue,  -21.08,  64845.00, 3609.19, 2279.39,  -27.57, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.71, 6,  drogue,  -21.08,  64878.00, 3605.25, 2275.45,  -26.87, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.74, 6,  drogue,  -21.08,  64878.00, 3605.25, 2275.45,  -26.87, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.81, 6,  drogue,  -19.61,  64913.00, 3601.07, 2271.27,  -26.20, 33.4, 1.39, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    86.91, 6,  drogue,  -20.59,  64925.00, 3599.63, 2269.83,  -25.65, 33.4, 1.39, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.01, 6,  drogue,  -18.14,  64963.00, 3595.10, 2265.30,  -25.09, 33.4, 1.39, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.06, 6,  drogue,  -18.14,  64963.00, 3595.10, 2265.30,  -25.09, 33.4, 1.40, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.11, 6,  drogue,  -16.18,  64978.00, 3593.31, 2263.51,  -24.58, 33.4, 1.40, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.21, 6,  drogue,  -14.71,  64950.00, 3596.65, 2266.85,  -24.14, 33.4, 1.40, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9467520,-106.9171122,  3845.0, 2022,  6, 24, 15, 18, 43,      964,     2634, 327,  69,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 32,  0,  0,  0,  0, 37, 36, 33, 33,  0,  0, 33,  0, 33, 31,  0,  0,  0, 37,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.31, 6,  drogue,  -13.24,  64967.00, 3594.62, 2264.82,  -23.76, 33.4, 1.40, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.31, 6,  drogue,  -13.24,  64967.00, 3594.62, 2264.82,  -23.76, 33.4, 1.40, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.31, 6,  drogue,  -13.24,  64967.00, 3594.62, 2264.82,  -23.76, 33.4, 1.40, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.38, 6,  drogue,  -13.24,  64967.00, 3594.62, 2264.82,  -23.76, 33.4, 1.39, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.41, 6,  drogue,  -18.63,  64961.00, 3595.34, 2265.54,  -23.52, 33.4, 1.39, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.51, 6,  drogue,  -16.67,  65035.00, 3586.51, 2256.71,  -23.34, 33.4, 1.39, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.61, 6,  drogue,  -16.67,  65084.00, 3580.67, 2250.87,  -23.25, 33.4, 1.39, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.70, 6,  drogue,  -16.67,  65084.00, 3580.67, 2250.87,  -23.25, 33.4, 1.39, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.71, 6,  drogue,  -18.14,  65128.00, 3575.43, 2245.63,  -23.21, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.81, 6,  drogue,  -16.67,  65131.00, 3575.08, 2245.28,  -23.21, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    87.91, 6,  drogue,  -18.63,  65142.00, 3573.77, 2243.97,  -23.27, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.01, 6,  drogue,  -17.16,  65140.00, 3574.01, 2244.21,  -23.35, 33.4, 1.39, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.02, 6,  drogue,  -17.16,  65140.00, 3574.01, 2244.21,  -23.35, 33.4, 1.38, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.11, 6,  drogue,  -19.61,  65127.00, 3575.55, 2245.75,  -23.51, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.21, 6,  drogue,  -15.69,  65076.00, 3581.63, 2251.83,  -23.72, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9468341,-106.9170687,  3815.0, 2022,  6, 24, 15, 18, 44,      969,     2608, 327,  68,   1.4,   0.8,   1.1,  0, 39, 28,  0,  0, 39,  0,  0,  0,  0, 36, 30, 33, 37,  0,  0, 31,  0, 33, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.31, 6,  drogue,  -14.71,  65141.00, 3573.89, 2244.09,  -24.00, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.31, 6,  drogue,  -14.71,  65141.00, 3573.89, 2244.09,  -24.00, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.31, 6,  drogue,  -14.71,  65141.00, 3573.89, 2244.09,  -24.00, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.34, 6,  drogue,  -14.71,  65141.00, 3573.89, 2244.09,  -24.00, 33.4, 1.39, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.04, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.41, 6,  drogue,  -14.71,  65162.00, 3571.39, 2241.59,  -24.28, 33.4, 1.39, 3.98, 3.98,   0.00,   0.00,   0.05,  64.09,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.04, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.51, 6,  drogue,   -9.81,  65215.00, 3565.08, 2235.28,  -24.58, 33.4, 1.39, 3.98, 3.98,   0.00,   0.00,   0.05,  64.09,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.04, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.61, 6,  drogue,  -10.30,  65249.00, 3561.04, 2231.24,  -24.89, 33.4, 1.39, 3.98, 3.98,   0.00,   0.00,   0.05,  64.09,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.04, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.66, 6,  drogue,  -10.30,  65249.00, 3561.04, 2231.24,  -24.89, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.05,  64.09,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.71, 6,  drogue,  -15.20,  65271.00, 3558.42, 2228.62,  -25.21, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.81, 6,  drogue,  -14.22,  65264.00, 3559.26, 2229.46,  -25.52, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.91, 6,  drogue,  -19.12,  65285.00, 3556.76, 2226.96,  -25.80, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    88.98, 6,  drogue,  -19.12,  65285.00, 3556.76, 2226.96,  -25.80, 33.4, 1.39, 3.97, 3.97,   0.00,   0.00,   0.00,  64.09,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.01, 6,  drogue,  -18.14,  65266.00, 3559.02, 2229.22,  -26.05, 33.4, 1.39, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.11, 6,  drogue,  -18.63,  65337.00, 3550.58, 2220.78,  -26.25, 33.4, 1.39, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.21, 6,  drogue,  -20.10,  65376.00, 3545.95, 2216.15,  -26.35, 33.4, 1.39, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.30, 6,  drogue,  -20.10,  65376.00, 3545.95, 2216.15,  -26.35, 33.4, 1.38, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469039,-106.9170217,  3786.0, 2022,  6, 24, 15, 18, 45,      974,     2583, 328,  68,   1.4,   0.8,   1.1,  0, 38, 29,  0,  0, 36,  0,  0,  0,  0, 38, 36, 31, 33,  0,  0, 30,  0, 29, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.31, 6,  drogue,  -22.06,  65439.00, 3538.48, 2208.68,  -26.40, 33.4, 1.38, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.31, 6,  drogue,  -22.06,  65439.00, 3538.48, 2208.68,  -26.40, 33.4, 1.38, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.31, 6,  drogue,  -22.06,  65439.00, 3538.48, 2208.68,  -26.40, 33.4, 1.38, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.41, 6,  drogue,  -20.10,  65487.00, 3532.79, 2202.99,  -26.35, 33.4, 1.38, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.51, 6,  drogue,  -23.05,  65497.00, 3531.60, 2201.80,  -26.24, 33.4, 1.38, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.61, 6,  drogue,  -20.10,  65515.00, 3529.47, 2199.67,  -26.07, 33.4, 1.38, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.62, 6,  drogue,  -20.10,  65515.00, 3529.47, 2199.67,  -26.07, 33.4, 1.38, 3.99, 3.98,   0.03,   0.00,   0.00,  64.09,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.71, 6,  drogue,  -22.56,  65519.00, 3528.99, 2199.19,  -25.90, 33.4, 1.38, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.81, 6,  drogue,  -20.10,  65466.00, 3535.28, 2205.48,  -25.65, 33.4, 1.38, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.91, 6,  drogue,  -17.65,  65491.00, 3532.31, 2202.51,  -25.40, 33.4, 1.38, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    89.94, 6,  drogue,  -17.65,  65491.00, 3532.31, 2202.51,  -25.40, 33.4, 1.38, 3.98, 3.98,   0.00,   0.00,   0.00,  64.21,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.01, 6,  drogue,  -18.63,  65502.00, 3531.01, 2201.21,  -25.08, 33.4, 1.38, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.11, 6,  drogue,  -18.63,  65574.00, 3522.48, 2192.68,  -24.74, 33.3, 1.38, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.21, 6,  drogue,  -17.16,  65568.00, 3523.19, 2193.39,  -24.39, 33.4, 1.38, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.03, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.26, 6,  drogue,  -17.16,  65568.00, 3523.19, 2193.39,  -24.39, 33.4, 1.38, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9469642,-106.9169705,  3756.0, 2022,  6, 24, 15, 18, 46,      977,     2556, 328,  68,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 36,  0,  0,  0,  0, 38, 30, 30, 34,  0,  0, 32,  0, 33, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.31, 6,  drogue,  -16.67,  65621.00, 3516.92, 2187.12,  -24.14, 33.4, 1.38, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.31, 6,  drogue,  -16.67,  65621.00, 3516.92, 2187.12,  -24.14, 33.4, 1.38, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.31, 6,  drogue,  -16.67,  65621.00, 3516.92, 2187.12,  -24.14, 33.4, 1.38, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.41, 6,  drogue,  -15.69,  65632.00, 3515.61, 2185.81,  -24.02, 33.3, 1.38, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.51, 6,  drogue,  -20.59,  65678.00, 3510.17, 2180.37,  -24.00, 33.3, 1.38, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.58, 6,  drogue,  -20.59,  65678.00, 3510.17, 2180.37,  -24.00, 33.3, 1.38, 3.96, 3.98,   0.02,   0.00,   0.00,  64.15,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.61, 6,  drogue,  -16.67,  65697.00, 3507.93, 2178.13,  -24.08, 33.3, 1.38, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.71, 6,  drogue,  -19.12,  65729.00, 3504.14, 2174.34,  -24.22, 33.4, 1.38, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.81, 6,  drogue,  -18.63,  65755.00, 3501.07, 2171.27,  -24.37, 33.4, 1.38, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.90, 6,  drogue,  -18.63,  65755.00, 3501.07, 2171.27,  -24.37, 33.4, 1.37, 3.98, 3.99,   0.00,   0.00,   0.00,  63.84,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    90.91, 6,  drogue,  -19.12,  65766.00, 3499.77, 2169.97,  -24.58, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.01, 6,  drogue,  -12.75,  65794.00, 3496.47, 2166.67,  -24.88, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.11, 6,  drogue,  -16.18,  65786.00, 3497.41, 2167.61,  -25.32, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.21, 6,  drogue,  -13.24,  65782.00, 3497.88, 2168.08,  -25.82, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.22, 6,  drogue,  -13.24,  65782.00, 3497.88, 2168.08,  -25.82, 33.3, 1.37, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.31, 6,  drogue,  -16.67,  65797.00, 3496.11, 2166.31,  -26.35, 33.3, 1.37, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.31, 6,  drogue,  -16.67,  65797.00, 3496.11, 2166.31,  -26.35, 33.3, 1.37, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.31, 6,  drogue,  -16.67,  65797.00, 3496.11, 2166.31,  -26.35, 33.3, 1.37, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9470232,-106.9169446,  3728.0, 2022,  6, 24, 15, 18, 47,      981,     2532, 328,  67,   1.4,   0.8,   1.1,  0, 39, 29,  0,  0, 37,  0,  0,  0,  0, 39, 31, 34, 32,  0,  0, 32,  0, 29, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,    91.41, 6,  drogue,  -11.28,  65781.00, 3498.00, 2168.20,  -26.89, 33.3, 1.37, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.51, 6,  drogue,   -9.32,  65750.00, 3501.66, 2171.86,  -27.44, 33.3, 1.37, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.54, 6,  drogue,   -9.32,  65750.00, 3501.66, 2171.86,  -27.44, 33.3, 1.37, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.61, 6,  drogue,   -4.41,  65795.00, 3496.35, 2166.55,  -27.99, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.71, 6,  drogue,  -12.75,  65899.00, 3484.08, 2154.27,  -28.53, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.81, 6,  drogue,  -13.73,  65923.00, 3481.25, 2151.44,  -28.99, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.86, 6,  drogue,  -13.73,  65923.00, 3481.25, 2151.44,  -28.99, 33.3, 1.38, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    91.91, 6,  drogue,  -11.77,  65977.00, 3474.88, 2145.08,  -29.46, 33.3, 1.38, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    92.01, 6,  drogue,  -14.22,  65961.00, 3476.77, 2146.97,  -29.89, 33.3, 1.38, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    92.11, 6,  drogue,  -12.75,  65979.00, 3474.65, 2144.84,  -30.32, 33.3, 1.38, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    92.18, 6,  drogue,  -12.75,  65979.00, 3474.65, 2144.84,  -30.32, 33.3, 1.37, 3.99, 3.99,   0.00,   0.00,   0.00,  64.03,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    92.21, 6,  drogue,  -13.24,  66019.00, 3469.93, 2140.13,  -30.68, 33.3, 1.37, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9470685,-106.9169567,  3699.0, 2022,  6, 24, 15, 18, 48,      986,     2507, 328,  67,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 24,  0,  0,  0,  0, 32, 38, 30, 28,  0,  0, 27,  0, 36, 26,  0,  0,  0, 37,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,    92.31, 6,  drogue,  -13.24,  66072.00, 3463.69, 2133.89,  -31.01, 33.3, 1.37, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.31, 6,  drogue,  -13.24,  66072.00, 3463.69, 2133.89,  -31.01, 33.3, 1.37, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.31, 6,  drogue,  -13.24,  66072.00, 3463.69, 2133.89,  -31.01, 33.3, 1.37, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.41, 6,  drogue,  -13.73,  66169.00, 3452.29, 2122.49,  -31.25, 33.3, 1.37, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.50, 6,  drogue,  -13.73,  66169.00, 3452.29, 2122.49,  -31.25, 33.3, 1.37, 3.98, 3.99,   0.08,   0.00,   0.00,  64.27,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.51, 6,  drogue,  -16.18,  66202.00, 3448.41, 2118.61,  -31.40, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.61, 6,  drogue,  -16.67,  66202.00, 3448.41, 2118.61,  -31.49, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.71, 6,  drogue,  -18.63,  66188.00, 3450.05, 2120.25,  -31.49, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.81, 6,  drogue,  -19.12,  66144.00, 3455.23, 2125.42,  -31.47, 33.3, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.82, 6,  drogue,  -19.12,  66144.00, 3455.23, 2125.42,  -31.47, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    92.91, 6,  drogue,  -17.16,  66158.00, 3453.58, 2123.78,  -31.39, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    93.01, 6,  drogue,  -15.20,  66234.00, 3444.65, 2114.85,  -31.29, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    93.11, 6,  drogue,  -10.79,  66315.00, 3435.14, 2105.34,  -31.13, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    93.14, 6,  drogue,  -10.79,  66315.00, 3435.14, 2105.34,  -31.13, 33.3, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    93.21, 6,  drogue,  -14.22,  66315.00, 3435.14, 2105.34,  -30.93, 33.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471057,-106.9169888,  3671.0, 2022,  6, 24, 15, 18, 49,      991,     2483, 328,  66,   1.4,   0.8,   1.1,  0, 35, 32,  0,  0, 31,  0,  0,  0,  0, 35, 28, 34, 33,  0,  0, 34,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,    93.31, 6,  drogue,  -11.28,  66285.00, 3438.66, 2108.86,  -30.74, 33.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.31, 6,  drogue,  -11.28,  66285.00, 3438.66, 2108.86,  -30.74, 33.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.31, 6,  drogue,  -11.28,  66285.00, 3438.66, 2108.86,  -30.74, 33.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.41, 6,  drogue,  -12.75,  66320.00, 3434.55, 2104.75,  -30.52, 33.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.46, 6,  drogue,  -12.75,  66320.00, 3434.55, 2104.75,  -30.52, 33.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.51, 6,  drogue,  -15.69,  66369.00, 3428.81, 2099.01,  -30.28, 33.3, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.61, 6,  drogue,  -15.20,  66424.00, 3422.36, 2092.56,  -30.03, 33.3, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.71, 6,  drogue,  -16.18,  66471.00, 3416.85, 2087.05,  -29.79, 33.3, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.78, 6,  drogue,  -16.18,  66471.00, 3416.85, 2087.05,  -29.79, 33.3, 1.35, 3.97, 3.97,   0.09,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.81, 6,  drogue,  -17.65,  66465.00, 3417.56, 2087.76,  -29.50, 33.3, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    93.91, 6,  drogue,  -17.65,  66514.00, 3411.82, 2082.02,  -29.19, 33.3, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    94.01, 6,  drogue,  -17.65,  66531.00, 3409.83, 2080.03,  -28.79, 33.3, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    94.10, 6,  drogue,  -17.65,  66531.00, 3409.83, 2080.03,  -28.79, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.97,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    94.11, 6,  drogue,  -16.18,  66558.00, 3406.67, 2076.87,  -28.34, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    94.21, 6,  drogue,  -17.65,  66593.00, 3402.58, 2072.78,  -27.85, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471456,-106.9170259,  3641.0, 2022,  6, 24, 15, 18, 50,      997,     2458, 328,  66,   1.4,   0.8,   1.1,  0, 27, 28,  0,  0, 38,  0,  0,  0,  0, 28, 32, 29, 35,  0,  0, 35,  0, 36, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    94.31, 6,  drogue,  -18.63,  66615.00, 3400.00, 2070.20,  -27.34, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.31, 6,  drogue,  -18.63,  66615.00, 3400.00, 2070.20,  -27.34, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.31, 6,  drogue,  -18.63,  66615.00, 3400.00, 2070.20,  -27.34, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.41, 6,  drogue,  -17.16,  66598.00, 3401.99, 2072.19,  -26.81, 33.3, 1.35, 3.95, 3.97,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.42, 6,  drogue,  -17.16,  66598.00, 3401.99, 2072.19,  -26.81, 33.3, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  63.66,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.51, 6,  drogue,  -17.16,  66595.00, 3402.34, 2072.54,  -26.23, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.61, 6,  drogue,  -17.16,  66643.00, 3396.73, 2066.93,  -25.61, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.71, 6,  drogue,  -15.69,  66647.00, 3396.26, 2066.46,  -24.95, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.74, 6,  drogue,  -15.69,  66647.00, 3396.26, 2066.46,  -24.95, 33.3, 1.35, 3.96, 3.97,   0.02,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.81, 6,  drogue,  -16.18,  66717.00, 3388.09, 2058.29,  -24.25, 33.3, 1.35, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    94.91, 6,  drogue,  -17.16,  66756.00, 3383.54, 2053.73,  -23.61, 33.3, 1.35, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    95.01, 6,  drogue,  -15.20,  66781.00, 3380.62, 2050.82,  -23.07, 33.3, 1.35, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    95.06, 6,  drogue,  -15.20,  66781.00, 3380.62, 2050.82,  -23.07, 33.3, 1.35, 3.99, 3.98,   0.00,   0.00,   0.00,  63.78,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    95.11, 6,  drogue,  -16.67,  66784.00, 3380.27, 2050.47,  -22.59, 33.3, 1.35, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    95.21, 6,  drogue,  -20.10,  66798.00, 3378.63, 2048.83,  -22.15, 33.3, 1.35, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9471914,-106.9170504,  3612.0, 2022,  6, 24, 15, 18, 51,     1002,     2434, 328,  66,   1.4,   0.8,   1.1,  0, 38, 31,  0,  0, 39,  0,  0,  0,  0, 38, 28, 29, 31,  0,  0, 32,  0, 29, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,    95.31, 6,  drogue,  -20.10,  66849.00, 3372.69, 2042.89,  -21.76, 33.3, 1.35, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.31, 6,  drogue,  -20.10,  66849.00, 3372.69, 2042.89,  -21.76, 33.3, 1.35, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.31, 6,  drogue,  -20.10,  66849.00, 3372.69, 2042.89,  -21.76, 33.3, 1.35, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.38, 6,  drogue,  -20.10,  66849.00, 3372.69, 2042.89,  -21.76, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.41, 6,  drogue,  -16.67,  66844.00, 3373.27, 2043.47,  -21.45, 33.3, 1.36, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.51, 6,  drogue,  -18.63,  66867.00, 3370.59, 2040.79,  -21.26, 33.3, 1.36, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.61, 6,  drogue,  -16.67,  66837.00, 3374.09, 2044.29,  -21.17, 33.3, 1.36, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.70, 6,  drogue,  -16.67,  66837.00, 3374.09, 2044.29,  -21.17, 33.3, 1.35, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.71, 6,  drogue,  -20.10,  66826.00, 3375.37, 2045.57,  -21.17, 33.3, 1.35, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.81, 6,  drogue,  -21.57,  66863.00, 3371.06, 2041.25,  -21.26, 33.3, 1.35, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    95.91, 6,  drogue,  -21.08,  66889.00, 3368.03, 2038.22,  -21.46, 33.3, 1.35, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    96.01, 6,  drogue,  -17.65,  66894.00, 3367.44, 2037.64,  -21.74, 33.3, 1.35, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    96.02, 6,  drogue,  -17.65,  66894.00, 3367.44, 2037.64,  -21.74, 33.3, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    96.11, 6,  drogue,  -22.56,  66918.00, 3364.65, 2034.85,  -22.10, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    96.21, 6,  drogue,  -18.14,  66948.00, 3361.15, 2031.35,  -22.52, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472335,-106.9170582,  3585.0, 2022,  6, 24, 15, 18, 52,     1007,     2411, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 33,  0,  0,  0,  0, 38, 36, 33, 32,  0,  0, 31,  0, 23, 25,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    96.31, 6,  drogue,  -19.61,  66972.00, 3358.36, 2028.56,  -23.01, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.31, 6,  drogue,  -19.61,  66972.00, 3358.36, 2028.56,  -23.01, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.31, 6,  drogue,  -19.61,  66972.00, 3358.36, 2028.56,  -23.01, 33.3, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.34, 6,  drogue,  -19.61,  66972.00, 3358.36, 2028.56,  -23.01, 33.3, 1.35, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.41, 6,  drogue,  -21.08,  66971.00, 3358.48, 2028.68,  -23.54, 33.3, 1.35, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.51, 6,  drogue,  -17.16,  66995.00, 3355.68, 2025.88,  -24.09, 33.3, 1.35, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.61, 6,  drogue,  -14.71,  67037.00, 3350.80, 2021.00,  -24.69, 33.2, 1.35, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.66, 6,  drogue,  -14.71,  67037.00, 3350.80, 2021.00,  -24.69, 33.2, 1.35, 3.98, 3.98,   0.02,   0.00,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.71, 6,  drogue,  -19.61,  67041.00, 3350.33, 2020.53,  -25.28, 33.3, 1.35, 3.98, 3.98,   0.06,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.81, 6,  drogue,  -16.67,  67064.00, 3347.66, 2017.86,  -25.87, 33.3, 1.35, 3.98, 3.98,   0.06,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.91, 6,  drogue,  -16.18,  67105.00, 3342.89, 2013.09,  -26.43, 33.3, 1.35, 3.98, 3.98,   0.06,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    96.98, 6,  drogue,  -16.18,  67105.00, 3342.89, 2013.09,  -26.43, 33.3, 1.35, 3.98, 3.98,   0.06,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    97.01, 6,  drogue,  -14.71,  67134.00, 3339.52, 2009.72,  -26.95, 33.2, 1.35, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    97.11, 6,  drogue,  -10.79,  67126.00, 3340.45, 2010.65,  -27.41, 33.2, 1.35, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    97.21, 6,  drogue,  -13.24,  67164.00, 3336.04, 2006.24,  -27.80, 33.2, 1.35, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    97.30, 6,  drogue,  -13.24,  67164.00, 3336.04, 2006.24,  -27.80, 33.2, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472672,-106.9170606,  3556.0, 2022,  6, 24, 15, 18, 53,     1010,     2386, 329,  65,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 32,  0,  0,  0,  0, 32, 26, 27, 38,  0,  0, 39,  0, 37, 25,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    97.31, 6,  drogue,  -13.24,  67184.00, 3333.71, 2003.91,  -28.15, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.31, 6,  drogue,  -13.24,  67184.00, 3333.71, 2003.91,  -28.15, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.31, 6,  drogue,  -13.24,  67184.00, 3333.71, 2003.91,  -28.15, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.41, 6,  drogue,  -15.69,  67199.00, 3331.97, 2002.17,  -28.37, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.51, 6,  drogue,  -11.28,  67238.00, 3327.45, 1997.65,  -28.54, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.61, 6,  drogue,  -15.20,  67257.00, 3325.24, 1995.44,  -28.62, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.62, 6,  drogue,  -15.20,  67257.00, 3325.24, 1995.44,  -28.62, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.71, 6,  drogue,  -16.67,  67274.00, 3323.27, 1993.47,  -28.63, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.81, 6,  drogue,  -18.14,  67335.00, 3316.20, 1986.40,  -28.62, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.91, 6,  drogue,  -15.20,  67371.00, 3312.03, 1982.23,  -28.59, 33.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    97.94, 6,  drogue,  -15.20,  67371.00, 3312.03, 1982.23,  -28.59, 33.2, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    98.01, 6,  drogue,  -17.65,  67392.00, 3309.60, 1979.79,  -28.50, 33.2, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    98.11, 6,  drogue,  -17.16,  67417.00, 3306.70, 1976.90,  -28.42, 33.2, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    98.21, 6,  drogue,  -16.18,  67405.00, 3308.09, 1978.29,  -28.32, 33.2, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    98.26, 6,  drogue,  -16.18,  67405.00, 3308.09, 1978.29,  -28.32, 33.2, 1.34, 3.99, 3.99,   0.02,   0.00,   0.00,  64.15,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9472869,-106.9170448,  3528.0, 2022,  6, 24, 15, 18, 54,     1011,     2361, 329,  65,   1.4,   0.8,   1.1,  0, 38, 27,  0,  0, 39,  0,  0,  0,  0, 36, 26, 33, 32,  0,  0, 39,  0, 37, 30,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,    98.31, 6,  drogue,  -17.65,  67466.00, 3301.03, 1971.23,  -28.18, 33.2, 1.34, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.31, 6,  drogue,  -17.65,  67466.00, 3301.03, 1971.23,  -28.18, 33.2, 1.34, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.31, 6,  drogue,  -17.65,  67466.00, 3301.03, 1971.23,  -28.18, 33.2, 1.34, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.41, 6,  drogue,  -19.12,  67500.00, 3297.10, 1967.29,  -27.98, 33.2, 1.34, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.51, 6,  drogue,  -23.05,  67509.00, 3296.05, 1966.25,  -27.76, 33.2, 1.34, 3.99, 3.99,   0.03,   0.00,   0.00,  64.27,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.58, 6,  drogue,  -23.05,  67509.00, 3296.05, 1966.25,  -27.76, 33.2, 1.35, 3.98, 3.99,   0.03,   0.00,   0.00,  64.27,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.61, 6,  drogue,  -24.52,  67526.00, 3294.09, 1964.29,  -27.56, 33.2, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.71, 6,  drogue,  -20.59,  67549.00, 3291.43, 1961.63,  -27.31, 33.2, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.81, 6,  drogue,  -23.05,  67529.00, 3293.74, 1963.94,  -27.03, 33.2, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.90, 6,  drogue,  -23.05,  67529.00, 3293.74, 1963.94,  -27.03, 33.2, 1.33, 3.97, 3.97,   0.09,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    98.91, 6,  drogue,  -20.59,  67570.00, 3289.00, 1959.20,  -26.75, 33.2, 1.33, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.01, 6,  drogue,  -20.10,  67609.00, 3284.50, 1954.70,  -26.45, 33.2, 1.33, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.11, 6,  drogue,  -19.61,  67647.00, 3280.11, 1950.31,  -26.08, 33.2, 1.33, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.21, 6,  drogue,  -19.12,  67661.00, 3278.49, 1948.69,  -25.66, 33.2, 1.33, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.22, 6,  drogue,  -19.12,  67661.00, 3278.49, 1948.69,  -25.66, 33.2, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.30, 6,  drogue,  -19.12,  67661.00, 3278.49, 1948.69,  -25.66, 33.2, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.30, 6,  drogue,  -19.12,  67661.00, 3278.49, 1948.69,  -25.66, 33.2, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.91,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9473052,-106.9170153,  3499.0, 2022,  6, 24, 15, 18, 55,     1011,     2335, 329,  64,   1.4,   0.8,   1.1,  0, 34, 28,  0,  0, 36,  0,  0,  0,  0, 33, 35, 28, 31,  0,  0, 32,  0, 37, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,    99.31, 6,  drogue,  -20.10,  67686.00, 3275.61, 1945.81,  -25.23, 33.2, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.41, 6,  drogue,  -21.08,  67669.00, 3277.57, 1947.77,  -24.84, 33.2, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.51, 6,  drogue,  -19.61,  67729.00, 3270.65, 1940.84,  -24.52, 33.2, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.54, 6,  drogue,  -19.61,  67729.00, 3270.65, 1940.84,  -24.52, 33.2, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  63.84,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.61, 6,  drogue,  -17.65,  67757.00, 3267.42, 1937.62,  -24.20, 33.2, 1.33, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.71, 6,  drogue,  -19.12,  67767.00, 3266.26, 1936.46,  -23.94, 33.2, 1.33, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.81, 6,  drogue,  -19.12,  67815.00, 3260.73, 1930.93,  -23.75, 33.2, 1.33, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.86, 6,  drogue,  -19.12,  67815.00, 3260.73, 1930.93,  -23.75, 33.2, 1.33, 3.98, 3.99,   0.03,   0.00,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,    99.91, 6,  drogue,  -22.06,  67850.00, 3256.70, 1926.90,  -23.59, 33.2, 1.33, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   100.01, 6,  drogue,  -17.65,  67846.00, 3257.16, 1927.36,  -23.48, 33.2, 1.33, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   100.11, 6,  drogue,  -13.73,  67908.00, 3250.02, 1920.22,  -23.47, 33.2, 1.33, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   100.18, 6,  drogue,  -13.73,  67908.00, 3250.02, 1920.22,  -23.47, 33.2, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   100.21, 6,  drogue,  -21.08,  67898.00, 3251.17, 1921.37,  -23.51, 33.2, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9473467,-106.9169811,  3470.0, 2022,  6, 24, 15, 18, 56,     1014,     2310, 329,  64,   1.4,   0.8,   1.1,  0, 32, 24,  0,  0, 36,  0,  0,  0,  0, 33, 38, 22, 34,  0,  0, 27,  0, 36, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   100.31, 6,  drogue,  -20.59,  67902.00, 3250.71, 1920.91,  -23.66, 33.2, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.31, 6,  drogue,  -20.59,  67902.00, 3250.71, 1920.91,  -23.66, 33.2, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.31, 6,  drogue,  -20.59,  67902.00, 3250.71, 1920.91,  -23.66, 33.2, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.41, 6,  drogue,  -19.61,  67872.00, 3254.17, 1924.36,  -23.84, 33.2, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.50, 6,  drogue,  -19.61,  67872.00, 3254.17, 1924.36,  -23.84, 33.2, 1.33, 3.97, 3.99,   0.09,   0.00,   0.00,  64.09,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.51, 6,  drogue,  -19.12,  67900.00, 3250.94, 1921.14,  -24.01, 33.2, 1.33, 3.97, 3.99,   0.02,   0.00,   0.00,  63.97,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.61, 6,  drogue,  -15.69,  67946.00, 3245.65, 1915.85,  -24.19, 33.2, 1.33, 3.97, 3.99,   0.02,   0.00,   0.00,  63.97,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.71, 6,  drogue,  -11.28,  67950.00, 3245.19, 1915.39,  -24.43, 33.2, 1.33, 3.97, 3.99,   0.02,   0.00,   0.00,  63.97,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.81, 6,  drogue,   -6.86,  67948.00, 3245.42, 1915.62,  -24.75, 33.2, 1.33, 3.97, 3.99,   0.02,   0.00,   0.00,  63.97,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.82, 6,  drogue,   -6.86,  67948.00, 3245.42, 1915.62,  -24.75, 33.2, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   100.91, 6,  drogue,  -13.24,  67993.00, 3240.24, 1910.44,  -25.11, 33.2, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   101.01, 6,  drogue,   -5.39,  68003.00, 3239.09, 1909.29,  -25.50, 33.2, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   101.11, 6,  drogue,  -10.30,  67990.00, 3240.59, 1910.79,  -25.89, 33.2, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   101.14, 6,  drogue,  -10.30,  67990.00, 3240.59, 1910.79,  -25.89, 33.2, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  63.97,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   101.21, 6,  drogue,   -9.32,  67974.00, 3242.43, 1912.63,  -26.28, 33.2, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474173,-106.9169438,  3441.0, 2022,  6, 24, 15, 18, 57,     1019,     2286, 330,  64,   1.4,   0.8,   1.1,  0, 27, 34,  0,  0, 36,  0,  0,  0,  0, 26, 31, 25, 36,  0,  0, 38,  0, 35, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   101.31, 6,  drogue,  -11.28,  68035.00, 3235.41, 1905.61,  -26.59, 33.2, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.31, 6,  drogue,  -11.28,  68035.00, 3235.41, 1905.61,  -26.59, 33.2, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.31, 6,  drogue,  -11.28,  68035.00, 3235.41, 1905.61,  -26.59, 33.2, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.41, 6,  drogue,   -7.85,  68143.00, 3223.01, 1893.21,  -26.84, 33.2, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.46, 6,  drogue,   -7.85,  68143.00, 3223.01, 1893.21,  -26.84, 33.2, 1.33, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.51, 6,  drogue,  -12.75,  68228.00, 3213.26, 1883.46,  -27.09, 33.2, 1.33, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.61, 6,  drogue,  -13.73,  68210.00, 3215.32, 1885.52,  -27.30, 33.2, 1.33, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.71, 6,  drogue,  -21.08,  68267.00, 3208.79, 1878.99,  -27.39, 33.2, 1.33, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.78, 6,  drogue,  -21.08,  68267.00, 3208.79, 1878.99,  -27.39, 33.2, 1.33, 3.96, 3.98,   0.02,   0.00,   0.00,  64.15,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.81, 6,  drogue,  -21.57,  68272.00, 3208.22, 1878.41,  -27.38, 33.1, 1.33, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   101.91, 6,  drogue,  -17.65,  68234.00, 3212.57, 1882.77,  -27.32, 33.1, 1.33, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.01, 6,  drogue,  -15.69,  68270.00, 3208.44, 1878.64,  -27.14, 33.1, 1.33, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.10, 6,  drogue,  -15.69,  68270.00, 3208.44, 1878.64,  -27.14, 33.1, 1.33, 3.99, 3.99,   0.00,   0.00,   0.00,  63.84,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.11, 6,  drogue,  -15.20,  68336.00, 3200.88, 1871.08,  -27.02, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.21, 6,  drogue,   -7.85,  68345.00, 3199.85, 1870.05,  -26.87, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.31, 6,  drogue,   -3.43,  68352.00, 3199.05, 1869.25,  -26.66, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.31, 6,  drogue,   -3.43,  68352.00, 3199.05, 1869.25,  -26.66, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.31, 6,  drogue,   -3.43,  68352.00, 3199.05, 1869.25,  -26.66, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475004,-106.9169220,  3413.0, 2022,  6, 24, 15, 18, 58,     1026,     2265, 330,  63,   1.4,   0.8,   1.1,  0, 37, 30,  0,  0, 37,  0,  0,  0,  0, 37, 31, 32, 24,  0,  0, 36,  0, 35, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   102.41, 6,  drogue,   -4.41,  68328.00, 3201.80, 1872.00,  -26.40, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.42, 6,  drogue,   -4.41,  68328.00, 3201.80, 1872.00,  -26.40, 33.1, 1.33, 3.99, 3.99,   0.00,   0.01,   0.00,  64.21,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.51, 6,  drogue,   -7.85,  68281.00, 3207.18, 1877.38,  -26.18, 33.1, 1.33, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.61, 6,  drogue,   -5.39,  68297.00, 3205.35, 1875.55,  -25.97, 33.1, 1.33, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.71, 6,  drogue,    2.45,  68400.00, 3193.56, 1863.76,  -25.81, 33.1, 1.33, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.74, 6,  drogue,    2.45,  68400.00, 3193.56, 1863.76,  -25.81, 33.1, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.81, 6,  drogue,    4.90,  68525.00, 3179.26, 1849.46,  -25.71, 33.1, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   102.91, 6,  drogue,  -13.24,  68527.00, 3179.04, 1849.23,  -25.66, 33.1, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   103.01, 6,  drogue,  -16.18,  68561.00, 3175.15, 1845.35,  -25.65, 33.1, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.27,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   103.06, 6,  drogue,  -16.18,  68561.00, 3175.15, 1845.35,  -25.65, 33.1, 1.33, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   103.11, 6,  drogue,   -5.88,  68564.00, 3174.81, 1845.01,  -25.69, 33.1, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   103.21, 6,  drogue,   -3.43,  68597.00, 3171.04, 1841.24,  -25.71, 33.1, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475655,-106.9169222,  3384.0, 2022,  6, 24, 15, 18, 59,     1032,     2242, 330,  63,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 31,  0,  0,  0,  0, 37, 34, 32, 31,  0,  0, 33,  0, 31, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   103.31, 6,  drogue,   -6.86,  68549.00, 3176.52, 1846.72,  -25.81, 33.1, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.31, 6,  drogue,   -6.86,  68549.00, 3176.52, 1846.72,  -25.81, 33.1, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.31, 6,  drogue,   -6.86,  68549.00, 3176.52, 1846.72,  -25.81, 33.1, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.38, 6,  drogue,   -6.86,  68549.00, 3176.52, 1846.72,  -25.81, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.21,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.41, 6,  drogue,  -16.67,  68579.00, 3173.10, 1843.30,  -26.01, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.51, 6,  drogue,   -3.92,  68625.00, 3167.85, 1838.04,  -26.25, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.61, 6,  drogue,    2.94,  68657.00, 3164.19, 1834.39,  -26.47, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.70, 6,  drogue,    2.94,  68657.00, 3164.19, 1834.39,  -26.47, 33.1, 1.32, 3.99, 3.99,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.71, 6,  drogue,   -9.81,  68598.00, 3170.93, 1841.13,  -26.71, 33.1, 1.32, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.81, 6,  drogue,  -12.26,  68581.00, 3172.87, 1843.07,  -26.90, 33.1, 1.32, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   103.91, 6,  drogue,   -6.86,  68636.00, 3166.59, 1836.79,  -27.06, 33.1, 1.32, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.01, 6,  drogue,  -12.26,  68650.00, 3164.99, 1835.19,  -27.23, 33.1, 1.32, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.02, 6,  drogue,  -12.26,  68650.00, 3164.99, 1835.19,  -27.23, 33.1, 1.31, 3.96, 3.98,   0.00,   0.00,   0.00,  64.27,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.11, 6,  drogue,   -0.49,  68795.00, 3148.46, 1818.66,  -27.43, 33.1, 1.31, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.21, 6,  drogue,   -2.45,  68843.00, 3143.00, 1813.20,  -27.59, 33.1, 1.31, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476104,-106.9169397,  3356.0, 2022,  6, 24, 15, 19,  0,     1037,     2219, 330,  62,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 36,  0,  0,  0,  0, 31, 34, 29, 35,  0,  0, 31,  0, 37, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.31, 6,  drogue,   -9.81,  68817.00, 3145.96, 1816.16,  -27.71, 33.1, 1.31, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.31, 6,  drogue,   -9.81,  68817.00, 3145.96, 1816.16,  -27.71, 33.1, 1.31, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.31, 6,  drogue,   -9.81,  68817.00, 3145.96, 1816.16,  -27.71, 33.1, 1.31, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.34, 6,  drogue,   -9.81,  68817.00, 3145.96, 1816.16,  -27.71, 33.1, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.41, 6,  drogue,  -14.71,  68806.00, 3147.21, 1817.41,  -27.80, 33.1, 1.32, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.51, 6,  drogue,  -15.69,  68854.00, 3141.75, 1811.94,  -27.86, 33.1, 1.32, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.61, 6,  drogue,  -16.67,  68837.00, 3143.68, 1813.88,  -27.91, 33.1, 1.32, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.66, 6,  drogue,  -16.67,  68837.00, 3143.68, 1813.88,  -27.91, 33.1, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.71, 6,  drogue,  -19.12,  68921.00, 3134.12, 1804.32,  -27.97, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.81, 6,  drogue,  -17.16,  68971.00, 3128.44, 1798.64,  -28.08, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.91, 6,  drogue,   -9.81,  68966.00, 3129.01, 1799.21,  -28.14, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   104.98, 6,  drogue,   -9.81,  68966.00, 3129.01, 1799.21,  -28.14, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   105.01, 6,  drogue,  -10.79,  68991.00, 3126.17, 1796.36,  -28.15, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   105.11, 6,  drogue,  -20.10,  69015.00, 3123.44, 1793.64,  -28.12, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   105.21, 6,  drogue,  -16.18,  68984.00, 3126.96, 1797.16,  -28.07, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.09,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   105.30, 6,  drogue,  -16.18,  68984.00, 3126.96, 1797.16,  -28.07, 33.1, 1.32, 3.99, 3.99,   0.08,   0.00,   0.00,  64.09,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9476673,-106.9169653,  3328.0, 2022,  6, 24, 15, 19,  1,     1044,     2198, 330,  62,   1.4,   0.8,   1.1,  0, 31, 30,  0,  0, 33,  0,  0,  0,  0, 31, 33, 32, 31,  0,  0, 33,  0, 35, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   105.31, 6,  drogue,  -14.71,  69005.00, 3124.57, 1794.77,  -27.95, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.31, 6,  drogue,  -14.71,  69005.00, 3124.57, 1794.77,  -27.95, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.31, 6,  drogue,  -14.71,  69005.00, 3124.57, 1794.77,  -27.95, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.41, 6,  drogue,  -15.69,  69067.00, 3117.53, 1787.73,  -27.86, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.51, 6,  drogue,  -13.73,  69103.00, 3113.45, 1783.65,  -27.78, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.61, 6,  drogue,  -14.71,  69133.00, 3110.04, 1780.24,  -27.70, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.01, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.62, 6,  drogue,  -14.71,  69133.00, 3110.04, 1780.24,  -27.70, 33.1, 1.32, 3.99, 3.99,   0.02,   0.00,   0.01,  64.27,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.71, 6,  drogue,  -14.22,  69154.00, 3107.66, 1777.86,  -27.57, 33.1, 1.32, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.81, 6,  drogue,  -16.67,  69149.00, 3108.23, 1778.43,  -27.45, 33.1, 1.32, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.91, 6,  drogue,  -18.63,  69188.00, 3103.81, 1774.00,  -27.37, 33.1, 1.32, 3.99, 3.99,   0.09,   0.00,   0.00,  64.21,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   105.94, 6,  drogue,  -18.63,  69188.00, 3103.81, 1774.00,  -27.37, 33.1, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.21,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   106.01, 6,  drogue,  -17.65,  69213.00, 3100.97, 1771.17,  -27.27, 33.1, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   106.11, 6,  drogue,  -15.69,  69251.00, 3096.67, 1766.86,  -27.21, 33.1, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   106.21, 6,  drogue,  -19.12,  69272.00, 3094.29, 1764.49,  -27.16, 33.1, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   106.26, 6,  drogue,  -19.12,  69272.00, 3094.29, 1764.49,  -27.16, 33.1, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477182,-106.9169846,  3301.0, 2022,  6, 24, 15, 19,  2,     1049,     2177, 330,  61,   1.4,   0.8,   1.1,  0, 31, 29,  0,  0, 38,  0,  0,  0,  0, 31, 33, 26, 37,  0,  0, 34,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   106.31, 6,  drogue,  -17.65,  69273.00, 3094.17, 1764.37,  -27.03, 33.1, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.31, 6,  drogue,  -17.65,  69273.00, 3094.17, 1764.37,  -27.03, 33.1, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.31, 6,  drogue,  -17.65,  69273.00, 3094.17, 1764.37,  -27.03, 33.1, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.41, 6,  drogue,  -19.12,  69328.00, 3087.95, 1758.15,  -26.88, 33.1, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.51, 6,  drogue,  -20.59,  69360.00, 3084.33, 1754.52,  -26.77, 33.1, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.58, 6,  drogue,  -20.59,  69360.00, 3084.33, 1754.52,  -26.77, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.61, 6,  drogue,  -19.12,  69376.00, 3082.51, 1752.71,  -26.66, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.71, 6,  drogue,  -22.06,  69357.00, 3084.66, 1754.86,  -26.61, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.81, 6,  drogue,  -22.56,  69416.00, 3077.99, 1748.19,  -26.58, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.90, 6,  drogue,  -22.56,  69416.00, 3077.99, 1748.19,  -26.58, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   106.91, 6,  drogue,  -16.18,  69451.00, 3074.03, 1744.23,  -26.48, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.01, 6,  drogue,  -19.61,  69459.00, 3073.13, 1743.33,  -26.40, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.11, 6,  drogue,  -19.12,  69482.00, 3070.53, 1740.73,  -26.28, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.21, 6,  drogue,  -14.22,  69504.00, 3068.05, 1738.25,  -26.16, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.22, 6,  drogue,  -14.22,  69504.00, 3068.05, 1738.25,  -26.16, 33.1, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477425,-106.9169784,  3272.0, 2022,  6, 24, 15, 19,  3,     1052,     2152, 331,  61,   1.4,   0.8,   1.1,  0, 35, 36,  0,  0, 38,  0,  0,  0,  0, 34, 27, 28, 34,  0,  0, 38,  0, 36, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.31, 6,  drogue,  -19.12,  69517.00, 3066.58, 1736.78,  -26.06, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.31, 6,  drogue,  -19.12,  69517.00, 3066.58, 1736.78,  -26.06, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.31, 6,  drogue,  -19.12,  69517.00, 3066.58, 1736.78,  -26.06, 33.1, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.41, 6,  drogue,  -20.10,  69558.00, 3061.95, 1732.15,  -26.06, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.51, 6,  drogue,  -16.67,  69575.00, 3060.03, 1730.23,  -26.08, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.54, 6,  drogue,  -16.67,  69575.00, 3060.03, 1730.23,  -26.08, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.61, 6,  drogue,  -15.69,  69580.00, 3059.47, 1729.66,  -26.07, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.71, 6,  drogue,  -20.10,  69619.00, 3055.06, 1725.26,  -26.04, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.81, 6,  drogue,  -16.18,  69642.00, 3052.47, 1722.67,  -25.99, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.86, 6,  drogue,  -16.18,  69642.00, 3052.47, 1722.67,  -25.99, 33.0, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   107.91, 6,  drogue,   -6.37,  69665.00, 3049.88, 1720.08,  -25.95, 33.0, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   108.01, 6,  drogue,  -13.24,  69666.00, 3049.76, 1719.96,  -25.94, 33.0, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   108.11, 6,  drogue,  -19.61,  69646.00, 3052.02, 1722.22,  -25.94, 33.0, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   108.18, 6,  drogue,  -19.61,  69646.00, 3052.02, 1722.22,  -25.94, 33.0, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   108.21, 6,  drogue,  -15.20,  69726.00, 3043.00, 1713.20,  -25.96, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477522,-106.9169510,  3243.0, 2022,  6, 24, 15, 19,  4,     1051,     2127, 331,  60,   1.4,   0.8,   1.1,  0, 32, 31,  0,  0, 29,  0,  0,  0,  0, 31, 32, 27, 37,  0,  0, 36,  0, 33, 29,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   108.31, 6,  drogue,  -15.20,  69741.00, 3041.31, 1711.51,  -25.99, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.31, 6,  drogue,  -15.20,  69741.00, 3041.31, 1711.51,  -25.99, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.31, 6,  drogue,  -15.20,  69741.00, 3041.31, 1711.51,  -25.99, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.41, 6,  drogue,  -17.65,  69777.00, 3037.26, 1707.46,  -26.06, 33.0, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.50, 6,  drogue,  -17.65,  69777.00, 3037.26, 1707.46,  -26.06, 33.0, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.51, 6,  drogue,  -16.67,  69851.00, 3028.93, 1699.13,  -26.17, 33.0, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.61, 6,  drogue,  -18.14,  69879.00, 3025.78, 1695.98,  -26.27, 33.0, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.71, 6,  drogue,  -19.61,  69902.00, 3023.19, 1693.39,  -26.38, 33.0, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.81, 6,  drogue,  -20.10,  69906.00, 3022.74, 1692.94,  -26.55, 33.0, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.82, 6,  drogue,  -20.10,  69906.00, 3022.74, 1692.94,  -26.55, 33.0, 1.29, 3.96, 3.98,   0.09,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   108.91, 6,  drogue,  -16.18,  69855.00, 3028.48, 1698.68,  -26.77, 33.0, 1.29, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   109.01, 6,  drogue,  -15.69,  69902.00, 3023.19, 1693.39,  -27.03, 33.0, 1.29, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   109.11, 6,  drogue,  -20.10,  69860.00, 3027.92, 1698.12,  -27.32, 33.0, 1.29, 3.96, 3.98,   0.00,   0.00,   0.00,  63.78,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   109.14, 6,  drogue,  -20.10,  69860.00, 3027.92, 1698.12,  -27.32, 33.0, 1.31, 3.97, 3.98,   0.00,   0.00,   0.00,  63.78,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   109.21, 6,  drogue,  -14.22,  69942.00, 3018.70, 1688.90,  -27.60, 33.0, 1.31, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477438,-106.9169092,  3214.0, 2022,  6, 24, 15, 19,  5,     1049,     2100, 331,  60,   1.4,   0.8,   1.1,  0, 35, 31,  0,  0, 32,  0,  0,  0,  0, 33, 33, 33, 31,  0,  0, 31,  0, 32, 34,  0,  0,  0, 30,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   109.31, 6,  drogue,  -15.69,  69964.00, 3016.23, 1686.42,  -27.89, 33.0, 1.31, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.31, 6,  drogue,  -15.69,  69964.00, 3016.23, 1686.42,  -27.89, 33.0, 1.31, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.31, 6,  drogue,  -15.69,  69964.00, 3016.23, 1686.42,  -27.89, 33.0, 1.31, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.41, 6,  drogue,  -13.73,  70069.00, 3004.44, 1674.63,  -28.13, 33.0, 1.31, 3.97, 3.98,   0.00,   0.00,   0.00,  63.97,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.46, 6,  drogue,  -13.73,  70069.00, 3004.44, 1674.63,  -28.13, 33.0, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  63.97,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.51, 6,  drogue,  -12.26,  70068.00, 3004.55, 1674.75,  -28.36, 33.0, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.61, 6,  drogue,  -10.30,  70032.00, 3008.59, 1678.79,  -28.59, 33.0, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.71, 6,  drogue,  -10.79,  70038.00, 3007.92, 1678.11,  -28.82, 33.0, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.78, 6,  drogue,  -10.79,  70038.00, 3007.92, 1678.11,  -28.82, 33.0, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.81, 6,  drogue,  -12.75,  70076.00, 3003.65, 1673.85,  -29.03, 33.0, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   109.91, 6,  drogue,  -12.26,  70101.00, 3000.85, 1671.04,  -29.18, 33.0, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.01, 6,  drogue,   -8.83,  70164.00, 2993.78, 1663.98,  -29.24, 33.0, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.10, 6,  drogue,   -8.83,  70164.00, 2993.78, 1663.98,  -29.24, 33.0, 1.31, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.11, 6,  drogue,  -13.24,  70195.00, 2990.31, 1660.51,  -29.27, 33.0, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.21, 6,  drogue,  -18.14,  70246.00, 2984.59, 1654.79,  -29.31, 33.0, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477268,-106.9168715,  3185.0, 2022,  6, 24, 15, 19,  6,     1045,     2074, 331,  60,   1.4,   0.8,   1.1,  0, 37, 26,  0,  0, 27,  0,  0,  0,  0, 36, 29, 33, 27,  0,  0, 35,  0, 35, 30,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.31, 6,  drogue,  -16.18,  70272.00, 2981.68, 1651.88,  -29.32, 33.0, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.31, 6,  drogue,  -16.18,  70272.00, 2981.68, 1651.88,  -29.32, 33.0, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.31, 6,  drogue,  -16.18,  70272.00, 2981.68, 1651.88,  -29.32, 33.0, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.41, 6,  drogue,  -14.71,  70303.00, 2978.21, 1648.41,  -29.27, 33.0, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.42, 6,  drogue,  -14.71,  70303.00, 2978.21, 1648.41,  -29.27, 33.0, 1.30, 3.99, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.51, 6,  drogue,  -15.69,  70329.00, 2975.30, 1645.50,  -29.20, 33.0, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.61, 6,  drogue,  -17.65,  70323.00, 2975.97, 1646.17,  -29.08, 33.0, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.71, 6,  drogue,  -18.14,  70362.00, 2971.61, 1641.81,  -28.86, 33.0, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.74, 6,  drogue,  -18.14,  70362.00, 2971.61, 1641.81,  -28.86, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.81, 6,  drogue,  -15.20,  70388.00, 2968.70, 1638.90,  -28.55, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   110.91, 6,  drogue,  -14.71,  70441.00, 2962.78, 1632.98,  -28.17, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   111.01, 6,  drogue,  -18.14,  70473.00, 2959.21, 1629.41,  -27.80, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   111.06, 6,  drogue,  -18.14,  70473.00, 2959.21, 1629.41,  -27.80, 33.0, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   111.11, 6,  drogue,  -19.61,  70483.00, 2958.09, 1628.29,  -27.38, 33.0, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   111.21, 6,  drogue,  -15.20,  70474.00, 2959.09, 1629.29,  -27.00, 33.0, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477035,-106.9168405,  3158.0, 2022,  6, 24, 15, 19,  7,     1041,     2049, 331,  59,   1.4,   0.8,   1.1,  0, 32, 28,  0,  0, 33,  0,  0,  0,  0, 34, 29, 26, 26,  0,  0, 40,  0, 37, 33,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   111.31, 6,  drogue,  -14.71,  70489.00, 2957.42, 1627.62,  -26.63, 33.0, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.31, 6,  drogue,  -14.71,  70489.00, 2957.42, 1627.62,  -26.63, 33.0, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.31, 6,  drogue,  -14.71,  70489.00, 2957.42, 1627.62,  -26.63, 33.0, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.38, 6,  drogue,  -14.71,  70489.00, 2957.42, 1627.62,  -26.63, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.41, 6,  drogue,  -19.61,  70440.00, 2962.89, 1633.09,  -26.30, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.51, 6,  drogue,  -17.16,  70499.00, 2956.30, 1626.50,  -25.97, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.61, 6,  drogue,  -16.18,  70579.00, 2947.37, 1617.57,  -25.60, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.70, 6,  drogue,  -16.18,  70579.00, 2947.37, 1617.57,  -25.60, 33.0, 1.29, 3.98, 4.00,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.71, 6,  drogue,  -12.75,  70633.00, 2941.35, 1611.55,  -25.29, 33.0, 1.29, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.81, 6,  drogue,  -16.18,  70662.00, 2938.12, 1608.32,  -25.01, 33.0, 1.29, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   111.91, 6,  drogue,  -18.63,  70649.00, 2939.57, 1609.77,  -24.76, 33.0, 1.29, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.01, 6,  drogue,  -19.12,  70649.00, 2939.57, 1609.77,  -24.57, 33.0, 1.29, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.02, 6,  drogue,  -19.12,  70649.00, 2939.57, 1609.77,  -24.57, 33.0, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.11, 6,  drogue,  -22.06,  70722.00, 2931.43, 1601.63,  -24.40, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.21, 6,  drogue,  -18.63,  70758.00, 2927.42, 1597.62,  -24.24, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476800,-106.9168131,  3130.0, 2022,  6, 24, 15, 19,  8,     1038,     2023, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 33, 27, 31,  0,  0, 32,  0, 30, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.31, 6,  drogue,  -20.59,  70792.00, 2923.64, 1593.84,  -24.09, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.31, 6,  drogue,  -20.59,  70792.00, 2923.64, 1593.84,  -24.09, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.31, 6,  drogue,  -20.59,  70792.00, 2923.64, 1593.84,  -24.09, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.34, 6,  drogue,  -20.59,  70792.00, 2923.64, 1593.84,  -24.09, 33.0, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.41, 6,  drogue,  -22.06,  70782.00, 2924.75, 1594.95,  -23.97, 33.0, 1.29, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.51, 6,  drogue,  -20.10,  70790.00, 2923.86, 1594.06,  -23.88, 33.0, 1.29, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.61, 6,  drogue,  -17.65,  70809.00, 2921.75, 1591.95,  -23.80, 33.0, 1.29, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.66, 6,  drogue,  -17.65,  70809.00, 2921.75, 1591.95,  -23.80, 33.0, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.71, 6,  drogue,  -16.67,  70754.00, 2927.87, 1598.07,  -23.76, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.81, 6,  drogue,   -9.32,  70755.00, 2927.76, 1597.96,  -23.74, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.91, 6,  drogue,  -13.24,  70801.00, 2922.64, 1592.84,  -23.73, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   112.98, 6,  drogue,  -13.24,  70801.00, 2922.64, 1592.84,  -23.73, 33.0, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.01, 6,  drogue,  -14.22,  70857.00, 2916.41, 1586.61,  -23.73, 32.9, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.11, 6,  drogue,  -13.24,  70886.00, 2913.18, 1583.38,  -23.72, 33.0, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.21, 6,  drogue,  -16.67,  70917.00, 2909.74, 1579.94,  -23.70, 33.0, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.30, 6,  drogue,  -16.67,  70917.00, 2909.74, 1579.94,  -23.70, 33.0, 1.30, 3.99, 3.98,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.31, 6,  drogue,  -17.16,  70958.00, 2905.18, 1575.38,  -23.70, 33.0, 1.30, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.31, 6,  drogue,  -17.16,  70958.00, 2905.18, 1575.38,  -23.70, 33.0, 1.30, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.31, 6,  drogue,  -17.16,  70958.00, 2905.18, 1575.38,  -23.70, 33.0, 1.30, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476568,-106.9167876,  3101.0, 2022,  6, 24, 15, 19,  9,     1035,     1996, 331,  59,   1.4,   0.8,   1.1,  0, 37, 28,  0,  0, 34,  0,  0,  0,  0, 37, 36, 32, 33,  0,  0, 32,  0, 30, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.41, 6,  drogue,  -20.59,  70975.00, 2903.30, 1573.50,  -23.67, 32.9, 1.30, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.51, 6,  drogue,  -18.14,  71023.00, 2897.97, 1568.17,  -23.65, 33.0, 1.30, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.61, 6,  drogue,  -19.12,  71016.00, 2898.74, 1568.94,  -23.59, 32.9, 1.30, 3.99, 3.98,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.62, 6,  drogue,  -19.12,  71016.00, 2898.74, 1568.94,  -23.59, 32.9, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.21,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.71, 6,  drogue,  -20.59,  71087.00, 2890.87, 1561.06,  -23.48, 32.9, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.81, 6,  drogue,  -15.20,  71076.00, 2892.09, 1562.29,  -23.34, 32.9, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.91, 6,  drogue,  -18.63,  71074.00, 2892.31, 1562.51,  -23.12, 32.9, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   113.94, 6,  drogue,  -18.63,  71074.00, 2892.31, 1562.51,  -23.12, 32.9, 1.30, 3.96, 3.97,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   114.01, 6,  drogue,  -17.65,  71100.00, 2889.42, 1559.62,  -22.93, 32.9, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   114.11, 6,  drogue,  -14.22,  71111.00, 2888.20, 1558.40,  -22.76, 32.9, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   114.21, 6,  drogue,  -12.26,  71090.00, 2890.53, 1560.73,  -22.57, 32.9, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   114.26, 6,  drogue,  -12.26,  71090.00, 2890.53, 1560.73,  -22.57, 32.9, 1.30, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476220,-106.9167671,  3075.0, 2022,  6, 24, 15, 19, 10,     1030,     1972, 331,  58,   1.4,   0.8,   1.1,  0, 31, 28,  0,  0, 40,  0,  0,  0,  0, 32, 32, 27, 36,  0,  0, 34,  0, 36, 24,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   114.31, 6,  drogue,  -14.22,  71113.00, 2887.98, 1558.18,  -22.40, 32.9, 1.30, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.31, 6,  drogue,  -14.22,  71113.00, 2887.98, 1558.18,  -22.40, 32.9, 1.30, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.31, 6,  drogue,  -14.22,  71113.00, 2887.98, 1558.18,  -22.40, 32.9, 1.30, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.41, 6,  drogue,  -20.10,  71167.00, 2882.00, 1552.20,  -22.20, 32.9, 1.30, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.51, 6,  drogue,  -15.20,  71206.00, 2877.68, 1547.88,  -22.01, 32.9, 1.30, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.58, 6,  drogue,  -15.20,  71206.00, 2877.68, 1547.88,  -22.01, 32.9, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.61, 6,  drogue,  -14.71,  71231.00, 2874.91, 1545.11,  -21.89, 32.9, 1.31, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.71, 6,  drogue,  -13.73,  71263.00, 2871.36, 1541.56,  -21.82, 32.9, 1.31, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.81, 6,  drogue,  -13.24,  71279.00, 2869.59, 1539.79,  -21.85, 32.9, 1.31, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.90, 6,  drogue,  -13.24,  71279.00, 2869.59, 1539.79,  -21.85, 32.9, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   114.91, 6,  drogue,  -17.16,  71268.00, 2870.81, 1541.01,  -21.96, 32.9, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.01, 6,  drogue,  -19.12,  71290.00, 2868.38, 1538.58,  -22.12, 32.9, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.11, 6,  drogue,  -22.06,  71319.00, 2865.17, 1535.37,  -22.37, 32.9, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.21, 6,  drogue,  -19.12,  71345.00, 2862.29, 1532.49,  -22.65, 32.9, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.22, 6,  drogue,  -19.12,  71345.00, 2862.29, 1532.49,  -22.65, 32.9, 1.31, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475918,-106.9167403,  3047.0, 2022,  6, 24, 15, 19, 11,     1026,     1946, 331,  58,   1.4,   0.8,   1.1,  0, 28, 29,  0,  0, 37,  0,  0,  0,  0, 28, 27, 27, 38,  0,  0, 27,  0, 29, 23,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.31, 6,  drogue,  -18.63,  71379.00, 2858.53, 1528.73,  -22.99, 32.9, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.31, 6,  drogue,  -18.63,  71379.00, 2858.53, 1528.73,  -22.99, 32.9, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.31, 6,  drogue,  -18.63,  71379.00, 2858.53, 1528.73,  -22.99, 32.9, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.41, 6,  drogue,  -18.63,  71416.00, 2854.44, 1524.64,  -23.38, 32.9, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.51, 6,  drogue,  -18.14,  71384.00, 2857.98, 1528.18,  -23.82, 32.9, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.54, 6,  drogue,  -18.14,  71384.00, 2857.98, 1528.18,  -23.82, 32.9, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.61, 6,  drogue,  -17.16,  71326.00, 2864.39, 1534.59,  -24.27, 32.9, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.71, 6,  drogue,  -17.65,  71332.00, 2863.73, 1533.93,  -24.73, 32.9, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.81, 6,  drogue,  -12.75,  71394.00, 2856.87, 1527.07,  -25.15, 32.9, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.86, 6,  drogue,  -12.75,  71394.00, 2856.87, 1527.07,  -25.15, 32.9, 1.31, 3.97, 3.97,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   115.91, 6,  drogue,  -10.30,  71414.00, 2854.66, 1524.86,  -25.54, 32.9, 1.31, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   116.01, 6,  drogue,  -11.77,  71541.00, 2840.64, 1510.84,  -25.97, 32.9, 1.31, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   116.11, 6,  drogue,  -15.20,  71568.00, 2837.66, 1507.86,  -26.35, 32.9, 1.31, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   116.18, 6,  drogue,  -15.20,  71568.00, 2837.66, 1507.86,  -26.35, 32.9, 1.32, 3.99, 3.99,   0.00,   0.00,   0.00,  63.91,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   116.21, 6,  drogue,  -13.73,  71545.00, 2840.20, 1510.40,  -26.68, 32.9, 1.32, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475673,-106.9167141,  3020.0, 2022,  6, 24, 15, 19, 12,     1023,     1921, 331,  58,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 37,  0,  0,  0,  0, 34, 28, 33, 32,  0,  0, 37,  0, 37, 30,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   116.31, 6,  drogue,  -16.67,  71585.00, 2835.79, 1505.99,  -26.99, 32.9, 1.32, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.31, 6,  drogue,  -16.67,  71585.00, 2835.79, 1505.99,  -26.99, 32.9, 1.32, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.31, 6,  drogue,  -16.67,  71585.00, 2835.79, 1505.99,  -26.99, 32.9, 1.32, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.41, 6,  drogue,  -16.67,  71593.00, 2834.90, 1505.10,  -27.30, 32.9, 1.32, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.50, 6,  drogue,  -16.67,  71593.00, 2834.90, 1505.10,  -27.30, 32.9, 1.33, 3.99, 3.98,   0.02,   0.00,   0.00,  64.27,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.51, 6,  drogue,  -17.16,  71604.00, 2833.69, 1503.89,  -27.58, 32.9, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.61, 6,  drogue,  -20.10,  71659.00, 2827.63, 1497.83,  -27.82, 32.9, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.71, 6,  drogue,  -17.65,  71728.00, 2820.03, 1490.23,  -28.01, 32.9, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.81, 6,  drogue,  -11.28,  71779.00, 2814.41, 1484.61,  -28.17, 32.9, 1.33, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.82, 6,  drogue,  -11.28,  71779.00, 2814.41, 1484.61,  -28.17, 32.9, 1.31, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   116.91, 6,  drogue,  -12.75,  71742.00, 2818.49, 1488.69,  -28.30, 32.9, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   117.01, 6,  drogue,   -8.83,  71699.00, 2823.22, 1493.42,  -28.42, 32.9, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   117.11, 6,  drogue,  -19.12,  71769.00, 2815.52, 1485.71,  -28.55, 32.9, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   117.14, 6,  drogue,  -19.12,  71769.00, 2815.52, 1485.71,  -28.55, 32.9, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   117.21, 6,  drogue,  -19.61,  71770.00, 2815.41, 1485.60,  -28.63, 32.9, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475246,-106.9167041,  2992.0, 2022,  6, 24, 15, 19, 13,     1018,     1895, 331,  58,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 37, 32, 33, 28,  0,  0, 32,  0, 29, 34,  0,  0,  0, 33,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   117.31, 6,  drogue,  -21.08,  71793.00, 2812.87, 1483.07,  -28.73, 32.9, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.31, 6,  drogue,  -21.08,  71793.00, 2812.87, 1483.07,  -28.73, 32.9, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.31, 6,  drogue,  -21.08,  71793.00, 2812.87, 1483.07,  -28.73, 32.9, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.41, 6,  drogue,  -20.59,  71873.00, 2804.08, 1474.27,  -28.83, 32.9, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.46, 6,  drogue,  -20.59,  71873.00, 2804.08, 1474.27,  -28.83, 32.9, 1.31, 3.99, 3.99,   0.03,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.51, 6,  drogue,  -14.71,  71894.00, 2801.77, 1471.97,  -28.88, 32.9, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.61, 6,  drogue,  -15.20,  71936.00, 2797.15, 1467.35,  -28.89, 32.9, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.71, 6,  drogue,  -16.18,  71922.00, 2798.69, 1468.89,  -28.94, 32.8, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.78, 6,  drogue,  -16.18,  71922.00, 2798.69, 1468.89,  -28.94, 32.8, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.81, 6,  drogue,  -16.18,  71930.00, 2797.81, 1468.01,  -29.06, 32.8, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   117.91, 6,  drogue,  -11.28,  71955.00, 2795.07, 1465.26,  -29.20, 32.8, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.01, 6,  drogue,  -11.77,  72055.00, 2784.09, 1454.29,  -29.37, 32.8, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.10, 6,  drogue,  -11.77,  72055.00, 2784.09, 1454.29,  -29.37, 32.8, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.11, 6,  drogue,  -18.14,  72040.00, 2785.73, 1455.93,  -29.50, 32.8, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.21, 6,  drogue,  -14.22,  72071.00, 2782.33, 1452.53,  -29.52, 32.8, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474836,-106.9167140,  2963.0, 2022,  6, 24, 15, 19, 14,     1014,     1868, 331,  57,   1.4,   0.8,   1.1,  0, 29, 29,  0,  0, 34,  0,  0,  0,  0, 31, 33, 31, 28,  0,  0, 36,  0, 36, 31,  0,  0,  0, 29,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.31, 6,  drogue,  -17.65,  72084.00, 2780.91, 1451.11,  -29.53, 32.8, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.31, 6,  drogue,  -17.65,  72084.00, 2780.91, 1451.11,  -29.53, 32.8, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.31, 6,  drogue,  -17.65,  72084.00, 2780.91, 1451.11,  -29.53, 32.8, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.41, 6,  drogue,  -18.63,  72140.00, 2774.77, 1444.97,  -29.47, 32.8, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.42, 6,  drogue,  -18.63,  72140.00, 2774.77, 1444.97,  -29.47, 32.8, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.51, 6,  drogue,  -11.77,  72148.00, 2773.89, 1444.09,  -29.40, 32.8, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.61, 6,  drogue,  -12.75,  72184.00, 2769.95, 1440.15,  -29.33, 32.8, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.71, 6,  drogue,  -14.22,  72191.00, 2769.18, 1439.38,  -29.24, 32.8, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.74, 6,  drogue,  -14.22,  72191.00, 2769.18, 1439.38,  -29.24, 32.8, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.81, 6,  drogue,  -20.59,  72227.00, 2765.24, 1435.44,  -29.13, 32.8, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   118.91, 6,  drogue,  -17.65,  72284.00, 2759.00, 1429.20,  -28.95, 32.8, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   119.01, 6,  drogue,  -24.03,  72301.00, 2757.14, 1427.34,  -28.67, 32.8, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   119.06, 6,  drogue,  -24.03,  72301.00, 2757.14, 1427.34,  -28.67, 32.8, 1.32, 3.96, 3.98,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   119.11, 6,  drogue,  -23.05,  72357.00, 2751.01, 1421.21,  -28.37, 32.8, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   119.21, 6,  drogue,  -13.73,  72300.00, 2757.25, 1427.45,  -28.04, 32.8, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9474917,-106.9167128,  2934.0, 2022,  6, 24, 15, 19, 15,     1015,     1844, 331,  57,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 29,  0,  0,  0,  0, 31, 33, 31, 32,  0,  0, 28,  0, 29, 26,  0,  0,  0, 34,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   119.31, 6,  drogue,  -13.24,  72358.00, 2750.90, 1421.10,  -27.71, 32.8, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.31, 6,  drogue,  -13.24,  72358.00, 2750.90, 1421.10,  -27.71, 32.8, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.31, 6,  drogue,  -13.24,  72358.00, 2750.90, 1421.10,  -27.71, 32.8, 1.32, 3.96, 3.98,   0.00,   0.00,   0.00,  63.84,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.38, 6,  drogue,  -13.24,  72358.00, 2750.90, 1421.10,  -27.71, 32.8, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.41, 6,  drogue,  -13.73,  72391.00, 2747.30, 1417.50,  -27.41, 32.8, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.51, 6,  drogue,  -14.22,  72402.00, 2746.10, 1416.29,  -27.09, 32.8, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.61, 6,  drogue,   -8.34,  72422.00, 2743.91, 1414.11,  -26.81, 32.8, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.70, 6,  drogue,   -8.34,  72422.00, 2743.91, 1414.11,  -26.81, 32.8, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.71, 6,  drogue,  -13.24,  72488.00, 2736.70, 1406.90,  -26.47, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.81, 6,  drogue,  -21.08,  72545.00, 2730.48, 1400.68,  -26.14, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   119.91, 6,  drogue,  -16.67,  72568.00, 2727.97, 1398.17,  -25.81, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   120.01, 6,  drogue,  -23.05,  72565.00, 2728.30, 1398.50,  -25.54, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   120.02, 6,  drogue,  -23.05,  72565.00, 2728.30, 1398.50,  -25.54, 32.8, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   120.11, 6,  drogue,  -17.16,  72557.00, 2729.17, 1399.37,  -25.26, 32.8, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   120.21, 6,  drogue,  -12.75,  72523.00, 2732.88, 1403.08,  -25.00, 32.8, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475378,-106.9166798,  2906.0, 2022,  6, 24, 15, 19, 16,     1018,     1823, 331,  56,   1.4,   0.8,   1.1,  0, 36, 34,  0,  0, 36,  0,  0,  0,  0, 37, 26, 25, 27,  0,  0, 40,  0, 38, 31,  0,  0,  0, 31,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   120.31, 6,  drogue,  -17.16,  72575.00, 2727.21, 1397.41,  -24.79, 32.8, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.31, 6,  drogue,  -17.16,  72575.00, 2727.21, 1397.41,  -24.79, 32.8, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.31, 6,  drogue,  -17.16,  72575.00, 2727.21, 1397.41,  -24.79, 32.8, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.34, 6,  drogue,  -17.16,  72575.00, 2727.21, 1397.41,  -24.79, 32.8, 1.31, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.41, 6,  drogue,  -18.14,  72599.00, 2724.59, 1394.79,  -24.64, 32.8, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.51, 6,  drogue,  -13.73,  72667.00, 2717.18, 1387.38,  -24.49, 32.8, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.61, 6,  drogue,  -15.69,  72703.00, 2713.26, 1383.46,  -24.40, 32.8, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.66, 6,  drogue,  -15.69,  72703.00, 2713.26, 1383.46,  -24.40, 32.8, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.09,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.71, 6,  drogue,  -15.20,  72722.00, 2711.19, 1381.39,  -24.29, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.81, 6,  drogue,  -16.18,  72751.00, 2708.03, 1378.23,  -24.24, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.91, 6,  drogue,  -17.65,  72780.00, 2704.87, 1375.07,  -24.24, 32.8, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   120.98, 6,  drogue,  -17.65,  72780.00, 2704.87, 1375.07,  -24.24, 32.8, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   121.01, 6,  drogue,  -19.12,  72725.00, 2710.86, 1381.06,  -24.28, 32.8, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   121.11, 6,  drogue,  -17.65,  72723.00, 2711.08, 1381.28,  -24.39, 32.8, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   121.21, 6,  drogue,  -22.06,  72762.00, 2706.83, 1377.03,  -24.49, 32.8, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   121.30, 6,  drogue,  -22.06,  72762.00, 2706.83, 1377.03,  -24.49, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9475727,-106.9166208,  2878.0, 2022,  6, 24, 15, 19, 17,     1019,     1800, 332,  56,   1.4,   0.8,   1.1,  0, 30, 26,  0,  0, 33,  0,  0,  0,  0, 25, 32, 30, 34,  0,  0, 39,  0, 37, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   121.31, 6,  drogue,  -19.61,  72817.00, 2700.85, 1371.05,  -24.66, 32.8, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.31, 6,  drogue,  -19.61,  72817.00, 2700.85, 1371.05,  -24.66, 32.8, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.31, 6,  drogue,  -19.61,  72817.00, 2700.85, 1371.05,  -24.66, 32.8, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.41, 6,  drogue,  -17.65,  72859.00, 2696.28, 1366.48,  -24.87, 32.8, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.51, 6,  drogue,  -14.22,  72875.00, 2694.54, 1364.74,  -25.10, 32.8, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.61, 6,  drogue,  -16.18,  72944.00, 2687.04, 1357.24,  -25.32, 32.8, 1.30, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.62, 6,  drogue,  -16.18,  72944.00, 2687.04, 1357.24,  -25.32, 32.8, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.71, 6,  drogue,  -18.14,  72912.00, 2690.52, 1360.72,  -25.56, 32.8, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.81, 6,  drogue,  -15.69,  72943.00, 2687.15, 1357.35,  -25.81, 32.8, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.91, 6,  drogue,  -16.67,  72936.00, 2687.91, 1358.11,  -26.05, 32.8, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   121.94, 6,  drogue,  -16.67,  72936.00, 2687.91, 1358.11,  -26.05, 32.8, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.01, 6,  drogue,  -18.63,  72961.00, 2685.20, 1355.40,  -26.21, 32.8, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.11, 6,  drogue,  -16.18,  73004.00, 2680.53, 1350.73,  -26.34, 32.8, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.21, 6,  drogue,  -17.16,  73023.00, 2678.47, 1348.67,  -26.42, 32.8, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.26, 6,  drogue,  -17.16,  73023.00, 2678.47, 1348.67,  -26.42, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.30, 6,  drogue,  -17.16,  73023.00, 2678.47, 1348.67,  -26.42, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.30, 6,  drogue,  -17.16,  73023.00, 2678.47, 1348.67,  -26.42, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475770,-106.9165638,  2851.0, 2022,  6, 24, 15, 19, 18,     1017,     1777, 332,  55,   1.4,   0.8,   1.1,  0, 34, 31,  0,  0, 33,  0,  0,  0,  0, 34, 36, 36, 33,  0,  0, 27,  0, 24, 33,  0,  0,  0, 34,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   122.31, 6,  drogue,  -16.18,  73077.00, 2672.61, 1342.81,  -26.49, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.41, 6,  drogue,  -12.26,  73117.00, 2668.27, 1338.47,  -26.54, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.51, 6,  drogue,  -14.71,  73101.00, 2670.01, 1340.20,  -26.57, 32.8, 1.30, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.58, 6,  drogue,  -14.71,  73101.00, 2670.01, 1340.20,  -26.57, 32.8, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.61, 6,  drogue,  -17.16,  73137.00, 2666.10, 1336.30,  -26.61, 32.8, 1.29, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.71, 6,  drogue,  -19.12,  73109.00, 2669.14, 1339.34,  -26.59, 32.8, 1.29, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.81, 6,  drogue,  -14.71,  73159.00, 2663.72, 1333.92,  -26.52, 32.8, 1.29, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.90, 6,  drogue,  -14.71,  73159.00, 2663.72, 1333.92,  -26.52, 32.8, 1.29, 3.97, 3.97,   0.08,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   122.91, 6,  drogue,  -20.10,  73201.00, 2659.17, 1329.37,  -26.44, 32.8, 1.29, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   123.01, 6,  drogue,  -17.16,  73249.00, 2653.97, 1324.17,  -26.25, 32.8, 1.29, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   123.11, 6,  drogue,  -15.69,  73305.00, 2647.91, 1318.11,  -26.04, 32.8, 1.29, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   123.21, 6,  drogue,  -18.63,  73332.00, 2644.99, 1315.19,  -25.84, 32.8, 1.29, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   123.22, 6,  drogue,  -18.63,  73332.00, 2644.99, 1315.19,  -25.84, 32.8, 1.28, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9475804,-106.9165371,  2824.0, 2022,  6, 24, 15, 19, 19,     1016,     1754, 332,  55,   1.4,   0.8,   1.1,  0, 31, 32,  0,  0, 31,  0,  0,  0,  0, 30, 37, 30, 28,  0,  0, 29,  0, 26, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   123.31, 6,  drogue,  -19.61,  73345.00, 2643.58, 1313.78,  -25.66, 32.8, 1.28, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.31, 6,  drogue,  -19.61,  73345.00, 2643.58, 1313.78,  -25.66, 32.8, 1.28, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.31, 6,  drogue,  -19.61,  73345.00, 2643.58, 1313.78,  -25.66, 32.8, 1.28, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.41, 6,  drogue,  -20.59,  73377.00, 2640.12, 1310.32,  -25.49, 32.7, 1.28, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.51, 6,  drogue,  -22.56,  73374.00, 2640.45, 1310.65,  -25.33, 32.7, 1.28, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.54, 6,  drogue,  -22.56,  73374.00, 2640.45, 1310.65,  -25.33, 32.7, 1.30, 3.99, 3.98,   0.02,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.61, 6,  drogue,  -18.63,  73366.00, 2641.31, 1311.51,  -25.22, 32.8, 1.30, 3.99, 3.98,   0.00,   0.00,   0.04,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.71, 6,  drogue,  -15.69,  73377.00, 2640.12, 1310.32,  -25.11, 32.7, 1.30, 3.99, 3.98,   0.00,   0.00,   0.04,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.81, 6,  drogue,  -14.22,  73411.00, 2636.45, 1306.65,  -25.04, 32.7, 1.30, 3.99, 3.98,   0.00,   0.00,   0.04,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.86, 6,  drogue,  -14.22,  73411.00, 2636.45, 1306.65,  -25.04, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.04,  64.21,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   123.91, 6,  drogue,  -17.65,  73442.00, 2633.10, 1303.30,  -25.02, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.01, 6,  drogue,  -15.20,  73436.00, 2633.75, 1303.95,  -25.06, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.11, 6,  drogue,  -15.20,  73473.00, 2629.75, 1299.95,  -25.19, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.18, 6,  drogue,  -15.20,  73473.00, 2629.75, 1299.95,  -25.19, 32.7, 1.30, 3.96, 3.97,   0.02,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.21, 6,  drogue,  -14.71,  73509.00, 2625.87, 1296.06,  -25.37, 32.7, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.30, 6,  drogue,  -14.71,  73509.00, 2625.87, 1296.06,  -25.37, 32.7, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.30, 6,  drogue,  -14.71,  73509.00, 2625.87, 1296.06,  -25.37, 32.7, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476022,-106.9165282,  2797.0, 2022,  6, 24, 15, 19, 20,     1018,     1733, 332,  54,   1.4,   0.8,   1.1,  0, 26, 28,  0,  0, 38,  0,  0,  0,  0, 26, 31, 26, 32,  0,  0, 36,  0, 38, 22,  0,  0,  0, 32,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   124.31, 6,  drogue,  -14.71,  73535.00, 2623.06, 1293.26,  -25.63, 32.7, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.41, 6,  drogue,  -15.69,  73560.00, 2620.36, 1290.56,  -25.93, 32.7, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.50, 6,  drogue,  -15.69,  73560.00, 2620.36, 1290.56,  -25.93, 32.7, 1.28, 3.97, 3.98,   0.00,   0.00,   0.00,  63.84,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.51, 6,  drogue,  -13.24,  73583.00, 2617.88, 1288.08,  -26.23, 32.7, 1.28, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.61, 6,  drogue,  -15.69,  73663.00, 2609.26, 1279.45,  -26.57, 32.7, 1.28, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.71, 6,  drogue,  -16.18,  73656.00, 2610.01, 1280.21,  -26.88, 32.7, 1.28, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.81, 6,  drogue,  -16.18,  73659.00, 2609.69, 1279.89,  -27.25, 32.7, 1.28, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.82, 6,  drogue,  -16.18,  73659.00, 2609.69, 1279.89,  -27.25, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   124.91, 6,  drogue,  -20.10,  73691.00, 2606.24, 1276.44,  -27.66, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   125.01, 6,  drogue,  -19.12,  73668.00, 2608.72, 1278.92,  -28.07, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   125.11, 6,  drogue,  -20.59,  73694.00, 2605.92, 1276.11,  -28.49, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   125.14, 6,  drogue,  -20.59,  73694.00, 2605.92, 1276.11,  -28.49, 32.7, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   125.21, 6,  drogue,  -18.14,  73711.00, 2604.08, 1274.28,  -28.87, 32.7, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476254,-106.9164992,  2771.0, 2022,  6, 24, 15, 19, 21,     1019,     1713, 332,  54,   1.4,   0.8,   1.1,  0, 36, 28,  0,  0, 39,  0,  0,  0,  0, 37, 30, 24, 32,  0,  0, 37,  0, 38, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   125.31, 6,  drogue,  -20.10,  73758.00, 2599.02, 1269.22,  -29.20, 32.7, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.31, 6,  drogue,  -20.10,  73758.00, 2599.02, 1269.22,  -29.20, 32.7, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.31, 6,  drogue,  -20.10,  73758.00, 2599.02, 1269.22,  -29.20, 32.7, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.41, 6,  drogue,  -15.20,  73796.00, 2594.93, 1265.13,  -29.48, 32.7, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.46, 6,  drogue,  -15.20,  73796.00, 2594.93, 1265.13,  -29.48, 32.7, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.51, 6,  drogue,  -16.67,  73834.00, 2590.85, 1261.04,  -29.71, 32.7, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.61, 6,  drogue,  -13.24,  73877.00, 2586.22, 1256.42,  -29.87, 32.7, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.71, 6,  drogue,  -16.67,  73910.00, 2582.67, 1252.87,  -29.97, 32.7, 1.30, 3.99, 3.99,   0.02,   0.00,   0.00,  64.27,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.78, 6,  drogue,  -16.67,  73910.00, 2582.67, 1252.87,  -29.97, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.27,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.81, 6,  drogue,  -17.65,  73940.00, 2579.45, 1249.65,  -30.01, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   125.91, 6,  drogue,  -19.61,  73977.00, 2575.48, 1245.68,  -29.98, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   126.01, 6,  drogue,  -19.61,  74017.00, 2571.18, 1241.38,  -29.83, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   126.10, 6,  drogue,  -19.61,  74017.00, 2571.18, 1241.38,  -29.83, 32.7, 1.29, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   126.11, 6,  drogue,  -17.16,  74045.00, 2568.18, 1238.38,  -29.64, 32.7, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   126.21, 6,  drogue,  -20.59,  74062.00, 2566.35, 1236.55,  -29.40, 32.7, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476320,-106.9164429,  2744.0, 2022,  6, 24, 15, 19, 22,     1017,     1690, 333,  53,   1.4,   0.8,   1.1,  0, 39, 26,  0,  0, 34,  0,  0,  0,  0, 38, 27, 37, 36,  0,  0, 35,  0, 31, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   126.31, 6,  drogue,  -17.16,  74094.00, 2562.92, 1233.12,  -29.11, 32.7, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.31, 6,  drogue,  -17.16,  74094.00, 2562.92, 1233.12,  -29.11, 32.7, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.31, 6,  drogue,  -17.16,  74094.00, 2562.92, 1233.12,  -29.11, 32.7, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.41, 6,  drogue,  -14.71,  74095.00, 2562.81, 1233.01,  -28.78, 32.7, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.42, 6,  drogue,  -14.71,  74095.00, 2562.81, 1233.01,  -28.78, 32.7, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.51, 6,  drogue,  -18.14,  74109.00, 2561.31, 1231.51,  -28.42, 32.7, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.61, 6,  drogue,  -16.67,  74131.00, 2558.95, 1229.15,  -28.06, 32.7, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.71, 6,  drogue,  -18.63,  74131.00, 2558.95, 1229.15,  -27.66, 32.7, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.74, 6,  drogue,  -18.63,  74131.00, 2558.95, 1229.15,  -27.66, 32.7, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.81, 6,  drogue,  -15.69,  74218.00, 2549.63, 1219.83,  -27.24, 32.7, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   126.91, 6,  drogue,  -19.61,  74258.00, 2545.35, 1215.55,  -26.80, 32.7, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   127.01, 6,  drogue,  -16.67,  74284.00, 2542.56, 1212.76,  -26.36, 32.7, 1.30, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   127.06, 6,  drogue,  -16.67,  74284.00, 2542.56, 1212.76,  -26.36, 32.7, 1.29, 3.99, 3.99,   0.03,   0.00,   0.00,  64.09,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   127.11, 6,  drogue,  -19.12,  74310.00, 2539.78, 1209.98,  -25.94, 32.7, 1.29, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   127.21, 6,  drogue,  -18.63,  74337.00, 2536.89, 1207.09,  -25.53, 32.7, 1.29, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476275,-106.9164005,  2716.0, 2022,  6, 24, 15, 19, 23,     1015,     1667, 333,  52,   1.4,   0.8,   1.1,  0, 31, 26,  0,  0, 21,  0,  0,  0,  0, 30, 37, 33, 28,  0,  0, 38,  0, 35, 29,  0,  0,  0, 34,  0,  0,  0,  0,  0, 36,  0,  0
+6, 6583, 3,VE3LIC,   127.31, 6,  drogue,  -20.59,  74353.00, 2535.18, 1205.38,  -25.19, 32.7, 1.29, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.31, 6,  drogue,  -20.59,  74353.00, 2535.18, 1205.38,  -25.19, 32.7, 1.29, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.31, 6,  drogue,  -20.59,  74353.00, 2535.18, 1205.38,  -25.19, 32.7, 1.29, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.38, 6,  drogue,  -20.59,  74353.00, 2535.18, 1205.38,  -25.19, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.21,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.41, 6,  drogue,  -21.57,  74367.00, 2533.68, 1203.88,  -24.91, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.51, 6,  drogue,  -17.16,  74397.00, 2530.48, 1200.67,  -24.71, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.61, 6,  drogue,  -22.56,  74411.00, 2528.98, 1199.18,  -24.59, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.70, 6,  drogue,  -22.56,  74411.00, 2528.98, 1199.18,  -24.59, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.71, 6,  drogue,  -20.59,  74419.00, 2528.12, 1198.32,  -24.49, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.81, 6,  drogue,  -21.08,  74426.00, 2527.38, 1197.58,  -24.43, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   127.91, 6,  drogue,  -15.69,  74437.00, 2526.20, 1196.40,  -24.40, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   128.01, 6,  drogue,  -18.14,  74423.00, 2527.70, 1197.90,  -24.41, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   128.02, 6,  drogue,  -18.14,  74423.00, 2527.70, 1197.90,  -24.41, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   128.11, 6,  drogue,  -17.16,  74467.00, 2523.00, 1193.19,  -24.42, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   128.21, 6,  drogue,  -15.20,  74519.00, 2517.44, 1187.64,  -24.46, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9476299,-106.9163762,  2688.0, 2022,  6, 24, 15, 19, 24,     1014,     1644, 333,  52,   1.7,   0.9,   1.4,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 34, 38, 27, 30,  0,  0, 28,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   128.31, 6,  drogue,  -20.10,  74565.00, 2512.53, 1182.73,  -24.49, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.31, 6,  drogue,  -20.10,  74565.00, 2512.53, 1182.73,  -24.49, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.31, 6,  drogue,  -20.10,  74565.00, 2512.53, 1182.73,  -24.49, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.34, 6,  drogue,  -20.10,  74565.00, 2512.53, 1182.73,  -24.49, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.41, 6,  drogue,  -14.71,  74590.00, 2509.87, 1180.06,  -24.51, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.51, 6,  drogue,  -15.69,  74637.00, 2504.85, 1175.05,  -24.54, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.61, 6,  drogue,  -18.63,  74658.00, 2502.61, 1172.81,  -24.58, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.66, 6,  drogue,  -18.63,  74658.00, 2502.61, 1172.81,  -24.58, 32.7, 1.29, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.71, 6,  drogue,  -18.63,  74667.00, 2501.65, 1171.85,  -24.58, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.81, 6,  drogue,  -17.65,  74685.00, 2499.74, 1169.94,  -24.60, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.91, 6,  drogue,  -15.20,  74658.00, 2502.61, 1172.81,  -24.63, 32.7, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   128.98, 6,  drogue,  -15.20,  74658.00, 2502.61, 1172.81,  -24.63, 32.7, 1.28, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   129.01, 6,  drogue,  -21.08,  74693.00, 2498.88, 1169.08,  -24.62, 32.7, 1.28, 3.98, 3.98,   0.06,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   129.11, 6,  drogue,  -15.20,  74722.00, 2495.79, 1165.99,  -24.58, 32.7, 1.28, 3.98, 3.98,   0.06,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   129.21, 6,  drogue,  -12.26,  74706.00, 2497.50, 1167.70,  -24.51, 32.7, 1.28, 3.98, 3.98,   0.06,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.05, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   129.30, 6,  drogue,  -12.26,  74706.00, 2497.50, 1167.70,  -24.51, 32.7, 1.29, 3.97, 3.98,   0.06,   0.00,   0.00,  64.03,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476429,-106.9163420,  2661.0, 2022,  6, 24, 15, 19, 25,     1014,     1623, 333,  51,   1.4,   0.8,   1.1,  0, 36, 29,  0,  0, 35,  0,  0,  0,  0, 36, 33, 31, 29,  0,  0, 32,  0, 38, 20,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   129.31, 6,  drogue,  -16.18,  74777.00, 2489.94, 1160.14,  -24.40, 32.7, 1.29, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.31, 6,  drogue,  -16.18,  74777.00, 2489.94, 1160.14,  -24.40, 32.7, 1.29, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.31, 6,  drogue,  -16.18,  74777.00, 2489.94, 1160.14,  -24.40, 32.7, 1.29, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.41, 6,  drogue,  -18.14,  74816.00, 2485.79, 1155.99,  -24.25, 32.7, 1.29, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.51, 6,  drogue,  -20.10,  74890.00, 2477.91, 1148.11,  -24.09, 32.7, 1.29, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.61, 6,  drogue,  -15.20,  74922.00, 2474.51, 1144.71,  -23.91, 32.7, 1.29, 3.97, 3.98,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.62, 6,  drogue,  -15.20,  74922.00, 2474.51, 1144.71,  -23.91, 32.7, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.71, 6,  drogue,  -17.65,  74906.00, 2476.21, 1146.41,  -23.72, 32.7, 1.29, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.81, 6,  drogue,  -17.16,  74912.00, 2475.58, 1145.77,  -23.54, 32.7, 1.29, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.91, 6,  drogue,  -14.22,  74914.00, 2475.36, 1145.56,  -23.39, 32.6, 1.29, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   129.94, 6,  drogue,  -14.22,  74914.00, 2475.36, 1145.56,  -23.39, 32.6, 1.29, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   130.01, 6,  drogue,  -15.20,  74935.00, 2473.13, 1143.33,  -23.27, 32.6, 1.29, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   130.11, 6,  drogue,  -14.71,  74947.00, 2471.86, 1142.05,  -23.21, 32.6, 1.29, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   130.21, 6,  drogue,  -17.65,  74977.00, 2468.67, 1138.87,  -23.18, 32.7, 1.29, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   130.26, 6,  drogue,  -17.65,  74977.00, 2468.67, 1138.87,  -23.18, 32.7, 1.28, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.75,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476565,-106.9162833,  2633.0, 2022,  6, 24, 15, 19, 26,     1013,     1600, 333,  51,   1.4,   0.8,   1.1,  0, 34, 29,  0,  0, 35,  0,  0,  0,  0, 36, 29, 35, 37,  0,  0, 38,  0, 31, 30,  0,  0,  0, 31,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   130.31, 6,  drogue,  -16.67,  74985.00, 2467.82, 1138.02,  -23.19, 32.6, 1.28, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  20.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.31, 6,  drogue,  -16.67,  74985.00, 2467.82, 1138.02,  -23.19, 32.6, 1.28, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  20.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.31, 6,  drogue,  -16.67,  74985.00, 2467.82, 1138.02,  -23.19, 32.6, 1.28, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  20.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.41, 6,  drogue,  -23.05,  75022.00, 2463.89, 1134.09,  -23.21, 32.6, 1.28, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  20.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.51, 6,  drogue,  -23.05,  75052.00, 2460.70, 1130.90,  -23.25, 32.6, 1.28, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  20.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.58, 6,  drogue,  -23.05,  75052.00, 2460.70, 1130.90,  -23.25, 32.6, 1.29, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  20.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.61, 6,  drogue,  -20.10,  75094.00, 2456.25, 1126.45,  -23.32, 32.6, 1.29, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.71, 6,  drogue,  -17.65,  75084.00, 2457.31, 1127.51,  -23.39, 32.6, 1.29, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.81, 6,  drogue,  -15.69,  75114.00, 2454.13, 1124.32,  -23.50, 32.6, 1.29, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.90, 6,  drogue,  -15.69,  75114.00, 2454.13, 1124.32,  -23.50, 32.6, 1.28, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   130.91, 6,  drogue,  -14.22,  75166.00, 2448.61, 1118.81,  -23.61, 32.6, 1.28, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   131.01, 6,  drogue,  -14.22,  75179.00, 2447.23, 1117.43,  -23.78, 32.6, 1.28, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   131.11, 6,  drogue,  -19.12,  75190.00, 2446.07, 1116.27,  -23.97, 32.6, 1.28, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   131.21, 6,  drogue,  -19.12,  75196.00, 2445.43, 1115.63,  -24.19, 32.6, 1.28, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   131.22, 6,  drogue,  -19.12,  75196.00, 2445.43, 1115.63,  -24.19, 32.6, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  20.69,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476618,-106.9162386,  2603.0, 2022,  6, 24, 15, 19, 27,     1011,     1576, 334,  50,   1.4,   0.8,   1.1,  0, 37, 29,  0,  0, 31,  0,  0,  0,  0, 36, 36, 35, 31,  0,  0, 29,  0, 28, 31,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   131.31, 6,  drogue,  -23.54,  75206.00, 2444.37, 1114.57,  -24.42, 32.6, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.31, 6,  drogue,  -23.54,  75206.00, 2444.37, 1114.57,  -24.42, 32.6, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.31, 6,  drogue,  -23.54,  75206.00, 2444.37, 1114.57,  -24.42, 32.6, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.41, 6,  drogue,  -16.67,  75224.00, 2442.46, 1112.66,  -24.65, 32.6, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.51, 6,  drogue,  -15.20,  75243.00, 2440.45, 1110.65,  -24.88, 32.6, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.54, 6,  drogue,  -15.20,  75243.00, 2440.45, 1110.65,  -24.88, 32.6, 1.29, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  20.87,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.61, 6,  drogue,  -14.71,  75272.00, 2437.38, 1107.58,  -25.10, 32.6, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.71, 6,  drogue,  -15.69,  75292.00, 2435.26, 1105.46,  -25.27, 32.6, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.81, 6,  drogue,  -11.28,  75351.00, 2429.02, 1099.22,  -25.44, 32.6, 1.29, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.86, 6,  drogue,  -11.28,  75351.00, 2429.02, 1099.22,  -25.44, 32.6, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  20.81,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   131.91, 6,  drogue,  -11.28,  75401.00, 2423.73, 1093.93,  -25.59, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.01, 6,  drogue,   -8.34,  75432.00, 2420.45, 1090.65,  -25.73, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.11, 6,  drogue,  -11.77,  75455.00, 2418.02, 1088.22,  -25.89, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.18, 6,  drogue,  -11.77,  75455.00, 2418.02, 1088.22,  -25.89, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.21, 6,  drogue,  -17.65,  75445.00, 2419.08, 1089.28,  -26.05, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.30, 6,  drogue,  -17.65,  75445.00, 2419.08, 1089.28,  -26.05, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.30, 6,  drogue,  -17.65,  75445.00, 2419.08, 1089.28,  -26.05, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9476799,-106.9162178,  2575.0, 2022,  6, 24, 15, 19, 28,     1012,     1555, 334,  49,   1.4,   0.8,   1.1,  0, 30, 29,  0,  0, 37,  0,  0,  0,  0, 28, 28, 28, 28,  0,  0, 38,  0, 38, 24,  0,  0,  0, 23,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   132.31, 6,  drogue,  -15.69,  75470.00, 2416.44, 1086.63,  -26.20, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.41, 6,  drogue,  -21.08,  75473.00, 2416.12, 1086.32,  -26.36, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.50, 6,  drogue,  -21.08,  75473.00, 2416.12, 1086.32,  -26.36, 32.6, 1.32, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.51, 6,  drogue,  -18.63,  75472.00, 2416.22, 1086.42,  -26.50, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.61, 6,  drogue,  -17.16,  75528.00, 2410.31, 1080.51,  -26.61, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.71, 6,  drogue,  -15.20,  75544.00, 2408.62, 1078.82,  -26.66, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.81, 6,  drogue,  -14.22,  75604.00, 2402.29, 1072.49,  -26.69, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.82, 6,  drogue,  -14.22,  75604.00, 2402.29, 1072.49,  -26.69, 32.6, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   132.91, 6,  drogue,  -14.22,  75640.00, 2398.49, 1068.69,  -26.73, 32.6, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.01, 6,  drogue,  -16.67,  75669.00, 2395.43, 1065.63,  -26.71, 32.6, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.11, 6,  drogue,  -15.69,  75678.00, 2394.48, 1064.68,  -26.67, 32.6, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.14, 6,  drogue,  -15.69,  75678.00, 2394.48, 1064.68,  -26.67, 32.6, 1.31, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.21, 6,  drogue,  -18.63,  75743.00, 2387.63, 1057.83,  -26.57, 32.6, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.30, 6,  drogue,  -18.63,  75743.00, 2387.63, 1057.83,  -26.57, 32.6, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.30, 6,  drogue,  -18.63,  75743.00, 2387.63, 1057.83,  -26.57, 32.6, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9477325,-106.9161813,  2549.0, 2022,  6, 24, 15, 19, 29,     1016,     1538, 334,  49,   1.4,   0.8,   1.1,  0, 31, 33,  0,  0, 36,  0,  0,  0,  0, 32, 29, 27, 34,  0,  0, 36,  0, 32, 30,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   133.31, 6,  drogue,  -21.08,  75712.00, 2390.90, 1061.10,  -26.44, 32.6, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.41, 6,  drogue,  -21.57,  75713.00, 2390.79, 1060.99,  -26.29, 32.6, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.46, 6,  drogue,  -21.57,  75713.00, 2390.79, 1060.99,  -26.29, 32.6, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.51, 6,  drogue,  -17.16,  75730.00, 2389.00, 1059.20,  -26.11, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.61, 6,  drogue,  -20.10,  75771.00, 2384.68, 1054.88,  -25.94, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.71, 6,  drogue,  -18.14,  75811.00, 2380.47, 1050.67,  -25.76, 32.6, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.78, 6,  drogue,  -18.14,  75811.00, 2380.47, 1050.67,  -25.76, 32.6, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.81, 6,  drogue,  -16.67,  75860.00, 2375.31, 1045.51,  -25.59, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   133.91, 6,  drogue,  -15.20,  75893.00, 2371.84, 1042.04,  -25.41, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   134.01, 6,  drogue,  -16.18,  75914.00, 2369.63, 1039.83,  -25.23, 32.6, 1.31, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   134.10, 6,  drogue,  -16.18,  75914.00, 2369.63, 1039.83,  -25.23, 32.6, 1.31, 3.96, 3.97,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   134.11, 6,  drogue,  -16.18,  75974.00, 2363.32, 1033.52,  -25.02, 32.6, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   134.21, 6,  drogue,  -20.10,  75985.00, 2362.17, 1032.37,  -24.81, 32.6, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9477904,-106.9161217,  2523.0, 2022,  6, 24, 15, 19, 30,     1019,     1521, 335,  48,   1.4,   0.8,   1.1,  0, 35, 27,  0,  0, 36,  0,  0,  0,  0, 36, 26, 32, 30,  0,  0, 28,  0, 29, 32,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   134.31, 6,  drogue,  -17.16,  75991.00, 2361.54, 1031.74,  -24.61, 32.6, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.31, 6,  drogue,  -17.16,  75991.00, 2361.54, 1031.74,  -24.61, 32.6, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.31, 6,  drogue,  -17.16,  75991.00, 2361.54, 1031.74,  -24.61, 32.6, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.41, 6,  drogue,  -19.61,  76026.00, 2357.86, 1028.06,  -24.41, 32.6, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.42, 6,  drogue,  -19.61,  76026.00, 2357.86, 1028.06,  -24.41, 32.6, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.51, 6,  drogue,  -18.63,  76023.00, 2358.17, 1028.37,  -24.24, 32.6, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.61, 6,  drogue,  -17.16,  76006.00, 2359.96, 1030.16,  -24.07, 32.6, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.71, 6,  drogue,  -19.12,  76005.00, 2360.06, 1030.26,  -23.92, 32.6, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.74, 6,  drogue,  -19.12,  76005.00, 2360.06, 1030.26,  -23.92, 32.6, 1.31, 3.99, 3.98,   0.00,   0.00,   0.00,  63.78,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.81, 6,  drogue,  -22.06,  76053.00, 2355.02, 1025.22,  -23.80, 32.6, 1.31, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   134.91, 6,  drogue,  -20.10,  76107.00, 2349.35, 1019.55,  -23.67, 32.6, 1.31, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.01, 6,  drogue,  -16.67,  76118.00, 2348.20, 1018.40,  -23.53, 32.6, 1.31, 3.99, 3.98,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.06, 6,  drogue,  -16.67,  76118.00, 2348.20, 1018.40,  -23.53, 32.6, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.21,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.11, 6,  drogue,  -18.63,  76153.00, 2344.53, 1014.73,  -23.39, 32.6, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.21, 6,  drogue,  -16.18,  76150.00, 2344.84, 1015.04,  -23.30, 32.5, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.31, 6,  drogue,  -12.75,  76181.00, 2341.59, 1011.79,  -23.17, 32.6, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.31, 6,  drogue,  -12.75,  76181.00, 2341.59, 1011.79,  -23.17, 32.6, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.31, 6,  drogue,  -12.75,  76181.00, 2341.59, 1011.79,  -23.17, 32.6, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478224,-106.9160627,  2496.0, 2022,  6, 24, 15, 19, 31,     1020,     1502, 335,  47,   1.4,   0.8,   1.1,  0, 35, 28,  0,  0, 31,  0,  0,  0,  0, 33, 30, 32, 30,  0,  0, 31,  0, 33, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.38, 6,  drogue,  -12.75,  76181.00, 2341.59, 1011.79,  -23.17, 32.6, 1.31, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.41, 6,  drogue,  -16.67,  76214.00, 2338.13, 1008.33,  -23.04, 32.5, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.51, 6,  drogue,  -18.14,  76241.00, 2335.30, 1005.50,  -22.93, 32.5, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.61, 6,  drogue,  -19.12,  76290.00, 2330.17, 1000.37,  -22.86, 32.5, 1.31, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.70, 6,  drogue,  -19.12,  76290.00, 2330.17, 1000.37,  -22.86, 32.5, 1.31, 3.99, 3.99,   0.09,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.71, 6,  drogue,  -15.69,  76312.00, 2327.86,  998.06,  -22.82, 32.5, 1.31, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.81, 6,  drogue,  -21.57,  76331.00, 2325.87,  996.07,  -22.81, 32.5, 1.31, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   135.91, 6,  drogue,  -16.18,  76333.00, 2325.66,  995.86,  -22.78, 32.5, 1.31, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.01, 6,  drogue,  -18.63,  76362.00, 2322.63,  992.83,  -22.80, 32.5, 1.31, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.02, 6,  drogue,  -18.63,  76362.00, 2322.63,  992.83,  -22.80, 32.5, 1.31, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.11, 6,  drogue,  -19.12,  76359.00, 2322.94,  993.14,  -22.83, 32.5, 1.31, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.21, 6,  drogue,  -24.03,  76401.00, 2318.55,  988.75,  -22.90, 32.5, 1.31, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.30, 6,  drogue,  -24.03,  76401.00, 2318.55,  988.75,  -22.90, 32.5, 1.31, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.30, 6,  drogue,  -24.03,  76401.00, 2318.55,  988.75,  -22.90, 32.5, 1.31, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9478412,-106.9160205,  2470.0, 2022,  6, 24, 15, 19, 32,     1021,     1483, 335,  47,   1.4,   0.8,   1.1,  0, 35, 29,  0,  0, 37,  0,  0,  0,  0, 35, 28, 32, 34,  0,  0, 37,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   136.31, 6,  drogue,  -22.06,  76419.00, 2316.66,  986.86,  -23.00, 32.5, 1.31, 3.99, 3.99,   0.00,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.34, 6,  drogue,  -22.06,  76419.00, 2316.66,  986.86,  -23.00, 32.5, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.27,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.41, 6,  drogue,  -22.06,  76428.00, 2315.72,  985.92,  -23.15, 32.5, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.51, 6,  drogue,  -19.12,  76462.00, 2312.17,  982.37,  -23.33, 32.5, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.61, 6,  drogue,  -17.16,  76439.00, 2314.57,  984.77,  -23.54, 32.5, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.66, 6,  drogue,  -17.16,  76439.00, 2314.57,  984.77,  -23.54, 32.5, 1.31, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.71, 6,  drogue,  -16.67,  76471.00, 2311.23,  981.42,  -23.78, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.81, 6,  drogue,  -15.69,  76510.00, 2307.15,  977.35,  -24.01, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.91, 6,  drogue,  -17.16,  76501.00, 2308.09,  978.29,  -24.29, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   136.98, 6,  drogue,  -17.16,  76501.00, 2308.09,  978.29,  -24.29, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.01, 6,  drogue,  -15.20,  76523.00, 2305.79,  975.99,  -24.57, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.11, 6,  drogue,  -16.18,  76587.00, 2299.11,  969.30,  -24.83, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.21, 6,  drogue,  -16.18,  76629.00, 2294.72,  964.92,  -25.06, 32.5, 1.31, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9478776,-106.9159967,  2445.0, 2022,  6, 24, 15, 19, 33,     1023,     1467, 335,  46,   1.4,   0.8,   1.1,  0, 31, 35,  0,  0, 31,  0,  0,  0,  0, 30, 32, 35, 37,  0,  0, 37,  0, 23, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.30, 6,  drogue,  -16.18,  76629.00, 2294.72,  964.92,  -25.06, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.30, 6,  drogue,  -16.18,  76629.00, 2294.72,  964.92,  -25.06, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.30, 6,  drogue,  -16.18,  76629.00, 2294.72,  964.92,  -25.06, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.15,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.31, 6,  drogue,  -14.22,  76643.00, 2293.26,  963.46,  -25.27, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.41, 6,  drogue,  -16.67,  76669.00, 2290.55,  960.75,  -25.42, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.51, 6,  drogue,  -17.16,  76699.00, 2287.42,  957.62,  -25.52, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.61, 6,  drogue,  -11.77,  76722.00, 2285.02,  955.22,  -25.56, 32.5, 1.32, 3.98, 4.00,   0.03,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.03, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.62, 6,  drogue,  -11.77,  76722.00, 2285.02,  955.22,  -25.56, 32.5, 1.31, 3.98, 3.99,   0.03,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.71, 6,  drogue,  -11.77,  76755.00, 2281.58,  951.78,  -25.55, 32.5, 1.31, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.81, 6,  drogue,  -11.28,  76756.00, 2281.47,  951.67,  -25.48, 32.5, 1.31, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.91, 6,  drogue,  -13.73,  76743.00, 2282.83,  953.03,  -25.33, 32.5, 1.31, 3.98, 3.99,   0.00,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   137.94, 6,  drogue,  -13.73,  76743.00, 2282.83,  953.03,  -25.33, 32.5, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.01, 6,  drogue,  -13.73,  76825.00, 2274.29,  944.48,  -25.15, 32.5, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.11, 6,  drogue,  -20.59,  76818.00, 2275.01,  945.21,  -24.94, 32.5, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.21, 6,  drogue,  -21.08,  76875.00, 2269.08,  939.28,  -24.72, 32.5, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.26, 6,  drogue,  -21.08,  76875.00, 2269.08,  939.28,  -24.72, 32.5, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.30, 6,  drogue,  -21.08,  76875.00, 2269.08,  939.28,  -24.72, 32.5, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.30, 6,  drogue,  -21.08,  76875.00, 2269.08,  939.28,  -24.72, 32.5, 1.31, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9479338,-106.9159365,  2419.0, 2022,  6, 24, 15, 19, 34,     1027,     1451, 336,  45,   1.4,   0.8,   1.1,  0, 27, 35,  0,  0, 34,  0,  0,  0,  0, 25, 30, 26, 35,  0,  0, 38,  0, 36, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   138.31, 6,  drogue,  -16.18,  76917.00, 2264.71,  934.91,  -24.47, 32.5, 1.31, 3.99, 3.99,   0.09,   0.00,   0.00,  64.27,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.41, 6,  drogue,  -19.12,  76943.00, 2262.00,  932.20,  -24.21, 32.5, 1.31, 3.99, 3.99,   0.09,   0.00,   0.00,  64.27,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.51, 6,  drogue,  -19.61,  76966.00, 2259.61,  929.81,  -23.94, 32.5, 1.31, 3.99, 3.99,   0.09,   0.00,   0.00,  64.27,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.58, 6,  drogue,  -19.61,  76966.00, 2259.61,  929.81,  -23.94, 32.5, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.27,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.61, 6,  drogue,  -19.61,  77007.00, 2255.35,  925.55,  -23.66, 32.5, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.71, 6,  drogue,  -16.67,  76998.00, 2256.28,  926.48,  -23.39, 32.5, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.81, 6,  drogue,  -17.16,  76945.00, 2261.79,  931.99,  -23.17, 32.5, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.90, 6,  drogue,  -17.16,  76945.00, 2261.79,  931.99,  -23.17, 32.5, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   138.91, 6,  drogue,  -17.65,  77016.00, 2254.41,  924.61,  -22.97, 32.5, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   139.01, 6,  drogue,  -20.59,  77050.00, 2250.88,  921.08,  -22.82, 32.5, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   139.11, 6,  drogue,  -12.75,  77053.00, 2250.57,  920.77,  -22.71, 32.5, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   139.21, 6,  drogue,  -17.65,  77094.00, 2246.31,  916.51,  -22.64, 32.5, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   139.22, 6,  drogue,  -17.65,  77094.00, 2246.31,  916.51,  -22.64, 32.5, 1.30, 3.96, 3.97,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9479898,-106.9158558,  2393.0, 2022,  6, 24, 15, 19, 35,     1029,     1434, 336,  44,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 34,  0,  0,  0,  0, 34, 34, 32, 27,  0,  0, 28,  0, 29, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   139.31, 6,  drogue,  -17.16,  77123.00, 2243.30,  913.49,  -22.59, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.31, 6,  drogue,  -17.16,  77123.00, 2243.30,  913.49,  -22.59, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.31, 6,  drogue,  -17.16,  77123.00, 2243.30,  913.49,  -22.59, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.41, 6,  drogue,  -23.05,  77106.00, 2245.06,  915.26,  -22.61, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.51, 6,  drogue,  -18.14,  77139.00, 2241.63,  911.83,  -22.66, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.54, 6,  drogue,  -18.14,  77139.00, 2241.63,  911.83,  -22.66, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.72,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.61, 6,  drogue,  -13.73,  77145.00, 2241.01,  911.21,  -22.78, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.71, 6,  drogue,  -13.73,  77188.00, 2236.55,  906.75,  -22.92, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.81, 6,  drogue,  -16.67,  77227.00, 2232.50,  902.70,  -23.04, 32.5, 1.30, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.86, 6,  drogue,  -16.67,  77227.00, 2232.50,  902.70,  -23.04, 32.5, 1.30, 3.98, 3.98,   0.00,   0.00,   0.00,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   139.91, 6,  drogue,  -17.16,  77236.00, 2231.57,  901.77,  -23.15, 32.5, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   140.01, 6,  drogue,  -17.16,  77268.00, 2228.25,  898.45,  -23.32, 32.4, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   140.11, 6,  drogue,  -17.16,  77308.00, 2224.11,  894.30,  -23.48, 32.5, 1.30, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   140.18, 6,  drogue,  -17.16,  77308.00, 2224.11,  894.30,  -23.48, 32.5, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   140.21, 6,  drogue,  -16.67,  77334.00, 2221.41,  891.61,  -23.67, 32.5, 1.30, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9480481,-106.9157921,  2366.0, 2022,  6, 24, 15, 19, 36,     1033,     1418, 337,  43,   1.4,   0.8,   1.1,  0, 33, 32,  0,  0, 36,  0,  0,  0,  0, 34, 36, 27, 35,  0,  0, 34,  0, 32, 27,  0,  0,  0, 36,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   140.31, 6,  drogue,  -14.71,  77336.00, 2221.20,  891.40,  -23.85, 32.4, 1.30, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.31, 6,  drogue,  -14.71,  77336.00, 2221.20,  891.40,  -23.85, 32.4, 1.30, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.31, 6,  drogue,  -14.71,  77336.00, 2221.20,  891.40,  -23.85, 32.4, 1.30, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.41, 6,  drogue,  -11.28,  77347.00, 2220.06,  890.26,  -24.00, 32.4, 1.30, 3.98, 3.99,   0.01,   0.00,   0.00,  64.09,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.50, 6,  drogue,  -11.28,  77347.00, 2220.06,  890.26,  -24.00, 32.4, 1.30, 3.98, 3.98,   0.01,   0.00,   0.00,  64.09,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.51, 6,  drogue,  -11.28,  77346.00, 2220.17,  890.37,  -24.14, 32.4, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.61, 6,  drogue,  -13.24,  77372.00, 2217.48,  887.67,  -24.27, 32.4, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.71, 6,  drogue,  -15.20,  77384.00, 2216.23,  886.43,  -24.32, 32.4, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.81, 6,  drogue,  -14.22,  77425.00, 2211.99,  882.19,  -24.34, 32.4, 1.30, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.82, 6,  drogue,  -14.22,  77425.00, 2211.99,  882.19,  -24.34, 32.4, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   140.91, 6,  drogue,   -7.85,  77486.00, 2205.68,  875.88,  -24.39, 32.4, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.01, 6,  drogue,   -8.83,  77502.00, 2204.02,  874.22,  -24.41, 32.4, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.11, 6,  drogue,  -14.22,  77498.00, 2204.44,  874.63,  -24.42, 32.4, 1.31, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.14, 6,  drogue,  -14.22,  77498.00, 2204.44,  874.63,  -24.42, 32.4, 1.30, 3.96, 3.97,   0.02,   0.00,   0.00,  64.15,  21.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.21, 6,  drogue,  -17.16,  77527.00, 2201.44,  871.64,  -24.44, 32.4, 1.30, 3.96, 3.97,   0.00,   0.00,   0.04,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.30, 6,  drogue,  -17.16,  77527.00, 2201.44,  871.64,  -24.44, 32.4, 1.30, 3.96, 3.97,   0.00,   0.00,   0.04,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.30, 6,  drogue,  -17.16,  77527.00, 2201.44,  871.64,  -24.44, 32.4, 1.30, 3.96, 3.97,   0.00,   0.00,   0.04,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.03, 1, 1, 11,  32.9481218,-106.9157641,  2341.0, 2022,  6, 24, 15, 19, 37,     1039,     1406, 337,  42,   1.4,   0.8,   1.1,  0, 29, 31,  0,  0, 36,  0,  0,  0,  0, 30, 29, 28, 32,  0,  0, 39,  0, 38, 28,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   141.31, 6,  drogue,  -16.18,  77558.00, 2198.23,  868.43,  -24.47, 32.4, 1.30, 3.96, 3.97,   0.00,   0.00,   0.04,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.41, 6,  drogue,  -22.56,  77634.00, 2190.38,  860.58,  -24.51, 32.4, 1.30, 3.96, 3.97,   0.00,   0.00,   0.04,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.46, 6,  drogue,  -22.56,  77634.00, 2190.38,  860.58,  -24.51, 32.4, 1.30, 3.98, 3.99,   0.00,   0.00,   0.04,  63.84,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.51, 6,  drogue,  -16.18,  77645.00, 2189.24,  859.44,  -24.57, 32.4, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.61, 6,  drogue,  -14.71,  77707.00, 2182.84,  853.04,  -24.63, 32.4, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.71, 6,  drogue,  -18.14,  77676.00, 2186.04,  856.24,  -24.69, 32.4, 1.30, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.78, 6,  drogue,  -18.14,  77676.00, 2186.04,  856.24,  -24.69, 32.4, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.15,  20.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.81, 6,  drogue,  -21.08,  77653.00, 2188.42,  858.62,  -24.74, 32.4, 1.33, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   141.91, 6,  drogue,  -21.08,  77675.00, 2186.15,  856.35,  -24.78, 32.4, 1.33, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.01, 6,  drogue,  -18.63,  77716.00, 2181.91,  852.11,  -24.83, 32.4, 1.33, 3.99, 3.99,   0.03,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.10, 6,  drogue,  -18.63,  77716.00, 2181.91,  852.11,  -24.83, 32.4, 1.32, 3.98, 3.98,   0.03,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.11, 6,  drogue,  -20.10,  77746.00, 2178.82,  849.02,  -24.88, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.21, 6,  drogue,  -17.65,  77785.00, 2174.80,  845.00,  -24.94, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.30, 6,  drogue,  -17.65,  77785.00, 2174.80,  845.00,  -24.94, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.30, 6,  drogue,  -17.65,  77785.00, 2174.80,  845.00,  -24.94, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482037,-106.9157540,  2315.0, 2022,  6, 24, 15, 19, 38,     1047,     1395, 337,  41,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 35,  0,  0,  0,  0, 24, 30, 28, 33,  0,  0, 39,  0, 38, 32,  0,  0,  0, 29,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   142.31, 6,  drogue,  -23.05,  77786.00, 2174.69,  844.89,  -25.00, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.41, 6,  drogue,  -21.08,  77811.00, 2172.12,  842.32,  -25.03, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.42, 6,  drogue,  -21.08,  77811.00, 2172.12,  842.32,  -25.03, 32.4, 1.32, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.51, 6,  drogue,  -18.14,  77845.00, 2168.61,  838.81,  -25.03, 32.4, 1.32, 3.97, 3.98,   0.03,   0.00,   0.00,  63.97,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.61, 6,  drogue,  -21.08,  77876.00, 2165.42,  835.62,  -25.03, 32.4, 1.32, 3.97, 3.98,   0.03,   0.00,   0.00,  63.97,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.71, 6,  drogue,  -16.67,  77849.00, 2168.20,  838.40,  -24.96, 32.4, 1.32, 3.97, 3.98,   0.03,   0.00,   0.00,  63.97,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.74, 6,  drogue,  -16.67,  77849.00, 2168.20,  838.40,  -24.96, 32.4, 1.32, 3.98, 3.99,   0.03,   0.00,   0.00,  63.97,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.81, 6,  drogue,  -12.75,  77932.00, 2159.65,  829.85,  -24.82, 32.4, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   142.91, 6,  drogue,  -18.14,  77959.00, 2156.87,  827.07,  -24.64, 32.4, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.01, 6,  drogue,  -14.71,  77961.00, 2156.67,  826.87,  -24.43, 32.4, 1.32, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.06, 6,  drogue,  -14.71,  77961.00, 2156.67,  826.87,  -24.43, 32.4, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.11, 6,  drogue,  -14.71,  78006.00, 2152.04,  822.23,  -24.18, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.21, 6,  drogue,  -16.18,  78038.00, 2148.74,  818.94,  -23.90, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.30, 6,  drogue,  -16.18,  78038.00, 2148.74,  818.94,  -23.90, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.30, 6,  drogue,  -16.18,  78038.00, 2148.74,  818.94,  -23.90, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9482699,-106.9157401,  2289.0, 2022,  6, 24, 15, 19, 39,     1054,     1383, 338,  40,   1.6,   0.8,   1.4,  0, 35, 29,  0,  0, 38,  0,  0,  0,  0, 37, 34, 29, 35,  0,  0, 35,  0, 37, 36,  0,  0,  0, 30,  0,  0,  0,  0,  0, 37,  0,  0
+6, 6583, 3,VE3LIC,   143.31, 6,  drogue,  -19.61,  78083.00, 2144.12,  814.32,  -23.59, 32.4, 1.32, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.38, 6,  drogue,  -19.61,  78083.00, 2144.12,  814.32,  -23.59, 32.4, 1.32, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.41, 6,  drogue,  -19.61,  78142.00, 2138.05,  808.25,  -23.30, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.51, 6,  drogue,  -18.14,  78142.00, 2138.05,  808.25,  -22.92, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.61, 6,  drogue,  -17.16,  78143.00, 2137.95,  808.15,  -22.57, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.70, 6,  drogue,  -17.16,  78143.00, 2137.95,  808.15,  -22.57, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.24,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.71, 6,  drogue,  -11.28,  78124.00, 2139.90,  810.10,  -22.21, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.81, 6,  drogue,   -4.90,  78117.00, 2140.62,  810.82,  -21.89, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   143.91, 6,  drogue,   -2.94,  78154.00, 2136.82,  807.02,  -21.63, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.01, 6,  drogue,  -11.28,  78186.00, 2133.53,  803.73,  -21.38, 32.4, 1.32, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.02, 6,  drogue,  -11.28,  78186.00, 2133.53,  803.73,  -21.38, 32.4, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.11, 6,  drogue,  -12.75,  78217.00, 2130.35,  800.55,  -21.23, 32.4, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.21, 6,  drogue,  -11.77,  78274.00, 2124.50,  794.70,  -21.13, 32.4, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.30, 6,  drogue,  -11.77,  78274.00, 2124.50,  794.70,  -21.13, 32.4, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.30, 6,  drogue,  -11.77,  78274.00, 2124.50,  794.70,  -21.13, 32.4, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483001,-106.9157315,  2262.0, 2022,  6, 24, 15, 19, 40,     1057,     1367, 338,  39,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 35,  0,  0,  0,  0, 39, 29, 34, 26,  0,  0, 28,  0, 30, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   144.31, 6,  drogue,  -18.14,  78310.00, 2120.81,  791.01,  -21.04, 32.4, 1.32, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.34, 6,  drogue,  -18.14,  78310.00, 2120.81,  791.01,  -21.04, 32.4, 1.31, 3.96, 3.97,   0.02,   0.00,   0.00,  64.03,  21.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.41, 6,  drogue,  -17.16,  78309.00, 2120.91,  791.11,  -21.03, 32.4, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.51, 6,  drogue,   -6.37,  78308.00, 2121.02,  791.21,  -21.14, 32.4, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.61, 6,  drogue,   -8.34,  78359.00, 2115.79,  785.99,  -21.33, 32.4, 1.31, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.66, 6,  drogue,   -8.34,  78359.00, 2115.79,  785.99,  -21.33, 32.4, 1.30, 3.97, 3.97,   0.00,   0.00,   0.00,  63.78,  21.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.71, 6,  drogue,  -18.63,  78293.00, 2122.55,  792.75,  -21.56, 32.4, 1.30, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.81, 6,  drogue,  -16.67,  78271.00, 2124.81,  795.01,  -21.85, 32.4, 1.30, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.91, 6,  drogue,  -17.16,  78307.00, 2121.12,  791.32,  -22.20, 32.3, 1.30, 3.97, 3.97,   0.00,   0.00,   0.00,  63.97,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   144.98, 6,  drogue,  -17.16,  78307.00, 2121.12,  791.32,  -22.20, 32.3, 1.33, 3.98, 3.98,   0.00,   0.00,   0.00,  63.97,  21.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   145.01, 6,  drogue,  -15.69,  78390.00, 2112.61,  782.81,  -22.61, 32.4, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   145.11, 6,  drogue,  -15.69,  78437.00, 2107.79,  777.99,  -23.04, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   145.21, 6,  drogue,  -19.61,  78467.00, 2104.72,  774.92,  -23.45, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483134,-106.9157320,  2237.0, 2022,  6, 24, 15, 19, 41,     1058,     1353, 338,  39,   1.6,   0.8,   1.4,  0, 37, 33,  0,  0, 35,  0,  0,  0,  0, 36, 30, 37, 31,  0,  0, 29,  0, 32, 33,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   145.30, 6,  drogue,  -19.61,  78467.00, 2104.72,  774.92,  -23.45, 32.3, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.30, 6,  drogue,  -19.61,  78467.00, 2104.72,  774.92,  -23.45, 32.3, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.30, 6,  drogue,  -19.61,  78467.00, 2104.72,  774.92,  -23.45, 32.3, 1.32, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.31, 6,  drogue,  -11.77,  78483.00, 2103.08,  773.28,  -23.88, 32.3, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.41, 6,  drogue,   -9.81,  78517.00, 2099.60,  769.80,  -24.33, 32.3, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.51, 6,  drogue,   -3.92,  78449.00, 2106.57,  776.76,  -24.68, 32.3, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.61, 6,  drogue,  -15.69,  78520.00, 2099.30,  769.50,  -24.94, 32.3, 1.32, 3.98, 3.98,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.62, 6,  drogue,  -15.69,  78520.00, 2099.30,  769.50,  -24.94, 32.3, 1.33, 3.99, 3.99,   0.09,   0.00,   0.00,  64.15,  21.30,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.71, 6,  drogue,  -16.67,  78581.00, 2093.06,  763.26,  -25.11, 32.3, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.81, 6,  drogue,  -15.69,  78651.00, 2085.90,  756.10,  -25.28, 32.3, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.91, 6,  drogue,  -15.69,  78647.00, 2086.31,  756.51,  -25.41, 32.3, 1.33, 3.99, 3.99,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   145.94, 6,  drogue,  -15.69,  78647.00, 2086.31,  756.51,  -25.41, 32.3, 1.33, 3.98, 3.98,   0.02,   0.00,   0.00,  64.21,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.01, 6,  drogue,   -9.32,  78596.00, 2091.52,  761.72,  -25.48, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.11, 6,  drogue,  -10.79,  78658.00, 2085.19,  755.38,  -25.49, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.21, 6,  drogue,  -20.59,  78669.00, 2084.06,  754.26,  -25.43, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.26, 6,  drogue,  -20.59,  78669.00, 2084.06,  754.26,  -25.43, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.31, 6,  drogue,  -16.18,  78638.00, 2087.23,  757.43,  -25.27, 32.3, 1.33, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.31, 6,  drogue,  -16.18,  78638.00, 2087.23,  757.43,  -25.27, 32.3, 1.33, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.31, 6,  drogue,  -16.18,  78638.00, 2087.23,  757.43,  -25.27, 32.3, 1.33, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483382,-106.9157356,  2212.0, 2022,  6, 24, 15, 19, 42,     1061,     1339, 338,  38,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 30,  0,  0,  0,  0, 33, 32, 33, 33,  0,  0, 36,  0, 35, 32,  0,  0,  0, 30,  0,  0,  0,  0,  0, 26,  0,  0
+6, 6583, 3,VE3LIC,   146.41, 6,  drogue,  -14.71,  78711.00, 2079.77,  749.97,  -25.08, 32.3, 1.33, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.51, 6,  drogue,   -6.37,  78823.00, 2068.34,  738.54,  -24.78, 32.3, 1.33, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.58, 6,  drogue,   -6.37,  78823.00, 2068.34,  738.54,  -24.78, 32.3, 1.34, 3.98, 3.98,   0.02,   0.00,   0.00,  64.15,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.61, 6,  drogue,   -7.85,  78841.00, 2066.50,  736.70,  -24.49, 32.3, 1.34, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.71, 6,  drogue,  -16.67,  78870.00, 2063.55,  733.74,  -24.26, 32.3, 1.34, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.81, 6,  drogue,  -26.48,  78837.00, 2066.91,  737.11,  -23.93, 32.3, 1.34, 3.98, 3.98,   0.09,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.90, 6,  drogue,  -26.48,  78837.00, 2066.91,  737.11,  -23.93, 32.3, 1.35, 3.98, 3.99,   0.09,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   146.91, 6,  drogue,  -17.65,  78900.00, 2060.49,  730.69,  -23.65, 32.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.01, 6,  drogue,  -19.61,  78962.00, 2054.17,  724.37,  -23.45, 32.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.11, 6,  drogue,  -21.08,  78940.00, 2056.41,  726.61,  -23.26, 32.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.21, 6,  drogue,  -22.56,  78923.00, 2058.14,  728.34,  -23.22, 32.3, 1.35, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.22, 6,  drogue,  -22.56,  78923.00, 2058.14,  728.34,  -23.22, 32.3, 1.34, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.30, 6,  drogue,  -22.56,  78923.00, 2058.14,  728.34,  -23.22, 32.3, 1.34, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.30, 6,  drogue,  -22.56,  78923.00, 2058.14,  728.34,  -23.22, 32.3, 1.34, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483956,-106.9157343,  2187.0, 2022,  6, 24, 15, 19, 43,     1066,     1329, 338,  37,   1.6,   0.8,   1.4,  0, 32, 32,  0,  0, 33,  0,  0,  0,  0, 36, 32, 29, 28,  0,  0, 32,  0, 32, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   147.31, 6,  drogue,  -21.08,  78958.00, 2054.58,  724.78,  -23.30, 32.3, 1.34, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.41, 6,  drogue,  -21.08,  79017.00, 2048.57,  718.77,  -23.48, 32.3, 1.34, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.51, 6,  drogue,  -20.59,  78972.00, 2053.15,  723.35,  -23.68, 32.3, 1.34, 3.98, 3.98,   0.00,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.54, 6,  drogue,  -20.59,  78972.00, 2053.15,  723.35,  -23.68, 32.3, 1.34, 3.99, 3.98,   0.00,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.61, 6,  drogue,  -19.61,  78945.00, 2055.90,  726.10,  -23.95, 32.3, 1.34, 3.99, 3.98,   0.09,   0.00,   0.00,  64.21,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.71, 6,  drogue,  -18.14,  78957.00, 2054.68,  724.88,  -24.29, 32.3, 1.34, 3.99, 3.98,   0.09,   0.00,   0.00,  64.21,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.81, 6,  drogue,  -19.12,  79108.00, 2039.31,  709.51,  -24.74, 32.3, 1.34, 3.99, 3.98,   0.09,   0.00,   0.00,  64.21,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.86, 6,  drogue,  -19.12,  79108.00, 2039.31,  709.51,  -24.74, 32.3, 1.33, 3.98, 3.98,   0.09,   0.00,   0.00,  64.21,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   147.91, 6,  drogue,  -15.69,  79119.00, 2038.19,  708.39,  -25.23, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.01, 6,  drogue,  -10.79,  79124.00, 2037.68,  707.88,  -25.71, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.11, 6,  drogue,  -11.28,  79133.00, 2036.76,  706.96,  -26.25, 32.3, 1.33, 3.98, 3.98,   0.08,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.18, 6,  drogue,  -11.28,  79133.00, 2036.76,  706.96,  -26.25, 32.3, 1.33, 3.96, 3.97,   0.08,   0.00,   0.00,  64.15,  21.42,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.21, 6,  drogue,   -9.81,  79121.00, 2037.99,  708.18,  -26.80, 32.3, 1.33, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.30, 6,  drogue,   -9.81,  79121.00, 2037.99,  708.18,  -26.80, 32.3, 1.33, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.30, 6,  drogue,   -9.81,  79121.00, 2037.99,  708.18,  -26.80, 32.3, 1.33, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484799,-106.9156931,  2161.0, 2022,  6, 24, 15, 19, 44,     1074,     1320, 338,  36,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 37,  0,  0,  0,  0, 36, 28, 33, 34,  0,  0, 35,  0, 34, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   148.31, 6,  drogue,   -6.37,  79105.00, 2039.61,  709.81,  -27.30, 32.3, 1.33, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.41, 6,  drogue,  -12.26,  79209.00, 2029.04,  699.24,  -27.79, 32.3, 1.33, 3.96, 3.97,   0.00,   0.00,   0.00,  63.84,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.50, 6,  drogue,  -12.26,  79209.00, 2029.04,  699.24,  -27.79, 32.3, 1.34, 3.98, 3.99,   0.00,   0.00,   0.00,  63.84,  21.36,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.51, 6,  drogue,   -2.45,  79173.00, 2032.70,  702.90,  -28.24, 32.3, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.61, 6,  drogue,   25.01,  79248.00, 2025.08,  695.28,  -28.62, 32.3, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.71, 6,  drogue,   19.12,  79452.00, 2004.38,  674.58,  -28.93, 32.3, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.81, 6,  drogue,    4.41,  79286.00, 2021.22,  691.42,  -29.14, 32.3, 1.34, 3.98, 3.99,   0.09,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.82, 6,  drogue,    4.41,  79286.00, 2021.22,  691.42,  -29.14, 32.3, 1.34, 3.97, 3.98,   0.09,   0.00,   0.00,  64.15,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   148.91, 6,  drogue,   -9.32,  79314.00, 2018.38,  688.58,  -29.29, 32.3, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.01, 6,  drogue,   -2.45,  79375.00, 2012.19,  682.39,  -29.40, 32.3, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.11, 6,  drogue,    7.35,  79355.00, 2014.22,  684.41,  -29.42, 32.3, 1.34, 3.97, 3.98,   0.02,   0.00,   0.00,  63.97,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.14, 6,  drogue,    7.35,  79355.00, 2014.22,  684.41,  -29.42, 32.3, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  63.97,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.21, 6,  drogue,    3.43,  79525.00, 1996.98,  667.18,  -29.35, 32.3, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.30, 6,  drogue,    3.43,  79525.00, 1996.98,  667.18,  -29.35, 32.3, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.30, 6,  drogue,    3.43,  79525.00, 1996.98,  667.18,  -29.35, 32.3, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485198,-106.9156275,  2133.0, 2022,  6, 24, 15, 19, 45,     1076,     1305, 339,  34,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 32, 33, 33,  0,  0, 34,  0, 31, 28,  0,  0,  0, 29,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   149.31, 6,  drogue,   -3.92,  79624.00, 1986.96,  657.16,  -29.22, 32.3, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.41, 6,  drogue,   -5.39,  79614.00, 1987.97,  658.17,  -29.05, 32.3, 1.34, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.46, 6,  drogue,   -5.39,  79614.00, 1987.97,  658.17,  -29.05, 32.3, 1.34, 3.96, 3.97,   0.02,   0.00,   0.00,  64.09,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.51, 6,  drogue,   -4.41,  79579.00, 1991.51,  661.71,  -28.76, 32.3, 1.34, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.61, 6,  drogue,   -5.39,  79512.00, 1998.30,  668.50,  -28.43, 32.2, 1.34, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.71, 6,  drogue,  -11.28,  79531.00, 1996.37,  666.57,  -28.08, 32.2, 1.34, 3.96, 3.97,   0.00,   0.00,   0.00,  63.78,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.78, 6,  drogue,  -11.28,  79531.00, 1996.37,  666.57,  -28.08, 32.2, 1.37, 3.98, 3.98,   0.00,   0.00,   0.00,  63.78,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.01, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.81, 6,  drogue,  -13.73,  79593.00, 1990.10,  660.30,  -27.82, 32.2, 1.37, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.01, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   149.91, 6,  drogue,   -6.37,  79668.00, 1982.51,  652.71,  -27.55, 32.2, 1.37, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.01, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.01, 6,  drogue,    1.96,  79686.00, 1980.69,  650.89,  -27.30, 32.2, 1.37, 3.98, 3.98,   0.00,   0.00,   0.00,  64.03,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.01, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.10, 6,  drogue,    1.96,  79686.00, 1980.69,  650.89,  -27.30, 32.2, 1.36, 3.97, 3.98,   0.00,   0.00,   0.00,  64.03,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.11, 6,  drogue,   -9.32,  79712.00, 1978.06,  648.26,  -27.06, 32.2, 1.36, 3.97, 3.98,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.21, 6,  drogue,  -15.69,  79758.00, 1973.41,  643.61,  -26.84, 32.2, 1.36, 3.97, 3.98,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.30, 6,  drogue,  -15.69,  79758.00, 1973.41,  643.61,  -26.84, 32.2, 1.36, 3.97, 3.98,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.30, 6,  drogue,  -15.69,  79758.00, 1973.41,  643.61,  -26.84, 32.2, 1.36, 3.97, 3.98,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485240,-106.9155726,  2105.0, 2022,  6, 24, 15, 19, 46,     1074,     1288, 339,  34,   1.6,   0.8,   1.4,  0, 27, 33,  0,  0, 33,  0,  0,  0,  0, 33, 33, 29, 36,  0,  0, 37,  0, 32, 28,  0,  0,  0, 33,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.31, 6,  drogue,  -20.59,  79745.00, 1974.72,  644.92,  -26.61, 32.2, 1.36, 3.97, 3.98,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.41, 6,  drogue,  -12.75,  79770.00, 1972.20,  642.40,  -26.41, 32.2, 1.36, 3.97, 3.98,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.42, 6,  drogue,  -12.75,  79770.00, 1972.20,  642.40,  -26.41, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  63.97,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.51, 6,  drogue,  -12.75,  79757.00, 1973.51,  643.71,  -26.16, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.61, 6,  drogue,  -17.16,  79831.00, 1966.04,  636.24,  -25.97, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.71, 6,  drogue,  -12.75,  79886.00, 1960.49,  630.69,  -25.88, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.74, 6,  drogue,  -12.75,  79886.00, 1960.49,  630.69,  -25.88, 32.2, 1.37, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.81, 6,  drogue,   -8.83,  79923.00, 1956.75,  626.95,  -25.67, 32.2, 1.37, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   150.91, 6,  drogue,  -18.14,  79946.00, 1954.43,  624.63,  -25.47, 32.2, 1.37, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.01, 6,  drogue,  -15.20,  80005.00, 1948.48,  618.68,  -25.31, 32.2, 1.37, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.06, 6,  drogue,  -15.20,  80005.00, 1948.48,  618.68,  -25.31, 32.2, 1.36, 3.98, 3.99,   0.09,   0.00,   0.00,  64.09,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.11, 6,  drogue,  -17.65,  80014.00, 1947.58,  617.78,  -25.12, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.21, 6,  drogue,  -12.75,  80016.00, 1947.38,  617.58,  -25.01, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.30, 6,  drogue,  -12.75,  80016.00, 1947.38,  617.58,  -25.01, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.30, 6,  drogue,  -12.75,  80016.00, 1947.38,  617.58,  -25.01, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485452,-106.9155151,  2078.0, 2022,  6, 24, 15, 19, 47,     1074,     1274, 339,  32,   1.6,   0.8,   1.4,  0, 27, 28,  0,  0, 34,  0,  0,  0,  0, 17, 36, 29, 35,  0,  0, 35,  0, 36, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.31, 6,  drogue,  -12.75,  80005.00, 1948.48,  618.68,  -24.92, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.38, 6,  drogue,  -12.75,  80005.00, 1948.48,  618.68,  -24.92, 32.2, 1.36, 3.98, 3.98,   0.08,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.41, 6,  drogue,  -11.77,  79995.00, 1949.49,  619.69,  -24.79, 32.2, 1.36, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.51, 6,  drogue,  -20.59,  79987.00, 1950.30,  620.50,  -24.63, 32.2, 1.36, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.61, 6,  drogue,  -16.67,  80030.00, 1945.97,  616.16,  -24.45, 32.2, 1.36, 3.98, 3.98,   0.03,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.70, 6,  drogue,  -16.67,  80030.00, 1945.97,  616.16,  -24.45, 32.2, 1.36, 3.98, 3.99,   0.03,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.71, 6,  drogue,  -16.67,  80063.00, 1942.64,  612.84,  -24.31, 32.2, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.81, 6,  drogue,  -15.69,  80154.00, 1933.48,  603.68,  -24.24, 32.2, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   151.91, 6,  drogue,  -18.14,  80190.00, 1929.86,  600.05,  -24.21, 32.2, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.01, 6,  drogue,  -16.18,  80255.00, 1923.32,  593.52,  -24.19, 32.2, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.02, 6,  drogue,  -16.18,  80255.00, 1923.32,  593.52,  -24.19, 32.2, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.11, 6,  drogue,  -19.12,  80286.00, 1920.20,  590.40,  -24.19, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.21, 6,  drogue,  -16.67,  80301.00, 1918.70,  588.89,  -24.21, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.30, 6,  drogue,  -16.67,  80301.00, 1918.70,  588.89,  -24.21, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.30, 6,  drogue,  -16.67,  80301.00, 1918.70,  588.89,  -24.21, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485733,-106.9154604,  2053.0, 2022,  6, 24, 15, 19, 48,     1076,     1261, 340,  31,   1.6,   0.8,   1.4,  0, 29, 28,  0,  0, 34,  0,  0,  0,  0, 23, 30, 29, 35,  0,  0, 36,  0, 36, 29,  0,  0,  0, 36,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   152.31, 6,  drogue,  -17.65,  80269.00, 1921.91,  592.11,  -24.22, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.34, 6,  drogue,  -17.65,  80269.00, 1921.91,  592.11,  -24.22, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.15,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.41, 6,  drogue,  -17.16,  80216.00, 1927.24,  597.44,  -24.25, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.51, 6,  drogue,  -20.10,  80228.00, 1926.03,  596.23,  -24.26, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.61, 6,  drogue,  -21.08,  80304.00, 1918.39,  588.59,  -24.33, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.66, 6,  drogue,  -21.08,  80304.00, 1918.39,  588.59,  -24.33, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.03,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.71, 6,  drogue,  -19.61,  80334.00, 1915.38,  585.58,  -24.44, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.81, 6,  drogue,  -18.63,  80378.00, 1910.96,  581.16,  -24.57, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.91, 6,  drogue,  -21.57,  80405.00, 1908.25,  578.45,  -24.66, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   152.98, 6,  drogue,  -21.57,  80405.00, 1908.25,  578.45,  -24.66, 32.2, 1.36, 3.98, 3.99,   0.02,   0.00,   0.00,  64.09,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   153.01, 6,  drogue,  -20.10,  80425.00, 1906.24,  576.44,  -24.79, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   153.11, 6,  drogue,  -19.12,  80448.00, 1903.93,  574.13,  -24.88, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   153.21, 6,  drogue,  -19.12,  80463.00, 1902.43,  572.63,  -24.95, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485882,-106.9154265,  2027.0, 2022,  6, 24, 15, 19, 49,     1076,     1248, 340,  30,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 28, 34, 34,  0,  0, 34,  0, 30, 33,  0,  0,  0, 28,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   153.30, 6,  drogue,  -19.12,  80463.00, 1902.43,  572.63,  -24.95, 32.2, 1.37, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.30, 6,  drogue,  -19.12,  80463.00, 1902.43,  572.63,  -24.95, 32.2, 1.37, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.30, 6,  drogue,  -19.12,  80463.00, 1902.43,  572.63,  -24.95, 32.2, 1.37, 3.98, 3.99,   0.08,   0.00,   0.00,  64.03,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.31, 6,  drogue,  -18.14,  80502.00, 1898.52,  568.72,  -25.00, 32.2, 1.37, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.41, 6,  drogue,  -20.10,  80525.00, 1896.21,  566.41,  -25.03, 32.2, 1.37, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.51, 6,  drogue,  -19.61,  80561.00, 1892.60,  562.80,  -25.07, 32.2, 1.37, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.61, 6,  drogue,  -21.08,  80596.00, 1889.09,  559.29,  -25.13, 32.2, 1.37, 3.98, 3.99,   0.00,   0.00,   0.00,  64.09,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.62, 6,  drogue,  -21.08,  80596.00, 1889.09,  559.29,  -25.13, 32.2, 1.36, 3.99, 3.99,   0.00,   0.00,   0.00,  64.09,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.71, 6,  drogue,  -15.20,  80614.00, 1887.29,  557.49,  -25.21, 32.2, 1.36, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.81, 6,  drogue,  -20.10,  80641.00, 1884.59,  554.79,  -25.32, 32.2, 1.36, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.91, 6,  drogue,  -19.61,  80652.00, 1883.49,  553.68,  -25.43, 32.2, 1.36, 3.99, 3.99,   0.08,   0.00,   0.00,  64.21,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   153.94, 6,  drogue,  -19.61,  80652.00, 1883.49,  553.68,  -25.43, 32.2, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.21,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.01, 6,  drogue,  -18.63,  80668.00, 1881.88,  552.08,  -25.53, 32.2, 1.36, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.11, 6,  drogue,  -20.10,  80681.00, 1880.58,  550.78,  -25.60, 32.2, 1.36, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.21, 6,  drogue,  -17.65,  80712.00, 1877.48,  547.68,  -25.64, 32.2, 1.36, 3.98, 3.99,   0.03,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.26, 6,  drogue,  -17.65,  80712.00, 1877.48,  547.68,  -25.64, 32.2, 1.36, 3.99, 3.98,   0.03,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.30, 6,  drogue,  -17.65,  80712.00, 1877.48,  547.68,  -25.64, 32.2, 1.36, 3.99, 3.98,   0.03,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.30, 6,  drogue,  -17.65,  80712.00, 1877.48,  547.68,  -25.64, 32.2, 1.36, 3.99, 3.98,   0.03,   0.00,   0.00,  64.09,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485773,-106.9153994,  1999.0, 2022,  6, 24, 15, 19, 50,     1074,     1233, 340,  29,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 35,  0,  0,  0,  0, 33, 36, 30, 37,  0,  0, 39,  0, 37, 19,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   154.31, 6,  drogue,  -23.05,  80736.00, 1875.08,  545.28,  -25.61, 32.2, 1.36, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.41, 6,  drogue,  -19.61,  80767.00, 1871.98,  542.18,  -25.54, 32.2, 1.36, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.51, 6,  drogue,  -20.59,  80781.00, 1870.58,  540.78,  -25.45, 32.2, 1.36, 3.99, 3.98,   0.00,   0.00,   0.00,  64.21,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.58, 6,  drogue,  -20.59,  80781.00, 1870.58,  540.78,  -25.45, 32.2, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  64.21,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.61, 6,  drogue,  -19.12,  80833.00, 1865.38,  535.58,  -25.41, 32.2, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.71, 6,  drogue,  -19.12,  80878.00, 1860.88,  531.08,  -25.38, 32.2, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.81, 6,  drogue,  -20.10,  80931.00, 1855.59,  525.79,  -25.33, 32.2, 1.35, 3.97, 3.97,   0.00,   0.00,   0.00,  63.91,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.90, 6,  drogue,  -20.10,  80931.00, 1855.59,  525.79,  -25.33, 32.2, 1.35, 3.98, 3.99,   0.00,   0.00,   0.00,  63.91,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   154.91, 6,  drogue,  -20.59,  80894.00, 1859.28,  529.48,  -25.26, 32.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   155.01, 6,  drogue,  -20.59,  80954.00, 1853.29,  523.49,  -25.18, 32.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   155.11, 6,  drogue,  -21.57,  80936.00, 1855.09,  525.29,  -25.06, 32.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   155.21, 6,  drogue,  -18.63,  80976.00, 1851.09,  521.29,  -24.91, 32.2, 1.35, 3.98, 3.99,   0.02,   0.00,   0.00,  64.15,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   155.22, 6,  drogue,  -18.63,  80976.00, 1851.09,  521.29,  -24.91, 32.2, 1.35, 3.97, 3.98,   0.02,   0.00,   0.00,  64.15,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9485486,-106.9153484,  1973.0, 2022,  6, 24, 15, 19, 51,     1069,     1216, 340,  28,   1.6,   0.8,   1.4,  0, 37, 28,  0,  0, 38,  0,  0,  0,  0, 37, 23, 34, 24,  0,  0, 37,  0, 36, 32,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   155.31, 6,  drogue,  -18.14,  80995.00, 1849.20,  519.40,  -24.74, 32.2, 1.35, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.31, 6,  drogue,  -18.14,  80995.00, 1849.20,  519.40,  -24.74, 32.2, 1.35, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.31, 6,  drogue,  -18.14,  80995.00, 1849.20,  519.40,  -24.74, 32.2, 1.35, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.41, 6,  drogue,  -20.10,  81019.00, 1846.80,  517.00,  -24.53, 32.1, 1.35, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.51, 6,  drogue,  -18.63,  81068.00, 1841.92,  512.11,  -24.30, 32.1, 1.35, 3.97, 3.98,   0.00,   0.00,   0.01,  63.97,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.54, 6,  drogue,  -18.63,  81068.00, 1841.92,  512.11,  -24.30, 32.1, 1.35, 3.98, 3.98,   0.00,   0.00,   0.01,  63.97,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.61, 6,  drogue,  -14.22,  81080.00, 1840.72,  510.92,  -24.09, 32.1, 1.35, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.71, 6,  drogue,  -18.63,  81130.00, 1835.73,  505.93,  -23.92, 32.1, 1.35, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.81, 6,  drogue,  -12.26,  81162.00, 1832.55,  502.75,  -23.77, 32.1, 1.35, 3.98, 3.98,   0.09,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.86, 6,  drogue,  -12.26,  81162.00, 1832.55,  502.75,  -23.77, 32.1, 1.35, 3.99, 3.99,   0.09,   0.00,   0.00,  64.09,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   155.91, 6,  drogue,   -8.83,  81190.00, 1829.76,  499.96,  -24.80, 32.1, 1.35, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.01, 6,  drogue,  -10.30,  81188.00, 1829.96,  500.16,  -25.19, 32.1, 1.35, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.11, 6,  drogue,  -13.73,  81202.00, 1828.56,  498.76,  -25.69, 32.1, 1.35, 3.99, 3.99,   0.08,   0.00,   0.00,  64.27,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.18, 6,  drogue,  -13.73,  81202.00, 1828.56,  498.76,  -25.69, 32.1, 1.36, 3.98, 3.99,   0.08,   0.00,   0.00,  64.27,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.21, 6,  drogue,  -13.73,  81225.00, 1826.27,  496.47,  -26.28, 32.1, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.30, 6,  drogue,  -13.73,  81225.00, 1826.27,  496.47,  -26.28, 32.1, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.30, 6,  drogue,  -13.73,  81225.00, 1826.27,  496.47,  -26.28, 32.1, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485104,-106.9152846,  1947.0, 2022,  6, 24, 15, 19, 52,     1063,     1199, 340,  27,   1.6,   0.8,   1.4,  0, 25, 29,  0,  0, 36,  0,  0,  0,  0, 30, 34, 24, 38,  0,  0, 38,  0, 36, 32,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.31, 6,  drogue,  -12.26,  81210.00, 1827.77,  497.96,  -26.97, 32.1, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.41, 6,  drogue,  -15.20,  81257.00, 1823.09,  493.29,  -27.73, 32.2, 1.36, 3.98, 3.99,   0.00,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.50, 6,  drogue,  -15.20,  81257.00, 1823.09,  493.29,  -27.73, 32.2, 1.35, 3.99, 3.99,   0.00,   0.00,   0.00,  64.15,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.51, 6,  drogue,  -14.22,  81269.00, 1821.89,  492.09,  -28.50, 32.1, 1.35, 3.99, 3.99,   0.02,   0.01,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.61, 6,  drogue,  -17.16,  81330.00, 1815.82,  486.02,  -29.27, 32.1, 1.35, 3.99, 3.99,   0.02,   0.01,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.71, 6,  drogue,  -21.08,  81368.00, 1812.04,  482.24,  -29.99, 32.1, 1.35, 3.99, 3.99,   0.02,   0.01,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.81, 6,  drogue,  -17.65,  81370.00, 1811.85,  482.04,  -30.62, 32.1, 1.35, 3.99, 3.99,   0.02,   0.01,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.82, 6,  drogue,  -17.65,  81370.00, 1811.85,  482.04,  -30.62, 32.1, 1.34, 3.98, 3.98,   0.02,   0.01,   0.00,  64.21,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   156.91, 6,  drogue,  -17.65,  81386.00, 1810.26,  480.45,  -31.05, 32.1, 1.34, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.01, 6,  drogue,  -16.18,  81424.00, 1806.48,  476.68,  -31.37, 32.1, 1.34, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.11, 6,  drogue,  -12.75,  81422.00, 1806.68,  476.88,  -31.49, 32.1, 1.34, 3.98, 3.98,   0.02,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.14, 6,  drogue,  -12.75,  81422.00, 1806.68,  476.88,  -31.49, 32.1, 1.35, 3.99, 3.99,   0.02,   0.00,   0.00,  64.03,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.21, 6,  drogue,  -10.30,  81426.00, 1806.28,  476.48,  -31.39, 32.1, 1.35, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.30, 6,  drogue,  -10.30,  81426.00, 1806.28,  476.48,  -31.39, 32.1, 1.35, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.30, 6,  drogue,  -10.30,  81426.00, 1806.28,  476.48,  -31.39, 32.1, 1.35, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484604,-106.9152221,  1921.0, 2022,  6, 24, 15, 19, 53,     1056,     1180, 340,  27,   1.7,   0.9,   1.4,  0, 39, 29,  0,  0, 29,  0,  0,  0,  0, 38, 31, 37, 34,  0,  0, 29,  0, 32, 33,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.31, 6,  drogue,  -12.75,  81461.00, 1802.80,  473.00,  -31.06, 32.1, 1.35, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.41, 6,  drogue,  -13.73,  81434.00, 1805.48,  475.68,  -30.49, 32.1, 1.35, 3.99, 3.99,   0.00,   0.00,   0.00,  64.21,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.46, 6,  drogue,  -13.73,  81434.00, 1805.48,  475.68,  -30.49, 32.1, 1.35, 3.98, 3.98,   0.00,   0.00,   0.00,  64.21,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.51, 6,  drogue,  -16.67,  81486.00, 1800.32,  470.52,  -29.69, 32.1, 1.35, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.61, 6,  drogue,  -14.71,  81552.00, 1793.77,  463.97,  -28.67, 32.1, 1.35, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.71, 6,  drogue,  -18.14,  81648.00, 1784.25,  454.44,  -27.47, 32.1, 1.35, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.78, 6,  drogue,  -18.14,  81648.00, 1784.25,  454.44,  -27.47, 32.1, 1.35, 3.98, 3.98,   0.02,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.81, 6,  drogue,  -20.59,  81676.00, 1781.47,  451.67,  -26.13, 32.1, 1.35, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.91, 6,  drogue,  -59.82,  83279.00, 1623.83,  294.03,  -24.69, 32.1, 1.35, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   157.97, 7,    main,  -59.82,  83279.00, 1623.83,  294.03,  -24.69, 32.1, 1.35, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.01, 7,    main,  -19.12,  81705.00, 1778.60,  448.79,  -23.15, 32.1, 1.35, 3.98, 3.98,   0.08,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.10, 7,    main,  -19.12,  81705.00, 1778.60,  448.79,  -23.15, 32.1, 1.36, 3.87, 3.98,   0.08,   0.00,   0.00,  64.09,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.11, 7,    main,  -11.77,  81708.00, 1778.30,  448.50,  -21.58, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.21, 7,    main,  -12.26,  81729.00, 1776.22,  446.42,  -20.03, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.30, 7,    main,  -12.26,  81729.00, 1776.22,  446.42,  -20.03, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.30, 7,    main,  -12.26,  81729.00, 1776.22,  446.42,  -20.03, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484117,-106.9151551,  1896.0, 2022,  6, 24, 15, 19, 54,     1049,     1163, 341,  26,   1.6,   0.8,   1.4,  0, 38, 28,  0,  0, 29,  0,  0,  0,  0, 37, 30, 32, 30,  0,  0, 32,  0, 32, 36,  0,  0,  0, 36,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.31, 7,    main,  -19.12,  81777.00, 1771.46,  441.66,  -18.52, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.41, 7,    main,  -23.54,  81806.00, 1768.59,  438.79,  -17.15, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.42, 7,    main,  -23.54,  81806.00, 1768.59,  438.79,  -17.15, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.38,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.51, 7,    main,  -20.59,  81813.00, 1767.90,  438.10,  -15.89, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.61, 7,    main,    2.45,  81845.00, 1764.73,  434.93,  -14.81, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.71, 7,    main,  -10.79,  81865.00, 1762.75,  432.95,  -13.90, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.74, 7,    main,  -10.79,  81865.00, 1762.75,  432.95,  -13.90, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.81, 7,    main,   -0.00,  81861.00, 1763.15,  433.35,  -13.15, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.04,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   158.91, 7,    main,   30.40,  81873.00, 1761.96,  432.16,  -12.55, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.04,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.01, 7,    main,  198.58,  81931.00, 1756.23,  426.43,  -12.11, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.04,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.06, 7,    main,  198.58,  81931.00, 1756.23,  426.43,  -12.11, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.04,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.11, 7,    main,   70.61,  81986.00, 1750.79,  420.99,  -11.79, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.21, 7,    main,    1.47,  81959.00, 1753.46,  423.66,  -11.58, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.30, 7,    main,    1.47,  81959.00, 1753.46,  423.66,  -11.58, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.30, 7,    main,    1.47,  81959.00, 1753.46,  423.66,  -11.58, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483725,-106.9151056,  1868.0, 2022,  6, 24, 15, 19, 55,     1043,     1146, 341,  24,   1.7,   0.8,   1.4,  0, 29, 27,  0,  0, 39,  0,  0,  0,  0, 31, 31, 32, 34,  0,  0, 37,  0, 33, 36,  0,  0,  0, 32,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   159.31, 7,    main,    4.41,  81965.00, 1752.87,  423.06,  -11.48, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.38, 7,    main,    4.41,  81965.00, 1752.87,  423.06,  -11.48, 32.1, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.41, 7,    main,  -17.65,  81974.00, 1751.98,  422.17,  -11.41, 32.1, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.51, 7,    main,  -16.18,  81962.00, 1753.16,  423.36,  -11.42, 32.1, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.61, 7,    main,  -50.99,  81992.00, 1750.20,  420.40,  -11.45, 32.1, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.70, 7,    main,  -50.99,  81992.00, 1750.20,  420.40,  -11.45, 32.1, 1.39, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.71, 7,    main,   20.59,  82006.00, 1748.81,  419.01,  -11.50, 32.1, 1.39, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.81, 7,    main,   59.82,  82049.00, 1744.57,  414.77,  -11.50, 32.1, 1.39, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   159.91, 7,    main,   19.12,  82077.00, 1741.80,  412.00,  -12.18, 32.1, 1.39, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.01, 7,    main,    3.92,  82054.00, 1744.07,  414.27,  -11.73, 32.1, 1.39, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.02, 7,    main,    3.92,  82054.00, 1744.07,  414.27,  -11.73, 32.1, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.01,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.11, 7,    main,   11.77,  82063.00, 1743.18,  413.38,  -11.29, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.21, 7,    main,   13.73,  82080.00, 1741.51,  411.70,  -10.87, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.30, 7,    main,   13.73,  82080.00, 1741.51,  411.70,  -10.87, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.30, 7,    main,   13.73,  82080.00, 1741.51,  411.70,  -10.87, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483388,-106.9150396,  1846.0, 2022,  6, 24, 15, 19, 56,     1038,     1132, 341,  24,   1.6,   0.8,   1.4,  0, 30, 27,  0,  0, 36,  0,  0,  0,  0, 31, 35, 26, 36,  0,  0, 34,  0, 37, 28,  0,  0,  0, 37,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.31, 7,    main,  -25.99,  82073.00, 1742.20,  412.40,  -10.50, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.34, 7,    main,  -25.99,  82073.00, 1742.20,  412.40,  -10.50, 32.1, 1.36, 3.85, 3.99,   0.09,   0.00,   0.00,  62.26,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.41, 7,    main,  -16.67,  82104.00, 1739.14,  409.34,  -10.14, 32.1, 1.36, 3.85, 3.99,   0.00,   0.00,   0.00,  62.07,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.51, 7,    main,   24.52,  82099.00, 1739.63,  409.83,   -9.80, 32.1, 1.36, 3.85, 3.99,   0.00,   0.00,   0.00,  62.07,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.61, 7,    main,   -0.00,  82123.00, 1737.26,  407.46,   -9.48, 32.1, 1.36, 3.85, 3.99,   0.00,   0.00,   0.00,  62.07,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.66, 7,    main,   -0.00,  82123.00, 1737.26,  407.46,   -9.48, 32.1, 1.36, 3.86, 3.99,   0.00,   0.00,   0.00,  62.07,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.71, 7,    main,  -15.69,  82133.00, 1736.27,  406.47,   -9.17, 32.1, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.81, 7,    main,  -11.28,  82145.00, 1735.09,  405.29,   -8.88, 32.1, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.91, 7,    main,  -10.30,  82142.00, 1735.39,  405.59,   -8.60, 32.1, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   160.98, 7,    main,  -10.30,  82142.00, 1735.39,  405.59,   -8.60, 32.1, 1.37, 3.87, 3.99,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   161.01, 7,    main,   -0.00,  82146.00, 1734.99,  405.19,   -8.38, 32.1, 1.37, 3.87, 3.99,   0.02,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   161.11, 7,    main,   -1.47,  82158.00, 1733.81,  404.01,   -8.18, 32.1, 1.37, 3.87, 3.99,   0.02,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   161.21, 7,    main,   -5.39,  82162.00, 1733.41,  403.61,   -7.97, 32.1, 1.37, 3.87, 3.99,   0.02,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9483260,-106.9150039,  1830.0, 2022,  6, 24, 15, 19, 57,     1035,     1123, 341,  23,   1.6,   0.8,   1.4,  0, 31, 27,  0,  0, 27,  0,  0,  0,  0, 28, 32, 31, 22,  0,  0, 32,  0, 30, 27,  0,  0,  0, 23,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   161.30, 7,    main,   -5.39,  82162.00, 1733.41,  403.61,   -7.97, 32.1, 1.38, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.30, 7,    main,   -5.39,  82162.00, 1733.41,  403.61,   -7.97, 32.1, 1.38, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.30, 7,    main,   -5.39,  82162.00, 1733.41,  403.61,   -7.97, 32.1, 1.38, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.31, 7,    main,   -2.94,  82174.00, 1732.23,  402.43,   -7.78, 32.1, 1.38, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.41, 7,    main,   -6.37,  82190.00, 1730.65,  400.85,   -7.61, 32.1, 1.38, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.51, 7,    main,   -3.92,  82205.00, 1729.17,  399.37,   -7.46, 32.1, 1.38, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.61, 7,    main,   -4.41,  82202.00, 1729.47,  399.67,   -7.35, 32.1, 1.38, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.62, 7,    main,   -4.41,  82202.00, 1729.47,  399.67,   -7.35, 32.1, 1.37, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.71, 7,    main,   -1.96,  82206.00, 1729.07,  399.27,   -7.27, 32.1, 1.37, 3.87, 3.99,   0.09,   0.00,   0.01,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.81, 7,    main,   -3.43,  82220.00, 1727.69,  397.89,   -7.24, 32.1, 1.37, 3.87, 3.99,   0.09,   0.00,   0.01,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.91, 7,    main,   -9.32,  82222.00, 1727.50,  397.70,   -7.23, 32.1, 1.37, 3.87, 3.99,   0.09,   0.00,   0.01,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   161.94, 7,    main,   -9.32,  82222.00, 1727.50,  397.70,   -7.23, 32.1, 1.38, 3.87, 3.98,   0.09,   0.00,   0.01,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.01, 7,    main,  -11.28,  82226.00, 1727.10,  397.30,   -7.22, 32.1, 1.38, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.11, 7,    main,  -10.30,  82224.00, 1727.30,  397.50,   -7.21, 32.1, 1.38, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.21, 7,    main,   -8.34,  82229.00, 1726.81,  397.01,   -7.24, 32.1, 1.38, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.26, 7,    main,   -8.34,  82229.00, 1726.81,  397.01,   -7.24, 32.1, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.30, 7,    main,   -8.34,  82229.00, 1726.81,  397.01,   -7.24, 32.1, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.30, 7,    main,   -8.34,  82229.00, 1726.81,  397.01,   -7.24, 32.1, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  22.22,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483499,-106.9150263,  1823.0, 2022,  6, 24, 15, 19, 58,     1039,     1124, 341,  22,   1.6,   0.8,   1.4,  0, 32, 31,  0,  0, 33,  0,  0,  0,  0, 32, 28, 34, 36,  0,  0, 34,  0, 35, 32,  0,  0,  0, 25,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   162.31, 7,    main,   -1.96,  82240.00, 1725.72,  395.92,   -7.26, 32.1, 1.38, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.41, 7,    main,    3.92,  82244.00, 1725.33,  395.53,   -7.31, 32.1, 1.38, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.51, 7,    main,   -1.47,  82251.00, 1724.64,  394.84,   -7.34, 32.1, 1.38, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.58, 7,    main,   -1.47,  82251.00, 1724.64,  394.84,   -7.34, 32.1, 1.39, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  22.28,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.61, 7,    main,   -0.98,  82259.00, 1723.85,  394.05,   -7.39, 32.1, 1.39, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.71, 7,    main,   -5.88,  82274.00, 1722.37,  392.57,   -7.43, 32.1, 1.39, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.81, 7,    main,   -7.35,  82280.00, 1721.78,  391.98,   -7.46, 32.1, 1.39, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.90, 7,    main,   -7.35,  82280.00, 1721.78,  391.98,   -7.46, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   162.91, 7,    main,   -1.47,  82291.00, 1720.70,  390.90,   -7.46, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.01, 7,    main,   -4.41,  82302.00, 1719.61,  389.81,   -7.45, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.11, 7,    main,   -5.39,  82305.00, 1719.32,  389.52,   -7.44, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.21, 7,    main,   -1.96,  82316.00, 1718.23,  388.43,   -7.41, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.22, 7,    main,   -1.96,  82316.00, 1718.23,  388.43,   -7.41, 32.1, 1.41, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.30, 7,    main,   -1.96,  82316.00, 1718.23,  388.43,   -7.41, 32.1, 1.41, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.30, 7,    main,   -1.96,  82316.00, 1718.23,  388.43,   -7.41, 32.1, 1.41, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483720,-106.9150268,  1815.0, 2022,  6, 24, 15, 19, 59,     1041,     1123, 341,  22,   1.6,   0.8,   1.4,  0, 32, 26,  0,  0, 29,  0,  0,  0,  0, 32, 28, 34, 26,  0,  0, 36,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.31, 7,    main,   -1.47,  82327.00, 1717.15,  387.35,   -7.37, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.41, 7,    main,    0.49,  82330.00, 1716.86,  387.05,   -7.32, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.51, 7,    main,   -2.94,  82349.00, 1714.98,  385.18,   -7.27, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.54, 7,    main,   -2.94,  82349.00, 1714.98,  385.18,   -7.27, 32.1, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.61, 7,    main,   -0.49,  82347.00, 1715.18,  385.38,   -7.19, 32.1, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.71, 7,    main,    1.96,  82359.00, 1714.00,  384.20,   -7.12, 32.1, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.81, 7,    main,    5.88,  82367.00, 1713.21,  383.41,   -7.04, 32.1, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.86, 7,    main,    5.88,  82367.00, 1713.21,  383.41,   -7.04, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   163.91, 7,    main,    3.43,  82379.00, 1712.03,  382.23,   -6.96, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.01, 7,    main,   -1.96,  82375.00, 1712.42,  382.62,   -6.89, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.11, 7,    main,   -2.45,  82369.00, 1713.02,  383.21,   -6.83, 32.1, 1.41, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.18, 7,    main,   -2.45,  82369.00, 1713.02,  383.21,   -6.83, 32.1, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.14,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.21, 7,    main,   -1.96,  82390.00, 1710.95,  381.15,   -6.78, 32.1, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.30, 7,    main,   -1.96,  82390.00, 1710.95,  381.15,   -6.78, 32.1, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.30, 7,    main,   -1.96,  82390.00, 1710.95,  381.15,   -6.78, 32.1, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483863,-106.9150254,  1807.0, 2022,  6, 24, 15, 20,  0,     1042,     1121, 341,  22,   1.6,   0.8,   1.4,  0, 27, 32,  0,  0, 32,  0,  0,  0,  0, 22, 33, 28, 33,  0,  0, 31,  0, 31, 34,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.31, 7,    main,   -0.49,  82395.00, 1710.46,  380.66,   -6.76, 32.1, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.41, 7,    main,   -1.47,  82401.00, 1709.87,  380.06,   -6.74, 32.1, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.50, 7,    main,   -1.47,  82401.00, 1709.87,  380.06,   -6.74, 32.1, 1.41, 3.85, 3.97,   0.09,   0.00,   0.00,  62.32,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.51, 7,    main,   -5.39,  82400.00, 1709.96,  380.16,   -6.74, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.61, 7,    main,   -4.90,  82406.00, 1709.37,  379.57,   -6.75, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.71, 7,    main,   -8.34,  82429.00, 1707.11,  377.31,   -6.77, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.81, 7,    main,   -7.35,  82419.00, 1708.09,  378.29,   -6.80, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.82, 7,    main,   -7.35,  82419.00, 1708.09,  378.29,   -6.80, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   164.91, 7,    main,   -7.35,  82419.00, 1708.09,  378.29,   -6.84, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.01, 7,    main,   -7.35,  82442.00, 1705.83,  376.03,   -6.88, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.11, 7,    main,   -3.92,  82452.00, 1704.85,  375.05,   -6.92, 32.1, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.14, 7,    main,   -3.92,  82452.00, 1704.85,  375.05,   -6.92, 32.1, 1.41, 3.87, 3.99,   0.00,   0.00,   0.00,  61.95,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.21, 7,    main,    2.94,  82463.00, 1703.77,  373.97,   -6.95, 32.1, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.30, 7,    main,    2.94,  82463.00, 1703.77,  373.97,   -6.95, 32.1, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.30, 7,    main,    2.94,  82463.00, 1703.77,  373.97,   -6.95, 32.1, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9483890,-106.9150420,  1799.0, 2022,  6, 24, 15, 20,  1,     1043,     1119, 341,  21,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 38,  0,  0,  0,  0, 34, 31, 32, 33,  0,  0, 37,  0, 26, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   165.31, 7,    main,   -3.43,  82461.00, 1703.96,  374.16,   -6.99, 32.1, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.41, 7,    main,   -1.96,  82468.00, 1703.27,  373.47,   -7.01, 32.1, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.46, 7,    main,   -1.96,  82468.00, 1703.27,  373.47,   -7.01, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.51, 7,    main,   -2.45,  82478.00, 1702.29,  372.49,   -7.01, 32.1, 1.41, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.61, 7,    main,    0.49,  82471.00, 1702.98,  373.18,   -7.00, 32.1, 1.41, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.71, 7,    main,  -11.28,  82496.00, 1700.52,  370.72,   -6.97, 32.1, 1.41, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.01, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.78, 7,    main,  -11.28,  82496.00, 1700.52,  370.72,   -6.97, 32.1, 1.41, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.81, 7,    main,   -3.92,  82490.00, 1701.11,  371.31,   -6.94, 32.1, 1.41, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   165.91, 7,    main,   -3.92,  82513.00, 1698.85,  369.05,   -6.90, 32.1, 1.41, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.01, 7,    main,   -1.96,  82510.00, 1699.14,  369.34,   -6.83, 32.1, 1.41, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.10, 7,    main,   -1.96,  82510.00, 1699.14,  369.34,   -6.83, 32.1, 1.41, 3.85, 3.99,   0.00,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.11, 7,    main,    2.45,  82528.00, 1697.38,  367.57,   -6.74, 32.1, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.21, 7,    main,   -0.98,  82532.00, 1696.98,  367.18,   -6.66, 32.1, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.30, 7,    main,   -0.98,  82532.00, 1696.98,  367.18,   -6.66, 32.1, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.30, 7,    main,   -0.98,  82532.00, 1696.98,  367.18,   -6.66, 32.1, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9483941,-106.9150613,  1792.0, 2022,  6, 24, 15, 20,  2,     1044,     1118, 341,  21,   1.7,   0.8,   1.4,  0, 32, 33,  0,  0, 37,  0,  0,  0,  0, 33, 28, 26, 21,  0,  0, 21,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   166.31, 7,    main,    4.41,  82542.00, 1696.00,  366.20,   -6.58, 32.1, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.41, 7,    main,   -0.00,  82544.00, 1695.80,  366.00,   -6.48, 32.1, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.42, 7,    main,   -0.00,  82544.00, 1695.80,  366.00,   -6.48, 32.1, 1.40, 3.85, 3.97,   0.09,   0.00,   0.00,  62.07,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.51, 7,    main,    2.94,  82550.00, 1695.21,  365.41,   -6.39, 32.1, 1.40, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.61, 7,    main,   -0.00,  82557.00, 1694.53,  364.72,   -6.30, 32.1, 1.40, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.71, 7,    main,   -0.00,  82558.00, 1694.43,  364.63,   -6.22, 32.1, 1.40, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.74, 7,    main,   -0.00,  82558.00, 1694.43,  364.63,   -6.22, 32.1, 1.41, 3.86, 3.99,   0.00,   0.00,   0.00,  61.95,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.81, 7,    main,    1.47,  82562.00, 1694.03,  364.23,   -6.15, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   166.91, 7,    main,    0.49,  82578.00, 1692.46,  362.66,   -6.07, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.01, 7,    main,    0.49,  82580.00, 1692.27,  362.46,   -6.02, 32.1, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.06, 7,    main,    0.49,  82580.00, 1692.27,  362.46,   -6.02, 32.1, 1.41, 3.87, 3.98,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.11, 7,    main,   -0.00,  82590.00, 1691.28,  361.48,   -5.98, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.21, 7,    main,   -1.96,  82597.00, 1690.60,  360.79,   -5.96, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.30, 7,    main,   -1.96,  82597.00, 1690.60,  360.79,   -5.96, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.30, 7,    main,   -1.96,  82597.00, 1690.60,  360.79,   -5.96, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484098,-106.9150755,  1784.0, 2022,  6, 24, 15, 20,  3,     1046,     1117, 341,  20,   1.6,   0.8,   1.4,  0, 33, 29,  0,  0, 31,  0,  0,  0,  0, 36, 35, 32, 32,  0,  0, 29,  0, 36, 24,  0,  0,  0, 34,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   167.31, 7,    main,   -3.92,  82598.00, 1690.50,  360.70,   -5.94, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.38, 7,    main,   -3.92,  82598.00, 1690.50,  360.70,   -5.94, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.41, 7,    main,   -1.47,  82605.00, 1689.81,  360.01,   -5.93, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.51, 7,    main,   -0.98,  82601.00, 1690.20,  360.40,   -5.92, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.61, 7,    main,   -2.94,  82604.00, 1689.91,  360.11,   -5.91, 32.1, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.70, 7,    main,   -2.94,  82604.00, 1689.91,  360.11,   -5.91, 32.1, 1.41, 3.86, 3.99,   0.00,   0.00,   0.00,  62.32,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.71, 7,    main,   -3.43,  82609.00, 1689.42,  359.62,   -5.92, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.81, 7,    main,   -3.92,  82630.00, 1687.35,  357.55,   -5.93, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   167.91, 7,    main,   -0.98,  82638.00, 1686.57,  356.77,   -5.95, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.01, 7,    main,   -1.47,  82628.00, 1687.55,  357.75,   -5.97, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.02, 7,    main,   -1.47,  82628.00, 1687.55,  357.75,   -5.97, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.11, 7,    main,   -5.88,  82646.00, 1685.78,  355.98,   -5.98, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.01,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.21, 7,    main,   -1.47,  82647.00, 1685.69,  355.88,   -5.98, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.01,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.30, 7,    main,   -1.47,  82647.00, 1685.69,  355.88,   -5.98, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.01,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.30, 7,    main,   -1.47,  82647.00, 1685.69,  355.88,   -5.98, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.01,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9484273,-106.9150963,  1776.0, 2022,  6, 24, 15, 20,  4,     1049,     1116, 341,  20,   1.6,   0.8,   1.4,  0, 34, 28,  0,  0, 31,  0,  0,  0,  0, 36, 27, 30, 28,  0,  0, 22,  0, 37, 30,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   168.31, 7,    main,   -4.90,  82660.00, 1684.41,  354.61,   -5.98, 32.1, 1.41, 3.86, 3.99,   0.09,   0.00,   0.01,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.01, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.34, 7,    main,   -4.90,  82660.00, 1684.41,  354.61,   -5.98, 32.1, 1.42, 3.87, 3.98,   0.09,   0.00,   0.01,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.09, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.41, 7,    main,   -1.96,  82655.00, 1684.90,  355.10,   -5.97, 32.1, 1.42, 3.87, 3.98,   0.12,   0.00,   0.00,  62.26,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.09, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.51, 7,    main,   -2.45,  82674.00, 1683.04,  353.23,   -5.97, 32.1, 1.42, 3.87, 3.98,   0.12,   0.00,   0.00,  62.26,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.09, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.61, 7,    main,   -1.47,  82679.00, 1682.54,  352.74,   -5.96, 32.1, 1.42, 3.87, 3.98,   0.12,   0.00,   0.00,  62.26,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.09, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.66, 7,    main,   -1.47,  82679.00, 1682.54,  352.74,   -5.96, 32.1, 1.40, 3.87, 3.99,   0.12,   0.00,   0.00,  62.26,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.71, 7,    main,   -6.37,  82684.00, 1682.05,  352.25,   -5.95, 32.1, 1.40, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.81, 7,    main,   -1.96,  82690.00, 1681.47,  351.66,   -5.94, 32.1, 1.40, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.91, 7,    main,   -0.00,  82694.00, 1681.07,  351.27,   -5.93, 32.1, 1.40, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   168.98, 7,    main,   -0.00,  82694.00, 1681.07,  351.27,   -5.93, 32.1, 1.39, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.58,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.01, 7,    main,   -2.45,  82703.00, 1680.19,  350.39,   -5.93, 32.1, 1.39, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.11, 7,    main,    1.47,  82710.00, 1679.50,  349.70,   -5.94, 32.1, 1.39, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.21, 7,    main,   -0.49,  82723.00, 1678.23,  348.43,   -5.94, 32.1, 1.39, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.30, 7,    main,   -0.49,  82723.00, 1678.23,  348.43,   -5.94, 32.1, 1.40, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.30, 7,    main,   -0.49,  82723.00, 1678.23,  348.43,   -5.94, 32.1, 1.40, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.30, 7,    main,   -0.49,  82723.00, 1678.23,  348.43,   -5.94, 32.1, 1.40, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9484502,-106.9151207,  1770.0, 2022,  6, 24, 15, 20,  5,     1052,     1117, 341,  20,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 31, 27, 22, 26,  0,  0, 28,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   169.31, 7,    main,    1.96,  82715.00, 1679.01,  349.21,   -5.95, 32.1, 1.40, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.41, 7,    main,   -1.47,  82718.00, 1678.72,  348.92,   -5.96, 32.1, 1.40, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.51, 7,    main,    0.49,  82720.00, 1678.52,  348.72,   -5.98, 32.1, 1.40, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.61, 7,    main,   -2.45,  82728.00, 1677.74,  347.94,   -6.00, 32.1, 1.40, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.62, 7,    main,   -2.45,  82728.00, 1677.74,  347.94,   -6.00, 32.1, 1.37, 3.84, 3.97,   0.00,   0.00,   0.00,  62.32,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.71, 7,    main,   -3.92,  82744.00, 1676.17,  346.37,   -6.04, 32.1, 1.37, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.81, 7,    main,   -1.47,  82746.00, 1675.97,  346.17,   -6.09, 32.1, 1.37, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.91, 7,    main,   -0.49,  82758.00, 1674.79,  344.99,   -6.14, 32.1, 1.37, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   169.94, 7,    main,   -0.49,  82758.00, 1674.79,  344.99,   -6.14, 32.1, 1.36, 3.85, 3.98,   0.00,   0.00,   0.00,  61.89,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.01, 7,    main,   -2.45,  82762.00, 1674.40,  344.60,   -6.18, 32.1, 1.36, 3.85, 3.98,   0.00,   0.00,   0.00,  62.01,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.11, 7,    main,   -4.41,  82752.00, 1675.38,  345.58,   -6.23, 32.0, 1.36, 3.85, 3.98,   0.00,   0.00,   0.00,  62.01,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.21, 7,    main,   -6.37,  82769.00, 1673.72,  343.91,   -6.28, 32.0, 1.36, 3.85, 3.98,   0.00,   0.00,   0.00,  62.01,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.26, 7,    main,   -6.37,  82769.00, 1673.72,  343.91,   -6.28, 32.0, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.01,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.30, 7,    main,   -6.37,  82769.00, 1673.72,  343.91,   -6.28, 32.0, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.01,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.30, 7,    main,   -6.37,  82769.00, 1673.72,  343.91,   -6.28, 32.0, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.01,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9484810,-106.9151522,  1764.0, 2022,  6, 24, 15, 20,  6,     1056,     1119, 341,  19,   1.6,   0.8,   1.4,  0, 24, 35,  0,  0, 34,  0,  0,  0,  0, 25, 35, 33, 25,  0,  0, 30,  0, 27, 30,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   170.31, 7,    main,   -3.43,  82770.00, 1673.62,  343.82,   -6.33, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.41, 7,    main,   -5.39,  82778.00, 1672.83,  343.03,   -6.36, 32.1, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.51, 7,    main,   -4.41,  82797.00, 1670.97,  341.17,   -6.40, 32.0, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.58, 7,    main,   -4.41,  82797.00, 1670.97,  341.17,   -6.40, 32.0, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.61, 7,    main,   -4.90,  82804.00, 1670.28,  340.48,   -6.44, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.71, 7,    main,   -3.43,  82815.00, 1669.21,  339.41,   -6.46, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.81, 7,    main,   -1.96,  82812.00, 1669.50,  339.70,   -6.48, 32.1, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.90, 7,    main,   -1.96,  82812.00, 1669.50,  339.70,   -6.48, 32.1, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   170.91, 7,    main,    0.49,  82816.00, 1669.11,  339.31,   -6.49, 32.0, 1.36, 3.86, 3.98,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.01, 7,    main,   -1.47,  82832.00, 1667.54,  337.74,   -6.50, 32.1, 1.36, 3.86, 3.98,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.11, 7,    main,    1.96,  82835.00, 1667.25,  337.45,   -6.50, 32.1, 1.36, 3.86, 3.98,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.21, 7,    main,   -1.47,  82833.00, 1667.44,  337.64,   -6.51, 32.1, 1.36, 3.86, 3.98,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.01, 0.00, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.22, 7,    main,   -1.47,  82833.00, 1667.44,  337.64,   -6.51, 32.1, 1.36, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.30, 7,    main,   -1.47,  82833.00, 1667.44,  337.64,   -6.51, 32.1, 1.36, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.30, 7,    main,   -1.47,  82833.00, 1667.44,  337.64,   -6.51, 32.1, 1.36, 3.86, 3.99,   0.00,   0.01,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485137,-106.9151730,  1758.0, 2022,  6, 24, 15, 20,  7,     1060,     1121, 341,  19,   1.6,   0.8,   1.4,  0, 34, 35,  0,  0, 38,  0,  0,  0,  0, 34, 31, 22, 26,  0,  0, 29,  0, 35, 21,  0,  0,  0, 29,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.31, 7,    main,   -1.96,  82844.00, 1666.36,  336.56,   -6.51, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.41, 7,    main,   -5.39,  82842.00, 1666.56,  336.76,   -6.51, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.51, 7,    main,   -3.43,  82863.00, 1664.50,  334.70,   -6.51, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.54, 7,    main,   -3.43,  82863.00, 1664.50,  334.70,   -6.51, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.61, 7,    main,   -4.90,  82866.00, 1664.21,  334.41,   -6.50, 32.1, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.71, 7,    main,   -3.92,  82878.00, 1663.03,  333.23,   -6.50, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.81, 7,    main,   -2.94,  82880.00, 1662.84,  333.04,   -6.51, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.86, 7,    main,   -2.94,  82880.00, 1662.84,  333.04,   -6.51, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   171.91, 7,    main,   -4.90,  82883.00, 1662.54,  332.74,   -6.51, 32.1, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.01, 7,    main,   -4.90,  82881.00, 1662.74,  332.94,   -6.51, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.11, 7,    main,   -1.96,  82901.00, 1660.78,  330.98,   -6.49, 32.1, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.18, 7,    main,   -1.96,  82901.00, 1660.78,  330.98,   -6.49, 32.1, 1.37, 3.87, 3.99,   0.08,   0.00,   0.00,  62.14,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.21, 7,    main,   -2.94,  82911.00, 1659.80,  330.00,   -6.50, 32.1, 1.37, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.30, 7,    main,   -2.94,  82911.00, 1659.80,  330.00,   -6.50, 32.1, 1.37, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.30, 7,    main,   -2.94,  82911.00, 1659.80,  330.00,   -6.50, 32.1, 1.37, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9485543,-106.9151921,  1753.0, 2022,  6, 24, 15, 20,  8,     1065,     1124, 341,  19,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 34,  0,  0,  0,  0, 34, 35, 33, 29,  0,  0, 23,  0, 33, 24,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   172.31, 7,    main,   -1.96,  82913.00, 1659.61,  329.80,   -6.51, 32.0, 1.37, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.41, 7,    main,   -2.45,  82910.00, 1659.90,  330.10,   -6.52, 32.0, 1.37, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.50, 7,    main,   -2.45,  82910.00, 1659.90,  330.10,   -6.52, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.51, 7,    main,   -3.92,  82924.00, 1658.53,  328.73,   -6.53, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.61, 7,    main,   -1.96,  82935.00, 1657.45,  327.65,   -6.54, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.71, 7,    main,   -2.45,  82931.00, 1657.84,  328.04,   -6.56, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.81, 7,    main,   -5.88,  82946.00, 1656.37,  326.57,   -6.57, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.82, 7,    main,   -5.88,  82946.00, 1656.37,  326.57,   -6.57, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   172.91, 7,    main,   -5.88,  82949.00, 1656.08,  326.28,   -6.58, 32.1, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.01, 7,    main,   -4.41,  82965.00, 1654.51,  324.71,   -6.59, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.11, 7,    main,   -7.35,  82962.00, 1654.81,  325.01,   -6.60, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.14, 7,    main,   -7.35,  82962.00, 1654.81,  325.01,   -6.60, 32.0, 1.37, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.21, 7,    main,   -2.45,  82979.00, 1653.14,  323.34,   -6.61, 32.1, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.30, 7,    main,   -2.45,  82979.00, 1653.14,  323.34,   -6.61, 32.1, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.30, 7,    main,   -2.45,  82979.00, 1653.14,  323.34,   -6.61, 32.1, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9485951,-106.9152055,  1746.0, 2022,  6, 24, 15, 20,  9,     1070,     1126, 341,  18,   1.7,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 35, 35, 30, 29,  0,  0, 22,  0, 32, 24,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   173.31, 7,    main,   -2.45,  82985.00, 1652.56,  322.76,   -6.62, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.41, 7,    main,   -4.41,  82990.00, 1652.07,  322.27,   -6.64, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.46, 7,    main,   -4.41,  82990.00, 1652.07,  322.27,   -6.64, 32.0, 1.36, 3.85, 3.97,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.51, 7,    main,   -3.43,  82986.00, 1652.46,  322.66,   -6.66, 32.0, 1.36, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.61, 7,    main,   -3.92,  82986.00, 1652.46,  322.66,   -6.69, 32.0, 1.36, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.71, 7,    main,   -3.43,  83002.00, 1650.89,  321.09,   -6.71, 32.0, 1.36, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.78, 7,    main,   -3.43,  83002.00, 1650.89,  321.09,   -6.71, 32.0, 1.36, 3.86, 3.99,   0.00,   0.00,   0.00,  62.01,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.81, 7,    main,   -3.92,  83022.00, 1648.94,  319.14,   -6.73, 32.1, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   173.91, 7,    main,   -3.43,  83010.00, 1650.11,  320.31,   -6.75, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.01, 7,    main,   -3.43,  83020.00, 1649.13,  319.33,   -6.76, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.10, 7,    main,   -3.43,  83020.00, 1649.13,  319.33,   -6.76, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.11, 7,    main,   -1.96,  83026.00, 1648.55,  318.75,   -6.77, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.21, 7,    main,   -4.90,  83045.00, 1646.69,  316.89,   -6.79, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.30, 7,    main,   -4.90,  83045.00, 1646.69,  316.89,   -6.79, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.30, 7,    main,   -4.90,  83045.00, 1646.69,  316.89,   -6.79, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9486294,-106.9152023,  1740.0, 2022,  6, 24, 15, 20, 10,     1073,     1128, 341,  18,   1.6,   0.8,   1.4,  0, 33, 28,  0,  0, 33,  0,  0,  0,  0, 34, 26, 30, 28,  0,  0, 22,  0, 36, 23,  0,  0,  0, 28,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.31, 7,    main,   -3.92,  83053.00, 1645.91,  316.11,   -6.78, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.41, 7,    main,   -4.41,  83063.00, 1644.93,  315.13,   -6.76, 32.0, 1.36, 3.87, 4.00,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.42, 7,    main,   -4.41,  83063.00, 1644.93,  315.13,   -6.76, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.32,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.51, 7,    main,   -2.45,  83055.00, 1645.71,  315.91,   -6.75, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.61, 7,    main,   -1.47,  83064.00, 1644.83,  315.03,   -6.73, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.71, 7,    main,   -0.00,  83090.00, 1642.29,  312.49,   -6.70, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.74, 7,    main,   -0.00,  83090.00, 1642.29,  312.49,   -6.70, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.81, 7,    main,   -5.39,  83083.00, 1642.97,  313.17,   -6.67, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   174.91, 7,    main,   -7.35,  83079.00, 1643.36,  313.56,   -6.63, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.01, 7,    main,   -2.45,  83094.00, 1641.90,  312.10,   -6.61, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.06, 7,    main,   -2.45,  83094.00, 1641.90,  312.10,   -6.61, 32.0, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.11, 7,    main,   -0.98,  83095.00, 1641.80,  312.00,   -6.57, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.21, 7,    main,   -0.98,  83109.00, 1640.43,  310.63,   -6.52, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.30, 7,    main,   -0.98,  83109.00, 1640.43,  310.63,   -6.52, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.30, 7,    main,   -0.98,  83109.00, 1640.43,  310.63,   -6.52, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9486714,-106.9151961,  1732.0, 2022,  6, 24, 15, 20, 11,     1078,     1129, 341,  17,   1.7,   0.8,   1.4,  0, 34, 19,  0,  0, 32,  0,  0,  0,  0, 31, 26, 33, 28,  0,  0, 29,  0, 34, 25,  0,  0,  0, 27,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.31, 7,    main,   -1.47,  83114.00, 1639.94,  310.14,   -6.49, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.38, 7,    main,   -1.47,  83114.00, 1639.94,  310.14,   -6.49, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.41, 7,    main,    1.96,  83143.00, 1637.11,  307.31,   -6.46, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.51, 7,    main,   -0.98,  83126.00, 1638.77,  308.97,   -6.43, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.61, 7,    main,   -3.43,  83150.00, 1636.43,  306.62,   -6.42, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.70, 7,    main,   -3.43,  83150.00, 1636.43,  306.62,   -6.42, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.71, 7,    main,   -2.45,  83144.00, 1637.01,  307.21,   -6.41, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.81, 7,    main,   -0.98,  83147.00, 1636.72,  306.92,   -6.42, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   175.91, 7,    main,   -2.45,  83155.00, 1635.94,  306.14,   -6.44, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.01, 7,    main,   -1.47,  83160.00, 1635.45,  305.65,   -6.47, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.02, 7,    main,   -1.47,  83160.00, 1635.45,  305.65,   -6.47, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.32,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.11, 7,    main,   -3.43,  83154.00, 1636.03,  306.23,   -6.50, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.21, 7,    main,   -2.94,  83187.00, 1632.81,  303.01,   -6.55, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.30, 7,    main,   -2.94,  83187.00, 1632.81,  303.01,   -6.55, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.30, 7,    main,   -2.94,  83187.00, 1632.81,  303.01,   -6.55, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9487221,-106.9151999,  1725.0, 2022,  6, 24, 15, 20, 12,     1083,     1132, 341,  17,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 27,  0,  0,  0,  0, 31, 35, 34, 29,  0,  0, 23,  0, 26, 31,  0,  0,  0, 34,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.31, 7,    main,   -1.47,  83164.00, 1635.06,  305.26,   -6.61, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.34, 7,    main,   -1.47,  83164.00, 1635.06,  305.26,   -6.61, 32.0, 1.37, 3.87, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.41, 7,    main,   -4.90,  83179.00, 1633.59,  303.79,   -6.68, 32.0, 1.37, 3.87, 3.98,   0.00,   0.00,   0.03,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.51, 7,    main,   -4.41,  83195.00, 1632.03,  302.23,   -6.73, 32.0, 1.37, 3.87, 3.98,   0.00,   0.00,   0.03,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.61, 7,    main,   -4.90,  83201.00, 1631.44,  301.64,   -6.80, 32.0, 1.37, 3.87, 3.98,   0.00,   0.00,   0.03,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.03, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.66, 7,    main,   -4.90,  83201.00, 1631.44,  301.64,   -6.80, 32.0, 1.36, 3.86, 3.99,   0.00,   0.00,   0.03,  62.32,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.71, 7,    main,   -4.41,  83199.00, 1631.64,  301.84,   -6.87, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.81, 7,    main,   -4.41,  83218.00, 1629.78,  299.98,   -6.94, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.91, 7,    main,   -4.41,  83221.00, 1629.49,  299.69,   -6.99, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   176.98, 7,    main,   -4.41,  83221.00, 1629.49,  299.69,   -6.99, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.14,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   177.01, 7,    main,   -5.39,  83243.00, 1627.34,  297.54,   -7.04, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   177.11, 7,    main,   -4.41,  83233.00, 1628.32,  298.52,   -7.09, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   177.21, 7,    main,   -3.43,  83227.00, 1628.91,  299.10,   -7.13, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487625,-106.9152172,  1718.0, 2022,  6, 24, 15, 20, 13,     1088,     1135, 341,  17,   1.6,   0.8,   1.4,  0, 39, 29,  0,  0, 34,  0,  0,  0,  0, 35, 30, 33, 37,  0,  0, 33,  0, 26, 23,  0,  0,  0, 23,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   177.30, 7,    main,   -3.43,  83227.00, 1628.91,  299.10,   -7.13, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.30, 7,    main,   -3.43,  83227.00, 1628.91,  299.10,   -7.13, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.30, 7,    main,   -3.43,  83227.00, 1628.91,  299.10,   -7.13, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.31, 7,    main,   -1.47,  83257.00, 1625.98,  296.18,   -7.16, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.41, 7,    main,   -0.49,  83259.00, 1625.78,  295.98,   -7.18, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.51, 7,    main,   -2.45,  83270.00, 1624.71,  294.91,   -7.17, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.61, 7,    main,   -2.94,  83277.00, 1624.03,  294.23,   -7.16, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.62, 7,    main,   -2.94,  83277.00, 1624.03,  294.23,   -7.16, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.71, 7,    main,    0.98,  83277.00, 1624.03,  294.23,   -7.13, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.81, 7,    main,   -2.94,  83298.00, 1621.98,  292.18,   -7.09, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.91, 7,    main,   -0.49,  83299.00, 1621.88,  292.08,   -7.06, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   177.94, 7,    main,   -0.49,  83299.00, 1621.88,  292.08,   -7.06, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.01, 7,    main,    1.47,  83302.00, 1621.59,  291.79,   -7.01, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.11, 7,    main,   -0.98,  83314.00, 1620.42,  290.62,   -6.96, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.21, 7,    main,   -0.98,  83313.00, 1620.51,  290.71,   -6.92, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.26, 7,    main,   -0.98,  83313.00, 1620.51,  290.71,   -6.92, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.20,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.30, 7,    main,   -0.98,  83313.00, 1620.51,  290.71,   -6.92, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.20,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.30, 7,    main,   -0.98,  83313.00, 1620.51,  290.71,   -6.92, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.20,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9487996,-106.9152468,  1712.0, 2022,  6, 24, 15, 20, 14,     1093,     1138, 341,  16,   1.6,   0.8,   1.4,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 31, 28, 31,  0,  0, 32,  0, 32, 24,  0,  0,  0, 26,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.31, 7,    main,   -4.90,  83323.00, 1619.54,  289.74,   -6.86, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.41, 7,    main,   -0.00,  83338.00, 1618.08,  288.28,   -6.81, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.51, 7,    main,   -3.92,  83339.00, 1617.98,  288.18,   -6.77, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.58, 7,    main,   -3.92,  83339.00, 1617.98,  288.18,   -6.77, 32.0, 1.37, 3.86, 3.98,   0.09,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.61, 7,    main,   -4.41,  83350.00, 1616.91,  287.10,   -6.74, 32.0, 1.37, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.71, 7,    main,   -2.94,  83358.00, 1616.13,  286.32,   -6.70, 32.0, 1.37, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.81, 7,    main,   -2.94,  83365.00, 1615.44,  285.64,   -6.68, 32.0, 1.37, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.90, 7,    main,   -2.94,  83365.00, 1615.44,  285.64,   -6.68, 32.0, 1.37, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   178.91, 7,    main,   -2.94,  83367.00, 1615.25,  285.45,   -6.66, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.01, 7,    main,   -6.37,  83375.00, 1614.47,  284.67,   -6.66, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.11, 7,    main,   -1.96,  83383.00, 1613.69,  283.89,   -6.65, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.21, 7,    main,   -5.88,  83389.00, 1613.10,  283.30,   -6.62, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.22, 7,    main,   -5.88,  83389.00, 1613.10,  283.30,   -6.62, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.30, 7,    main,   -5.88,  83389.00, 1613.10,  283.30,   -6.62, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.30, 7,    main,   -5.88,  83389.00, 1613.10,  283.30,   -6.62, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488392,-106.9152780,  1704.0, 2022,  6, 24, 15, 20, 15,     1098,     1141, 341,  16,   1.6,   0.8,   1.4,  0, 36, 29,  0,  0, 32,  0,  0,  0,  0, 37, 34, 29, 31,  0,  0, 27,  0, 33, 26,  0,  0,  0, 31,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   179.31, 7,    main,   -4.90,  83382.00, 1613.79,  283.99,   -6.62, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.41, 7,    main,   -6.86,  83392.00, 1612.81,  283.01,   -6.62, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.51, 7,    main,   -3.92,  83396.00, 1612.42,  282.62,   -6.62, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.54, 7,    main,   -3.92,  83396.00, 1612.42,  282.62,   -6.62, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.61, 7,    main,   -6.86,  83415.00, 1610.57,  280.77,   -6.62, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.71, 7,    main,   -2.45,  83421.00, 1609.99,  280.18,   -6.61, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.81, 7,    main,    0.98,  83425.00, 1609.60,  279.79,   -6.61, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.03, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.86, 7,    main,    0.98,  83425.00, 1609.60,  279.79,   -6.61, 32.0, 1.35, 3.85, 3.96,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   179.91, 7,    main,   -0.00,  83444.00, 1607.74,  277.94,   -6.60, 32.0, 1.35, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.01, 7,    main,   -0.98,  83442.00, 1607.94,  278.14,   -6.59, 32.0, 1.35, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.11, 7,    main,   -0.49,  83454.00, 1606.77,  276.97,   -6.57, 32.0, 1.35, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.18, 7,    main,   -0.49,  83454.00, 1606.77,  276.97,   -6.57, 32.0, 1.35, 3.87, 3.98,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.21, 7,    main,   -0.00,  83462.00, 1605.99,  276.19,   -6.54, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.30, 7,    main,   -0.00,  83462.00, 1605.99,  276.19,   -6.54, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.30, 7,    main,   -0.00,  83462.00, 1605.99,  276.19,   -6.54, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488849,-106.9153006,  1697.0, 2022,  6, 24, 15, 20, 16,     1103,     1144, 341,  15,   1.7,   0.8,   1.4,  0, 31, 36,  0,  0, 26,  0,  0,  0,  0, 31, 35, 34, 24,  0,  0, 38,  0, 38, 35,  0,  0,  0, 32,  0,  0,  0,  0,  0, 35,  0,  0
+6, 6583, 3,VE3LIC,   180.31, 7,    main,   -0.49,  83455.00, 1606.67,  276.87,   -6.51, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.41, 7,    main,    0.98,  83462.00, 1605.99,  276.19,   -6.49, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.50, 7,    main,    0.98,  83462.00, 1605.99,  276.19,   -6.49, 32.0, 1.35, 3.84, 3.98,   0.08,   0.00,   0.00,  62.32,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.51, 7,    main,   -2.94,  83479.00, 1604.34,  274.53,   -6.45, 32.0, 1.35, 3.84, 3.98,   0.00,   0.00,   0.00,  61.89,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.61, 7,    main,   -4.41,  83485.00, 1603.75,  273.95,   -6.41, 32.0, 1.35, 3.84, 3.98,   0.00,   0.00,   0.00,  61.89,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.71, 7,    main,   -4.41,  83491.00, 1603.17,  273.37,   -6.38, 32.0, 1.35, 3.84, 3.98,   0.00,   0.00,   0.00,  61.89,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.81, 7,    main,   -4.41,  83492.00, 1603.07,  273.27,   -6.34, 32.0, 1.35, 3.84, 3.98,   0.00,   0.00,   0.00,  61.89,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.82, 7,    main,   -4.41,  83492.00, 1603.07,  273.27,   -6.34, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  61.89,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   180.91, 7,    main,   -8.34,  83511.00, 1601.22,  271.42,   -6.32, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.01, 7,    main,   -3.43,  83513.00, 1601.03,  271.22,   -6.29, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.11, 7,    main,   -9.81,  83513.00, 1601.03,  271.22,   -6.26, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.14, 7,    main,   -9.81,  83513.00, 1601.03,  271.22,   -6.26, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.21, 7,    main,   -3.43,  83510.00, 1601.32,  271.52,   -6.25, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.30, 7,    main,   -3.43,  83510.00, 1601.32,  271.52,   -6.25, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.30, 7,    main,   -3.43,  83510.00, 1601.32,  271.52,   -6.25, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489373,-106.9153057,  1690.0, 2022,  6, 24, 15, 20, 17,     1109,     1148, 341,  15,   1.6,   0.8,   1.4,  0, 29, 29,  0,  0, 31,  0,  0,  0,  0, 31, 35, 30, 29,  0,  0, 38,  0, 38, 31,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   181.31, 7,    main,   -1.47,  83521.00, 1600.25,  270.45,   -6.23, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.41, 7,    main,   -0.00,  83534.00, 1598.98,  269.18,   -6.22, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.46, 7,    main,   -0.00,  83534.00, 1598.98,  269.18,   -6.22, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.51, 7,    main,   -2.94,  83546.00, 1597.81,  268.01,   -6.22, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.61, 7,    main,    0.49,  83549.00, 1597.52,  267.72,   -6.23, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.71, 7,    main,   -2.94,  83551.00, 1597.33,  267.53,   -6.24, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.78, 7,    main,   -2.94,  83551.00, 1597.33,  267.53,   -6.24, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.81, 7,    main,   -0.49,  83553.00, 1597.13,  267.33,   -6.26, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   181.91, 7,    main,   -0.00,  83573.00, 1595.19,  265.39,   -6.29, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.01, 7,    main,   -3.92,  83570.00, 1595.48,  265.68,   -6.32, 32.0, 1.36, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.10, 7,    main,   -3.92,  83570.00, 1595.48,  265.68,   -6.32, 32.0, 1.35, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.11, 7,    main,   -1.96,  83570.00, 1595.48,  265.68,   -6.35, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.21, 7,    main,   -1.96,  83589.00, 1593.63,  263.83,   -6.38, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.30, 7,    main,   -1.96,  83589.00, 1593.63,  263.83,   -6.38, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.30, 7,    main,   -1.96,  83589.00, 1593.63,  263.83,   -6.38, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489885,-106.9153062,  1683.0, 2022,  6, 24, 15, 20, 18,     1114,     1151, 341,  15,   1.6,   0.8,   1.4,  0, 29, 30,  0,  0, 31,  0,  0,  0,  0, 25, 34, 29, 23,  0,  0, 32,  0, 37, 27,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   182.31, 7,    main,   -4.41,  83580.00, 1594.51,  264.70,   -6.40, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.41, 7,    main,   -0.98,  83602.00, 1592.37,  262.56,   -6.43, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.42, 7,    main,   -0.98,  83602.00, 1592.37,  262.56,   -6.43, 32.0, 1.35, 3.87, 3.98,   0.00,   0.00,   0.00,  62.14,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.51, 7,    main,   -3.43,  83593.00, 1593.24,  263.44,   -6.46, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.61, 7,    main,   -2.45,  83609.00, 1591.68,  261.88,   -6.49, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.71, 7,    main,   -5.39,  83624.00, 1590.23,  260.42,   -6.52, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.74, 7,    main,   -5.39,  83624.00, 1590.23,  260.42,   -6.52, 32.0, 1.35, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.81, 7,    main,   -2.45,  83623.00, 1590.32,  260.52,   -6.54, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   182.91, 7,    main,   -3.43,  83642.00, 1588.48,  258.67,   -6.57, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.01, 7,    main,   -0.00,  83634.00, 1589.25,  259.45,   -6.60, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.06, 7,    main,   -0.00,  83634.00, 1589.25,  259.45,   -6.60, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.11, 7,    main,   -3.43,  83639.00, 1588.77,  258.97,   -6.62, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.21, 7,    main,   -6.37,  83659.00, 1586.82,  257.02,   -6.64, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.30, 7,    main,   -6.37,  83659.00, 1586.82,  257.02,   -6.64, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.30, 7,    main,   -6.37,  83659.00, 1586.82,  257.02,   -6.64, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490331,-106.9153122,  1676.0, 2022,  6, 24, 15, 20, 19,     1119,     1154, 341,  14,   1.6,   0.8,   1.4,  0, 29, 31,  0,  0, 37,  0,  0,  0,  0, 24, 31, 29, 34,  0,  0, 22,  0, 24, 28,  0,  0,  0, 30,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   183.31, 7,    main,   -7.35,  83656.00, 1587.11,  257.31,   -6.66, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.38, 7,    main,   -7.35,  83656.00, 1587.11,  257.31,   -6.66, 32.0, 1.35, 3.86, 3.98,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.41, 7,    main,   -3.92,  83660.00, 1586.73,  256.92,   -6.69, 32.0, 1.35, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.51, 7,    main,   -3.92,  83674.00, 1585.36,  255.56,   -6.72, 32.0, 1.35, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.61, 7,    main,   -0.00,  83670.00, 1585.75,  255.95,   -6.74, 32.0, 1.35, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.70, 7,    main,   -0.00,  83670.00, 1585.75,  255.95,   -6.74, 32.0, 1.35, 3.87, 3.99,   0.01,   0.00,   0.00,  62.20,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.71, 7,    main,   -2.45,  83686.00, 1584.20,  254.40,   -6.76, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.81, 7,    main,    3.92,  83694.00, 1583.42,  253.62,   -6.77, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   183.91, 7,    main,   -0.49,  83707.00, 1582.16,  252.36,   -6.80, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.01, 7,    main,   -1.96,  83705.00, 1582.35,  252.55,   -6.82, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.02, 7,    main,   -1.96,  83705.00, 1582.35,  252.55,   -6.82, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.32,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.11, 7,    main,   -0.49,  83716.00, 1581.28,  251.48,   -6.84, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.21, 7,    main,    0.49,  83711.00, 1581.77,  251.97,   -6.86, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.30, 7,    main,    0.49,  83711.00, 1581.77,  251.97,   -6.86, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.30, 7,    main,    0.49,  83711.00, 1581.77,  251.97,   -6.86, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490719,-106.9153096,  1670.0, 2022,  6, 24, 15, 20, 20,     1123,     1156, 341,  14,   1.6,   0.8,   1.4,  0, 38, 26,  0,  0, 39,  0,  0,  0,  0, 37, 34, 30, 29,  0,  0, 22,  0, 30, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   184.31, 7,    main,   -1.96,  83723.00, 1580.60,  250.80,   -6.89, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.34, 7,    main,   -1.96,  83723.00, 1580.60,  250.80,   -6.89, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.41, 7,    main,   -1.47,  83740.00, 1578.95,  249.15,   -6.92, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.51, 7,    main,   -3.43,  83736.00, 1579.34,  249.54,   -6.95, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.61, 7,    main,   -5.39,  83751.00, 1577.88,  248.08,   -6.99, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.66, 7,    main,   -5.39,  83751.00, 1577.88,  248.08,   -6.99, 32.0, 1.35, 3.85, 3.97,   0.08,   0.00,   0.00,  62.32,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.71, 7,    main,    0.49,  83758.00, 1577.20,  247.40,   -7.03, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.81, 7,    main,   -0.49,  83766.00, 1576.43,  246.63,   -7.07, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.91, 7,    main,   -0.98,  83769.00, 1576.13,  246.33,   -7.12, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   184.98, 7,    main,   -0.98,  83769.00, 1576.13,  246.33,   -7.12, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   185.01, 7,    main,   -2.94,  83779.00, 1575.16,  245.36,   -7.16, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   185.11, 7,    main,   -0.00,  83784.00, 1574.68,  244.88,   -7.20, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   185.21, 7,    main,   -3.43,  83792.00, 1573.90,  244.10,   -7.25, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9491197,-106.9152953,  1661.0, 2022,  6, 24, 15, 20, 21,     1128,     1159, 341,  13,   1.6,   0.8,   1.4,  0, 35, 27,  0,  0, 39,  0,  0,  0,  0, 32, 30, 33, 29,  0,  0, 25,  0, 36, 27,  0,  0,  0, 29,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   185.30, 7,    main,   -3.43,  83792.00, 1573.90,  244.10,   -7.25, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.30, 7,    main,   -3.43,  83792.00, 1573.90,  244.10,   -7.25, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.30, 7,    main,   -3.43,  83792.00, 1573.90,  244.10,   -7.25, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  61.95,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.31, 7,    main,   -1.47,  83801.00, 1573.03,  243.23,   -7.30, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.41, 7,    main,   -3.43,  83805.00, 1572.64,  242.84,   -7.34, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.51, 7,    main,    2.45,  83820.00, 1571.18,  241.38,   -7.39, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.61, 7,    main,   -0.49,  83813.00, 1571.86,  242.06,   -7.43, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.62, 7,    main,   -0.49,  83813.00, 1571.86,  242.06,   -7.43, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.71, 7,    main,   -2.45,  83831.00, 1570.12,  240.32,   -7.47, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.81, 7,    main,   -2.94,  83825.00, 1570.70,  240.90,   -7.51, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.91, 7,    main,   -0.98,  83845.00, 1568.76,  238.96,   -7.55, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   185.94, 7,    main,   -0.98,  83845.00, 1568.76,  238.96,   -7.55, 32.0, 1.36, 3.87, 3.98,   0.00,   0.00,   0.00,  62.20,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.01, 7,    main,   -3.43,  83860.00, 1567.30,  237.50,   -7.59, 32.0, 1.36, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.11, 7,    main,   -4.90,  83860.00, 1567.30,  237.50,   -7.61, 32.0, 1.36, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.21, 7,    main,   -3.43,  83859.00, 1567.40,  237.60,   -7.63, 32.0, 1.36, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.26, 7,    main,   -3.43,  83859.00, 1567.40,  237.60,   -7.63, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.26,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.30, 7,    main,   -3.43,  83859.00, 1567.40,  237.60,   -7.63, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.26,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.30, 7,    main,   -3.43,  83859.00, 1567.40,  237.60,   -7.63, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.26,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491510,-106.9152702,  1654.0, 2022,  6, 24, 15, 20, 22,     1130,     1160, 342,  13,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 27, 33, 30, 22,  0,  0, 31,  0, 30, 28,  0,  0,  0, 36,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.31, 7,    main,   -5.88,  83886.00, 1564.78,  234.98,   -7.64, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.41, 7,    main,   -0.98,  83884.00, 1564.97,  235.17,   -7.65, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.51, 7,    main,   -1.96,  83901.00, 1563.32,  233.52,   -7.64, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.58, 7,    main,   -1.96,  83901.00, 1563.32,  233.52,   -7.64, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.14,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.61, 7,    main,   -1.47,  83905.00, 1562.94,  233.14,   -7.63, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.71, 7,    main,   -2.94,  83902.00, 1563.23,  233.43,   -7.62, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.81, 7,    main,   -2.45,  83928.00, 1560.71,  230.91,   -7.61, 32.0, 1.36, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.90, 7,    main,   -2.45,  83928.00, 1560.71,  230.91,   -7.61, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   186.91, 7,    main,   -1.47,  83926.00, 1560.90,  231.10,   -7.59, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.01, 7,    main,   -3.43,  83932.00, 1560.32,  230.52,   -7.57, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.11, 7,    main,   -2.94,  83940.00, 1559.54,  229.74,   -7.55, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.21, 7,    main,   -6.37,  83944.00, 1559.16,  229.35,   -7.53, 32.0, 1.35, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.22, 7,    main,   -6.37,  83944.00, 1559.16,  229.35,   -7.53, 32.0, 1.35, 3.87, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.30, 7,    main,   -6.37,  83944.00, 1559.16,  229.35,   -7.53, 32.0, 1.35, 3.87, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.30, 7,    main,   -6.37,  83944.00, 1559.16,  229.35,   -7.53, 32.0, 1.35, 3.87, 3.99,   0.00,   0.00,   0.00,  62.20,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491527,-106.9152341,  1646.0, 2022,  6, 24, 15, 20, 23,     1129,     1157, 342,  13,   1.7,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 25, 32, 33, 23,  0,  0, 36,  0, 36, 19,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   187.31, 7,    main,   -1.47,  83966.00, 1557.02,  227.22,   -7.50, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.41, 7,    main,   -5.39,  83954.00, 1558.19,  228.39,   -7.48, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.51, 7,    main,   -3.92,  83966.00, 1557.02,  227.22,   -7.45, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.54, 7,    main,   -3.92,  83966.00, 1557.02,  227.22,   -7.45, 32.0, 1.35, 3.85, 3.97,   0.08,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.61, 7,    main,   -4.41,  83978.00, 1555.86,  226.06,   -7.42, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.71, 7,    main,   -1.96,  83994.00, 1554.31,  224.51,   -7.40, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.81, 7,    main,   -3.92,  83995.00, 1554.21,  224.41,   -7.38, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.86, 7,    main,   -3.92,  83995.00, 1554.21,  224.41,   -7.38, 32.0, 1.35, 3.87, 3.98,   0.00,   0.00,   0.00,  61.95,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   187.91, 7,    main,   -1.47,  84008.00, 1552.95,  223.15,   -7.35, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.01, 7,    main,   -0.98,  84019.00, 1551.89,  222.09,   -7.34, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.11, 7,    main,    2.94,  84019.00, 1551.89,  222.09,   -7.32, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.18, 7,    main,    2.94,  84019.00, 1551.89,  222.09,   -7.32, 32.0, 1.36, 3.86, 3.98,   0.09,   0.00,   0.00,  62.26,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.21, 7,    main,   -1.47,  84022.00, 1551.60,  221.80,   -7.29, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.30, 7,    main,   -1.47,  84022.00, 1551.60,  221.80,   -7.29, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.30, 7,    main,   -1.47,  84022.00, 1551.60,  221.80,   -7.29, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491274,-106.9152009,  1637.0, 2022,  6, 24, 15, 20, 24,     1126,     1152, 342,  12,   1.7,   0.8,   1.4,  0, 29, 29,  0,  0, 39,  0,  0,  0,  0, 25, 27, 30, 33,  0,  0, 34,  0, 23, 28,  0,  0,  0, 28,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.31, 7,    main,   -0.00,  84027.00, 1551.11,  221.31,   -7.27, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.41, 7,    main,   -3.92,  84037.00, 1550.14,  220.34,   -7.25, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.50, 7,    main,   -3.92,  84037.00, 1550.14,  220.34,   -7.25, 32.0, 1.35, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.51, 7,    main,   -0.98,  84032.00, 1550.63,  220.83,   -7.23, 32.0, 1.35, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.61, 7,    main,    1.47,  84062.00, 1547.72,  217.92,   -7.21, 32.0, 1.35, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.71, 7,    main,   -2.94,  84063.00, 1547.63,  217.82,   -7.19, 32.0, 1.35, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.81, 7,    main,   -4.90,  84074.00, 1546.56,  216.76,   -7.17, 32.0, 1.35, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.82, 7,    main,   -4.90,  84074.00, 1546.56,  216.76,   -7.17, 32.0, 1.35, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   188.91, 7,    main,   -3.92,  84086.00, 1545.40,  215.60,   -7.14, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.01, 7,    main,   -3.43,  84090.00, 1545.01,  215.21,   -7.11, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.11, 7,    main,   -6.37,  84090.00, 1545.01,  215.21,   -7.09, 32.0, 1.35, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.14, 7,    main,   -6.37,  84090.00, 1545.01,  215.21,   -7.09, 32.0, 1.34, 3.86, 3.98,   0.08,   0.00,   0.00,  62.26,  21.73,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.21, 7,    main,   -2.45,  84103.00, 1543.75,  213.95,   -7.06, 32.0, 1.34, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.30, 7,    main,   -2.45,  84103.00, 1543.75,  213.95,   -7.06, 32.0, 1.34, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.30, 7,    main,   -2.45,  84103.00, 1543.75,  213.95,   -7.06, 32.0, 1.34, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490794,-106.9151795,  1629.0, 2022,  6, 24, 15, 20, 25,     1120,     1144, 342,  12,   1.7,   0.8,   1.4,  0, 18, 28,  0,  0, 39,  0,  0,  0,  0, 24, 27, 29, 30,  0,  0, 35,  0, 24, 29,  0,  0,  0, 21,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   189.31, 7,    main,   -0.49,  84104.00, 1543.66,  213.86,   -7.04, 32.0, 1.34, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.41, 7,    main,   -2.45,  84115.00, 1542.59,  212.79,   -7.01, 32.0, 1.34, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.46, 7,    main,   -2.45,  84115.00, 1542.59,  212.79,   -7.01, 32.0, 1.35, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.51, 7,    main,   -0.98,  84114.00, 1542.69,  212.89,   -6.98, 32.0, 1.35, 3.86, 3.99,   0.07,   0.00,   0.00,  62.20,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.61, 7,    main,   -0.00,  84126.00, 1541.53,  211.73,   -6.96, 32.0, 1.35, 3.86, 3.99,   0.07,   0.00,   0.00,  62.20,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.71, 7,    main,   -2.94,  84144.00, 1539.79,  209.98,   -6.93, 32.0, 1.35, 3.86, 3.99,   0.07,   0.00,   0.00,  62.20,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.78, 7,    main,   -2.94,  84144.00, 1539.79,  209.98,   -6.93, 32.0, 1.35, 3.85, 3.97,   0.07,   0.00,   0.00,  62.20,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.81, 7,    main,   -5.39,  84143.00, 1539.88,  210.08,   -6.91, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   189.91, 7,    main,   -3.92,  84145.00, 1539.69,  209.89,   -6.88, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.01, 7,    main,   -4.90,  84161.00, 1538.14,  208.34,   -6.84, 32.0, 1.35, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.10, 7,    main,   -4.90,  84161.00, 1538.14,  208.34,   -6.84, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  62.01,  21.67,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.11, 7,    main,   -2.94,  84167.00, 1537.56,  207.76,   -6.80, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.21, 7,    main,   -6.37,  84163.00, 1537.95,  208.15,   -6.76, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.30, 7,    main,   -6.37,  84163.00, 1537.95,  208.15,   -6.76, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.30, 7,    main,   -6.37,  84163.00, 1537.95,  208.15,   -6.76, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490195,-106.9151800,  1621.0, 2022,  6, 24, 15, 20, 26,     1114,     1137, 342,  12,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 38,  0,  0,  0,  0, 37, 28, 29, 32,  0,  0, 35,  0, 22, 28,  0,  0,  0, 21,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   190.31, 7,    main,   -5.39,  84168.00, 1537.46,  207.66,   -6.71, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.41, 7,    main,   -3.92,  84198.00, 1534.56,  204.76,   -6.67, 32.0, 1.33, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.42, 7,    main,   -3.92,  84198.00, 1534.56,  204.76,   -6.67, 32.0, 1.34, 3.86, 3.98,   0.00,   0.00,   0.00,  61.89,  21.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.51, 7,    main,   -2.45,  84188.00, 1535.53,  205.73,   -6.62, 32.0, 1.34, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.61, 7,    main,   -5.39,  84216.00, 1532.82,  203.02,   -6.58, 32.0, 1.34, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.71, 7,    main,   -0.98,  84207.00, 1533.69,  203.89,   -6.54, 32.0, 1.34, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.74, 7,    main,   -0.98,  84207.00, 1533.69,  203.89,   -6.54, 32.0, 1.34, 3.87, 3.99,   0.00,   0.00,   0.00,  62.20,  21.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.81, 7,    main,   -4.41,  84218.00, 1532.63,  202.83,   -6.50, 32.0, 1.34, 3.87, 3.99,   0.09,   0.00,   0.00,  62.38,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   190.91, 7,    main,   -7.85,  84212.00, 1533.21,  203.41,   -6.47, 32.0, 1.34, 3.87, 3.99,   0.09,   0.00,   0.00,  62.38,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.01, 7,    main,   -2.94,  84219.00, 1532.53,  202.73,   -6.43, 32.0, 1.34, 3.87, 3.99,   0.09,   0.00,   0.00,  62.38,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.06, 7,    main,   -2.94,  84219.00, 1532.53,  202.73,   -6.43, 32.0, 1.34, 3.86, 3.98,   0.09,   0.00,   0.00,  62.38,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.11, 7,    main,    0.49,  84234.00, 1531.08,  201.28,   -6.39, 32.0, 1.34, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.21, 7,    main,   -2.45,  84249.00, 1529.63,  199.83,   -6.36, 32.0, 1.34, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.30, 7,    main,   -2.45,  84249.00, 1529.63,  199.83,   -6.36, 32.0, 1.34, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.30, 7,    main,   -2.45,  84249.00, 1529.63,  199.83,   -6.36, 32.0, 1.34, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489645,-106.9152057,  1613.0, 2022,  6, 24, 15, 20, 27,     1109,     1130, 341,  11,   1.6,   0.8,   1.4,  0, 28, 28,  0,  0, 31,  0,  0,  0,  0, 32, 28, 28, 36,  0,  0, 26,  0, 22, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   191.31, 7,    main,   -1.96,  84238.00, 1530.69,  200.89,   -6.33, 32.0, 1.34, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.38, 7,    main,   -1.96,  84238.00, 1530.69,  200.89,   -6.33, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.41, 7,    main,   -4.41,  84256.00, 1528.95,  199.15,   -6.32, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.51, 7,    main,   -0.00,  84262.00, 1528.37,  198.57,   -6.30, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.61, 7,    main,   -2.94,  84271.00, 1527.50,  197.70,   -6.30, 32.0, 1.35, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.70, 7,    main,   -2.94,  84271.00, 1527.50,  197.70,   -6.30, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.14,  21.79,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.71, 7,    main,   -1.47,  84265.00, 1528.08,  198.28,   -6.31, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.81, 7,    main,   -2.45,  84284.00, 1526.25,  196.45,   -6.32, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   191.91, 7,    main,   -2.45,  84281.00, 1526.54,  196.74,   -6.34, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.01, 7,    main,   -4.41,  84282.00, 1526.44,  196.64,   -6.36, 32.0, 1.36, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.02, 7,    main,   -4.41,  84282.00, 1526.44,  196.64,   -6.36, 32.0, 1.37, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.11, 7,    main,   -3.92,  84290.00, 1525.67,  195.87,   -6.39, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.01,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.21, 7,    main,   -2.45,  84308.00, 1523.93,  194.13,   -6.41, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.01,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.30, 7,    main,   -2.45,  84308.00, 1523.93,  194.13,   -6.41, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.01,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.30, 7,    main,   -2.45,  84308.00, 1523.93,  194.13,   -6.41, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.01,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1,  9,  32.9489186,-106.9152596,  1606.0, 2022,  6, 24, 15, 20, 28,     1105,     1126, 341,  11,   2.1,   0.9,   1.9,  0, 35, 29,  0,  0, 36,  0,  0,  0,  0, 26, 28, 29, 36,  0,  0, 23,  0, 31, 28,  0,  0,  0, 22,  0,  0,  0,  0,  0, 30,  0,  0
+6, 6583, 3,VE3LIC,   192.31, 7,    main,   -3.92,  84315.00, 1523.25,  193.45,   -6.44, 32.0, 1.37, 3.86, 3.99,   0.09,   0.00,   0.01,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.01, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.34, 7,    main,   -3.92,  84315.00, 1523.25,  193.45,   -6.44, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.01,  62.14,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.41, 7,    main,   -5.39,  84320.00, 1522.77,  192.97,   -6.49, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.51, 7,    main,   -0.49,  84320.00, 1522.77,  192.97,   -6.54, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.61, 7,    main,   -4.41,  84323.00, 1522.48,  192.68,   -6.60, 32.0, 1.38, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.66, 7,    main,   -4.41,  84323.00, 1522.48,  192.68,   -6.60, 32.0, 1.36, 3.87, 3.99,   0.09,   0.00,   0.00,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.71, 7,    main,   -0.00,  84337.00, 1521.13,  191.33,   -6.64, 32.0, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.81, 7,    main,   -3.43,  84347.00, 1520.16,  190.36,   -6.70, 32.0, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.91, 7,    main,   -1.96,  84348.00, 1520.07,  190.27,   -6.74, 32.0, 1.36, 3.87, 3.99,   0.00,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   192.98, 7,    main,   -1.96,  84348.00, 1520.07,  190.27,   -6.74, 32.0, 1.37, 3.86, 3.98,   0.00,   0.00,   0.00,  62.26,  21.97,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   193.01, 7,    main,   -2.45,  84353.00, 1519.58,  189.78,   -6.78, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   193.11, 7,    main,   -1.47,  84367.00, 1518.23,  188.43,   -6.84, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   193.21, 7,    main,   -4.41,  84373.00, 1517.65,  187.85,   -6.89, 32.0, 1.37, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488884,-106.9153264,  1598.0, 2022,  6, 24, 15, 20, 29,     1104,     1123, 341,  10,   1.6,   0.8,   1.4,  0, 35, 34,  0,  0, 37,  0,  0,  0,  0, 36, 29, 30, 33,  0,  0, 26,  0, 33, 28,  0,  0,  0, 26,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   193.30, 7,    main,   -4.41,  84373.00, 1517.65,  187.85,   -6.89, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.30, 7,    main,   -4.41,  84373.00, 1517.65,  187.85,   -6.89, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.30, 7,    main,   -4.41,  84373.00, 1517.65,  187.85,   -6.89, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.31, 7,    main,   -2.94,  84382.00, 1516.78,  186.98,   -6.93, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.41, 7,    main,    2.45,  84390.00, 1516.01,  186.21,   -6.98, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.51, 7,    main,   -3.43,  84389.00, 1516.11,  186.31,   -7.02, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.61, 7,    main,   -3.43,  84409.00, 1514.18,  184.38,   -7.05, 32.0, 1.36, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.62, 7,    main,   -3.43,  84409.00, 1514.18,  184.38,   -7.05, 32.0, 1.38, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  21.91,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.71, 7,    main,   -0.98,  84410.00, 1514.08,  184.28,   -7.08, 32.0, 1.38, 3.86, 3.98,   0.06,   0.00,   0.01,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.81, 7,    main,   -2.94,  84411.00, 1513.98,  184.18,   -7.11, 32.0, 1.38, 3.86, 3.98,   0.06,   0.00,   0.01,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.91, 7,    main,   -4.90,  84417.00, 1513.41,  183.60,   -7.12, 32.0, 1.38, 3.86, 3.98,   0.06,   0.00,   0.01,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   193.94, 7,    main,   -4.90,  84417.00, 1513.41,  183.60,   -7.12, 32.0, 1.37, 3.86, 3.98,   0.06,   0.00,   0.01,  62.14,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.01, 7,    main,   -2.94,  84420.00, 1513.12,  183.31,   -7.12, 32.0, 1.37, 3.86, 3.98,   0.00,   0.00,   0.01,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.11, 7,    main,   -1.47,  84437.00, 1511.48,  181.67,   -7.12, 32.0, 1.37, 3.86, 3.98,   0.00,   0.00,   0.01,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.21, 7,    main,   -3.43,  84440.00, 1511.19,  181.38,   -7.12, 32.0, 1.37, 3.86, 3.98,   0.00,   0.00,   0.01,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.01, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.26, 7,    main,   -3.43,  84440.00, 1511.19,  181.38,   -7.12, 32.0, 1.36, 3.86, 3.99,   0.00,   0.00,   0.01,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.30, 7,    main,   -3.43,  84440.00, 1511.19,  181.38,   -7.12, 32.0, 1.36, 3.86, 3.99,   0.00,   0.00,   0.01,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.30, 7,    main,   -3.43,  84440.00, 1511.19,  181.38,   -7.12, 32.0, 1.36, 3.86, 3.99,   0.00,   0.00,   0.01,  62.20,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9488772,-106.9153972,  1592.0, 2022,  6, 24, 15, 20, 30,     1105,     1123, 340,  10,   1.6,   0.8,   1.4,  0, 33, 34,  0,  0, 38,  0,  0,  0,  0, 33, 30, 23, 22,  0,  0, 22,  0, 35, 28,  0,  0,  0, 27,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   194.31, 7,    main,   -5.39,  84452.00, 1510.03,  180.23,   -7.10, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.41, 7,    main,   -0.00,  84466.00, 1508.68,  178.88,   -7.07, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.51, 7,    main,   -0.49,  84480.00, 1507.33,  177.53,   -7.03, 32.0, 1.36, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.58, 7,    main,   -0.49,  84480.00, 1507.33,  177.53,   -7.03, 32.0, 1.37, 3.87, 3.98,   0.09,   0.00,   0.00,  62.20,  21.85,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.61, 7,    main,    0.98,  84486.00, 1506.75,  176.95,   -6.98, 32.0, 1.37, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.71, 7,    main,   -2.94,  84480.00, 1507.33,  177.53,   -6.93, 32.0, 1.37, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.81, 7,    main,    1.47,  84492.00, 1506.17,  176.37,   -6.87, 32.0, 1.37, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.90, 7,    main,    1.47,  84492.00, 1506.17,  176.37,   -6.87, 32.0, 1.37, 3.85, 3.97,   0.08,   0.00,   0.00,  62.32,  22.03,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   194.91, 7,    main,   -2.45,  84495.00, 1505.88,  176.08,   -6.80, 32.0, 1.37, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.01, 7,    main,   -2.45,  84503.00, 1505.11,  175.31,   -6.73, 32.0, 1.37, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.11, 7,    main,   -2.45,  84514.00, 1504.05,  174.25,   -6.67, 32.0, 1.37, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.21, 7,    main,   -1.96,  84523.00, 1503.18,  173.38,   -6.61, 32.0, 1.37, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.22, 7,    main,   -1.96,  84523.00, 1503.18,  173.38,   -6.61, 32.0, 1.38, 3.84, 3.96,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.30, 7,    main,   -1.96,  84523.00, 1503.18,  173.38,   -6.61, 32.0, 1.38, 3.84, 3.96,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.30, 7,    main,   -1.96,  84523.00, 1503.18,  173.38,   -6.61, 32.0, 1.38, 3.84, 3.96,   0.00,   0.00,   0.00,  62.07,  22.10,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9488888,-106.9154659,  1585.0, 2022,  6, 24, 15, 20, 31,     1109,     1125, 340,  10,   1.9,   1.0,   1.6,  0, 35, 34,  0,  0, 38,  0,  0,  0,  0, 34, 30, 25, 31,  0,  0, 23,  0, 36, 33,  0,  0,  0, 27,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.31, 7,    main,   -1.47,  84531.00, 1502.41,  172.61,   -6.55, 32.0, 1.38, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.41, 7,    main,   -2.94,  84527.00, 1502.80,  172.99,   -6.50, 32.0, 1.38, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.51, 7,    main,   -0.98,  84541.00, 1501.45,  171.64,   -6.44, 32.0, 1.38, 3.84, 3.96,   0.00,   0.00,   0.00,  61.89,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.54, 7,    main,   -0.98,  84541.00, 1501.45,  171.64,   -6.44, 32.0, 1.39, 3.87, 3.99,   0.00,   0.00,   0.00,  61.89,  22.16,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.61, 7,    main,   -2.45,  84542.00, 1501.35,  171.55,   -6.41, 32.0, 1.39, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.71, 7,    main,   -1.96,  84566.00, 1499.04,  169.24,   -6.37, 32.0, 1.39, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.81, 7,    main,   -2.94,  84557.00, 1499.90,  170.10,   -6.34, 32.0, 1.39, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.86, 7,    main,   -2.94,  84557.00, 1499.90,  170.10,   -6.34, 32.0, 1.39, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   195.91, 7,    main,    1.47,  84568.00, 1498.84,  169.04,   -6.32, 32.0, 1.39, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.01, 7,    main,   -0.49,  84568.00, 1498.84,  169.04,   -6.31, 32.0, 1.39, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.11, 7,    main,   -3.43,  84577.00, 1497.98,  168.18,   -6.31, 32.0, 1.39, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.18, 7,    main,   -3.43,  84577.00, 1497.98,  168.18,   -6.31, 32.0, 1.40, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  22.40,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.21, 7,    main,   -2.94,  84580.00, 1497.69,  167.89,   -6.31, 32.0, 1.40, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.30, 7,    main,   -2.94,  84580.00, 1497.69,  167.89,   -6.31, 32.0, 1.40, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.30, 7,    main,   -2.94,  84580.00, 1497.69,  167.89,   -6.31, 32.0, 1.40, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9489200,-106.9155154,  1578.0, 2022,  6, 24, 15, 20, 32,     1114,     1129, 340,   9,   1.6,   0.8,   1.4,  0, 32, 29,  0,  0, 34,  0,  0,  0,  0, 34, 34, 31, 32,  0,  0, 30,  0, 34, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 28,  0,  0
+6, 6583, 3,VE3LIC,   196.31, 7,    main,   -0.00,  84588.00, 1496.92,  167.12,   -6.32, 32.0, 1.40, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.41, 7,    main,   -3.92,  84592.00, 1496.53,  166.73,   -6.33, 32.0, 1.40, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.50, 7,    main,   -3.92,  84592.00, 1496.53,  166.73,   -6.33, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.51, 7,    main,   -1.47,  84600.00, 1495.76,  165.96,   -6.35, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.61, 7,    main,   -0.98,  84605.00, 1495.28,  165.48,   -6.35, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.71, 7,    main,    0.49,  84620.00, 1493.83,  164.03,   -6.36, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.81, 7,    main,   -1.96,  84620.00, 1493.83,  164.03,   -6.37, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.82, 7,    main,   -1.96,  84620.00, 1493.83,  164.03,   -6.37, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   196.91, 7,    main,   -0.00,  84628.00, 1493.06,  163.26,   -6.38, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.01, 7,    main,   -0.49,  84638.00, 1492.10,  162.30,   -6.37, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.11, 7,    main,    2.45,  84647.00, 1491.23,  161.43,   -6.37, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.14, 7,    main,    2.45,  84647.00, 1491.23,  161.43,   -6.37, 32.0, 1.41, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.21, 7,    main,   -0.98,  84661.00, 1489.89,  160.08,   -6.37, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.30, 7,    main,   -0.98,  84661.00, 1489.89,  160.08,   -6.37, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.30, 7,    main,   -0.98,  84661.00, 1489.89,  160.08,   -6.37, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9489611,-106.9155462,  1570.0, 2022,  6, 24, 15, 20, 33,     1119,     1133, 340,   9,   2.1,   0.9,   1.9,  0, 37, 29,  0,  0, 29,  0,  0,  0,  0, 37, 35, 25, 25,  0,  0, 20,  0, 36, 27,  0,  0,  0, 33,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.31, 7,    main,    1.96,  84658.00, 1490.17,  160.37,   -6.35, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.41, 7,    main,   -0.49,  84671.00, 1488.92,  159.12,   -6.33, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.46, 7,    main,   -0.49,  84671.00, 1488.92,  159.12,   -6.33, 32.0, 1.42, 3.87, 3.98,   0.00,   0.00,   0.00,  62.14,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.51, 7,    main,   -0.00,  84663.00, 1489.69,  159.89,   -6.30, 32.0, 1.42, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.61, 7,    main,   -4.41,  84685.00, 1487.58,  157.77,   -6.26, 32.0, 1.42, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.71, 7,    main,   -4.90,  84672.00, 1488.83,  159.03,   -6.22, 32.0, 1.42, 3.87, 3.98,   0.00,   0.00,   0.00,  62.32,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.78, 7,    main,   -4.90,  84672.00, 1488.83,  159.03,   -6.22, 32.0, 1.41, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.81, 7,    main,   -2.94,  84694.00, 1486.71,  156.91,   -6.17, 32.0, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   197.91, 7,    main,   -5.39,  84694.00, 1486.71,  156.91,   -6.12, 32.0, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.01, 7,    main,   -3.92,  84699.00, 1486.23,  156.43,   -6.06, 32.0, 1.41, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.10, 7,    main,   -3.92,  84699.00, 1486.23,  156.43,   -6.06, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.11, 7,    main,   -5.88,  84713.00, 1484.88,  155.08,   -5.99, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.21, 7,    main,   -0.49,  84716.00, 1484.59,  154.79,   -5.93, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.30, 7,    main,   -0.49,  84716.00, 1484.59,  154.79,   -5.93, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.30, 7,    main,   -0.49,  84716.00, 1484.59,  154.79,   -5.93, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9490012,-106.9155554,  1564.0, 2022,  6, 24, 15, 20, 34,     1123,     1136, 340,   9,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 34,  0,  0,  0,  0, 34, 26, 27, 30,  0,  0, 29,  0, 36, 27,  0,  0,  0, 30,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   198.31, 7,    main,   -3.43,  84723.00, 1483.92,  154.12,   -5.87, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.41, 7,    main,   -0.49,  84722.00, 1484.01,  154.21,   -5.81, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.42, 7,    main,   -0.49,  84722.00, 1484.01,  154.21,   -5.81, 32.0, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.20,  22.77,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.51, 7,    main,   -1.96,  84739.00, 1482.38,  152.58,   -5.75, 32.0, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.61, 7,    main,   -1.47,  84734.00, 1482.86,  153.06,   -5.70, 32.0, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.71, 7,    main,   -2.94,  84760.00, 1480.36,  150.56,   -5.66, 32.0, 1.41, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.74, 7,    main,   -2.94,  84760.00, 1480.36,  150.56,   -5.66, 32.0, 1.41, 3.85, 3.97,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.81, 7,    main,   -4.90,  84749.00, 1481.42,  151.62,   -5.62, 32.0, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   198.91, 7,    main,   -6.37,  84774.00, 1479.01,  149.21,   -5.58, 32.0, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.01, 7,    main,   -4.90,  84755.00, 1480.84,  151.04,   -5.55, 32.0, 1.41, 3.85, 3.97,   0.00,   0.00,   0.00,  62.01,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.06, 7,    main,   -4.90,  84755.00, 1480.84,  151.04,   -5.55, 32.0, 1.42, 3.85, 3.99,   0.00,   0.00,   0.00,  62.01,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.11, 7,    main,   -4.90,  84782.00, 1478.24,  148.44,   -5.53, 32.0, 1.42, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.21, 7,    main,   -7.35,  84770.00, 1479.40,  149.60,   -5.54, 32.0, 1.42, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.30, 7,    main,   -7.35,  84770.00, 1479.40,  149.60,   -5.54, 32.0, 1.42, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.30, 7,    main,   -7.35,  84770.00, 1479.40,  149.60,   -5.54, 32.0, 1.42, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490476,-106.9155453,  1557.0, 2022,  6, 24, 15, 20, 35,     1128,     1140, 340,   8,   1.7,   0.8,   1.4,  0, 29, 35,  0,  0, 31,  0,  0,  0,  0, 31, 36, 32, 24,  0,  0, 38,  0, 37, 32,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   199.31, 7,    main,   -3.43,  84780.00, 1478.44,  148.63,   -5.53, 32.0, 1.42, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.38, 7,    main,   -3.43,  84780.00, 1478.44,  148.63,   -5.53, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.07,  22.83,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.41, 7,    main,   -0.98,  84785.00, 1477.95,  148.15,   -5.55, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.51, 7,    main,   -4.90,  84785.00, 1477.95,  148.15,   -5.56, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.61, 7,    main,   -0.98,  84788.00, 1477.67,  147.86,   -5.58, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.70, 7,    main,   -0.98,  84788.00, 1477.67,  147.86,   -5.58, 32.0, 1.40, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.71, 7,    main,   -0.98,  84789.00, 1477.57,  147.77,   -5.61, 32.0, 1.40, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.81, 7,    main,   -3.43,  84807.00, 1475.84,  146.04,   -5.65, 32.0, 1.40, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   199.91, 7,    main,    0.98,  84822.00, 1474.40,  144.60,   -5.69, 32.0, 1.40, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.01, 7,    main,   -5.88,  84817.00, 1474.88,  145.08,   -5.72, 32.0, 1.40, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.02, 7,    main,   -5.88,  84817.00, 1474.88,  145.08,   -5.72, 32.0, 1.39, 3.85, 3.96,   0.00,   0.00,   0.00,  62.20,  22.52,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.11, 7,    main,   -7.35,  84815.00, 1475.07,  145.27,   -5.77, 32.0, 1.39, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.21, 7,    main,   -5.88,  84848.00, 1471.90,  142.10,   -5.81, 32.0, 1.39, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.30, 7,    main,   -5.88,  84848.00, 1471.90,  142.10,   -5.81, 32.0, 1.39, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.30, 7,    main,   -5.88,  84848.00, 1471.90,  142.10,   -5.81, 32.0, 1.39, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9490943,-106.9155342,  1550.0, 2022,  6, 24, 15, 20, 36,     1132,     1143, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 23,  0,  0,  0,  0, 30, 36, 28, 32,  0,  0, 38,  0, 37, 35,  0,  0,  0, 29,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   200.31, 7,    main,   -7.85,  84833.00, 1473.34,  143.54,   -5.84, 32.0, 1.39, 3.85, 3.96,   0.00,   0.00,   0.00,  61.95,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 3.97, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.34, 7,    main,   -7.85,  84833.00, 1473.34,  143.54,   -5.84, 32.0, 1.39, 3.86, 3.99,   0.00,   0.00,   0.00,  61.95,  22.34,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.41, 7,    main,   -3.43,  84843.00, 1472.38,  142.58,   -5.86, 32.0, 1.39, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.51, 7,    main,  -10.30,  84849.00, 1471.80,  142.00,   -5.89, 32.0, 1.39, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.61, 7,    main,   -6.86,  84863.00, 1470.46,  140.66,   -5.90, 32.0, 1.39, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.66, 7,    main,   -6.86,  84863.00, 1470.46,  140.66,   -5.90, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  22.46,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.21, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.71, 7,    main,   -5.39,  84864.00, 1470.36,  140.56,   -5.92, 32.0, 1.41, 3.86, 3.99,   0.26,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.21, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.81, 7,    main,   -4.90,  84864.00, 1470.36,  140.56,   -5.93, 32.0, 1.41, 3.86, 3.99,   0.26,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.21, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.91, 7,    main,   -0.98,  84875.00, 1469.30,  139.50,   -5.93, 32.0, 1.41, 3.86, 3.99,   0.26,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.21, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   200.98, 7,    main,   -0.98,  84875.00, 1469.30,  139.50,   -5.93, 32.0, 1.41, 3.86, 3.98,   0.26,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   201.01, 7,    main,    0.49,  84875.00, 1469.30,  139.50,   -5.93, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   201.11, 7,    main,   -1.96,  84885.00, 1468.34,  138.54,   -5.92, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   201.21, 7,    main,   -1.96,  84910.00, 1465.94,  136.14,   -5.91, 32.0, 1.41, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9491398,-106.9155258,  1545.0, 2022,  6, 24, 15, 20, 37,     1137,     1147, 340,   8,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 35, 31, 27,  0,  0, 30,  0, 24, 32,  0,  0,  0, 35,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   201.30, 7,    main,   -1.96,  84910.00, 1465.94,  136.14,   -5.91, 32.0, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.30, 7,    main,   -1.96,  84910.00, 1465.94,  136.14,   -5.91, 32.0, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.30, 7,    main,   -1.96,  84910.00, 1465.94,  136.14,   -5.91, 32.0, 1.41, 3.87, 3.98,   0.00,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.31, 7,    main,    1.96,  84894.00, 1467.48,  137.68,   -5.89, 32.0, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.41, 7,    main,    0.98,  84913.00, 1465.65,  135.85,   -5.89, 32.0, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.51, 7,    main,    2.45,  84907.00, 1466.23,  136.43,   -5.87, 32.0, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.61, 7,    main,    1.96,  84921.00, 1464.88,  135.08,   -5.86, 32.0, 1.41, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.62, 7,    main,    1.96,  84921.00, 1464.88,  135.08,   -5.86, 32.0, 1.41, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.71, 7,    main,   -0.00,  84926.00, 1464.40,  134.60,   -5.85, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.81, 7,    main,   -4.90,  84935.00, 1463.54,  133.74,   -5.84, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.91, 7,    main,   -1.96,  84935.00, 1463.54,  133.74,   -5.83, 32.0, 1.41, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   201.94, 7,    main,   -1.96,  84935.00, 1463.54,  133.74,   -5.83, 32.0, 1.41, 3.86, 4.00,   0.08,   0.00,   0.00,  62.20,  22.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.01, 7,    main,   -7.35,  84937.00, 1463.35,  133.55,   -5.83, 32.0, 1.41, 3.86, 4.00,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.11, 7,    main,   -4.90,  84953.00, 1461.81,  132.01,   -5.82, 32.0, 1.41, 3.86, 4.00,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.21, 7,    main,   -7.35,  84951.00, 1462.00,  132.20,   -5.83, 32.0, 1.41, 3.86, 4.00,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.26, 7,    main,   -7.35,  84951.00, 1462.00,  132.20,   -5.83, 32.0, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.30, 7,    main,   -7.35,  84951.00, 1462.00,  132.20,   -5.83, 32.0, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.30, 7,    main,   -7.35,  84951.00, 1462.00,  132.20,   -5.83, 32.0, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.20,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9491776,-106.9155120,  1538.0, 2022,  6, 24, 15, 20, 38,     1140,     1149, 340,   7,   1.7,   0.8,   1.4,  0, 35, 31,  0,  0, 37,  0,  0,  0,  0, 34, 31, 31, 32,  0,  0, 24,  0, 30, 30,  0,  0,  0, 28,  0,  0,  0,  0,  0, 25,  0,  0
+6, 6583, 3,VE3LIC,   202.31, 7,    main,   -2.94,  84957.00, 1461.43,  131.63,   -5.82, 32.0, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.41, 7,    main,   -2.45,  84958.00, 1461.33,  131.53,   -5.82, 32.0, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.51, 7,    main,   -3.43,  84987.00, 1458.55,  128.75,   -5.81, 32.0, 1.41, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.58, 7,    main,   -3.43,  84987.00, 1458.55,  128.75,   -5.81, 32.0, 1.42, 3.86, 3.99,   0.09,   0.00,   0.00,  62.07,  22.71,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.61, 7,    main,   -0.00,  84967.00, 1460.47,  130.67,   -5.81, 32.0, 1.42, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.71, 7,    main,   -1.47,  84987.00, 1458.55,  128.75,   -5.81, 32.0, 1.42, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.81, 7,    main,   -0.49,  84998.00, 1457.49,  127.69,   -5.81, 32.0, 1.42, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.90, 7,    main,   -0.49,  84998.00, 1457.49,  127.69,   -5.81, 32.0, 1.43, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.89,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   202.91, 7,    main,    0.49,  84998.00, 1457.49,  127.69,   -5.81, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.01, 7,    main,   -0.00,  85010.00, 1456.34,  126.54,   -5.81, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.11, 7,    main,    0.98,  85002.00, 1457.11,  127.31,   -5.82, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.21, 7,    main,   -4.90,  85015.00, 1455.86,  126.06,   -5.83, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.22, 7,    main,   -4.90,  85015.00, 1455.86,  126.06,   -5.83, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.30, 7,    main,   -4.90,  85015.00, 1455.86,  126.06,   -5.83, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.30, 7,    main,   -4.90,  85015.00, 1455.86,  126.06,   -5.83, 32.0, 1.43, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  23.01,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492115,-106.9155088,  1531.0, 2022,  6, 24, 15, 20, 39,     1144,     1152, 341,   7,   1.6,   0.8,   1.4,  0, 26, 32,  0,  0, 22,  0,  0,  0,  0, 25, 32, 30, 26,  0,  0, 35,  0, 37, 31,  0,  0,  0, 19,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   203.31, 7,    main,   -2.94,  85024.00, 1455.00,  125.20,   -5.84, 32.0, 1.43, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.41, 7,    main,   -2.45,  85037.00, 1453.75,  123.95,   -5.85, 32.0, 1.43, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.51, 7,    main,   -4.41,  85024.00, 1455.00,  125.20,   -5.85, 32.0, 1.43, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.54, 7,    main,   -4.41,  85024.00, 1455.00,  125.20,   -5.85, 32.0, 1.44, 3.87, 3.99,   0.09,   0.00,   0.00,  62.14,  22.95,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.61, 7,    main,   -4.90,  85042.00, 1453.27,  123.47,   -5.85, 32.0, 1.44, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.71, 7,    main,   -1.96,  85045.00, 1452.98,  123.18,   -5.85, 32.0, 1.44, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.81, 7,    main,   -4.41,  85046.00, 1452.89,  123.09,   -5.86, 32.0, 1.44, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.86, 7,    main,   -4.41,  85046.00, 1452.89,  123.09,   -5.86, 32.0, 1.44, 3.85, 3.98,   0.08,   0.00,   0.00,  62.26,  23.19,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   203.91, 7,    main,   -7.85,  85051.00, 1452.41,  122.61,   -5.85, 32.0, 1.44, 3.85, 3.98,   0.09,   0.00,   0.00,  62.07,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.01, 7,    main,   -6.37,  85072.00, 1450.39,  120.59,   -5.85, 32.0, 1.44, 3.85, 3.98,   0.09,   0.00,   0.00,  62.07,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.11, 7,    main,   -5.39,  85065.00, 1451.06,  121.26,   -5.85, 32.0, 1.44, 3.85, 3.98,   0.09,   0.00,   0.00,  62.07,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.18, 7,    main,   -5.39,  85065.00, 1451.06,  121.26,   -5.85, 32.0, 1.44, 3.87, 3.98,   0.09,   0.00,   0.00,  62.07,  23.13,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.21, 7,    main,   -1.47,  85081.00, 1449.53,  119.73,   -5.84, 32.0, 1.44, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.30, 7,    main,   -1.47,  85081.00, 1449.53,  119.73,   -5.84, 32.0, 1.44, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.30, 7,    main,   -1.47,  85081.00, 1449.53,  119.73,   -5.84, 32.0, 1.44, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9492543,-106.9155270,  1526.0, 2022,  6, 24, 15, 20, 40,     1149,     1156, 341,   7,   1.6,   0.8,   1.4,  0, 32, 37,  0,  0, 31,  0,  0,  0,  0, 34, 36, 34, 26,  0,  0, 31,  0, 25, 25,  0,  0,  0, 36,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   204.31, 7,    main,   -4.90,  85078.00, 1449.82,  120.02,   -5.83, 32.0, 1.44, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.41, 7,    main,   -0.49,  85088.00, 1448.86,  119.06,   -5.81, 32.0, 1.44, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.50, 7,    main,   -0.49,  85088.00, 1448.86,  119.06,   -5.81, 32.0, 1.44, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.51, 7,    main,   -0.49,  85095.00, 1448.19,  118.39,   -5.81, 32.0, 1.44, 3.87, 3.98,   0.00,   0.00,   0.00,  62.26,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.61, 7,    main,   -1.47,  85093.00, 1448.38,  118.58,   -5.78, 32.0, 1.44, 3.87, 3.98,   0.00,   0.00,   0.00,  62.26,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.71, 7,    main,   -3.92,  85121.00, 1445.69,  115.89,   -5.76, 32.0, 1.44, 3.87, 3.98,   0.00,   0.00,   0.00,  62.26,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.81, 7,    main,   -2.45,  85113.00, 1446.46,  116.66,   -5.74, 32.0, 1.44, 3.87, 3.98,   0.00,   0.00,   0.00,  62.26,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.82, 7,    main,   -2.45,  85113.00, 1446.46,  116.66,   -5.74, 32.0, 1.44, 3.86, 3.98,   0.00,   0.00,   0.00,  62.26,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   204.91, 7,    main,   -5.88,  85122.00, 1445.60,  115.80,   -5.71, 32.0, 1.44, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.01, 7,    main,    0.49,  85120.00, 1445.79,  115.99,   -5.69, 32.0, 1.44, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.11, 7,    main,   -0.49,  85143.00, 1443.59,  113.79,   -5.65, 32.0, 1.44, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.14, 7,    main,   -0.49,  85143.00, 1443.59,  113.79,   -5.65, 32.0, 1.44, 3.85, 3.97,   0.00,   0.00,   0.00,  62.14,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.21, 7,    main,   -1.96,  85135.00, 1444.35,  114.55,   -5.61, 32.0, 1.44, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.30, 7,    main,   -1.96,  85135.00, 1444.35,  114.55,   -5.61, 32.0, 1.44, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.30, 7,    main,   -1.96,  85135.00, 1444.35,  114.55,   -5.61, 32.0, 1.44, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493026,-106.9155299,  1519.0, 2022,  6, 24, 15, 20, 41,     1154,     1161, 341,   6,   1.6,   0.8,   1.4,  0, 37, 26,  0,  0, 38,  0,  0,  0,  0, 33, 28, 33, 35,  0,  0, 25,  0, 32, 27,  0,  0,  0, 22,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.31, 7,    main,   -0.98,  85147.00, 1443.20,  113.40,   -5.58, 32.0, 1.44, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.41, 7,    main,   -3.92,  85146.00, 1443.30,  113.50,   -5.56, 32.0, 1.44, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.46, 7,    main,   -3.92,  85146.00, 1443.30,  113.50,   -5.56, 32.0, 1.46, 3.87, 3.98,   0.00,   0.00,   0.00,  62.07,  23.26,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.51, 7,    main,   -2.45,  85152.00, 1442.72,  112.92,   -5.52, 32.0, 1.46, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.61, 7,    main,   -3.43,  85151.00, 1442.82,  113.02,   -5.49, 32.0, 1.46, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.71, 7,    main,   -2.45,  85166.00, 1441.38,  111.58,   -5.47, 32.0, 1.46, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.78, 7,    main,   -2.45,  85166.00, 1441.38,  111.58,   -5.47, 32.0, 1.46, 3.85, 3.98,   0.09,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.81, 7,    main,   -5.39,  85175.00, 1440.52,  110.72,   -5.43, 32.0, 1.46, 3.85, 3.98,   0.00,   0.00,   0.00,  62.01,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   205.91, 7,    main,   -4.41,  85178.00, 1440.23,  110.43,   -5.41, 32.0, 1.46, 3.85, 3.98,   0.00,   0.00,   0.00,  62.01,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.01, 7,    main,   -0.98,  85183.00, 1439.75,  109.95,   -5.40, 32.0, 1.46, 3.85, 3.98,   0.00,   0.00,   0.00,  62.01,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.10, 7,    main,   -0.98,  85183.00, 1439.75,  109.95,   -5.40, 32.0, 1.46, 3.87, 3.99,   0.00,   0.00,   0.00,  62.01,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.11, 7,    main,   -1.96,  85192.00, 1438.89,  109.09,   -5.39, 32.0, 1.46, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.21, 7,    main,   -1.96,  85194.00, 1438.70,  108.90,   -5.39, 32.0, 1.46, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.30, 7,    main,   -1.96,  85194.00, 1438.70,  108.90,   -5.39, 32.0, 1.46, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.30, 7,    main,   -1.96,  85194.00, 1438.70,  108.90,   -5.39, 32.0, 1.46, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493529,-106.9155336,  1513.0, 2022,  6, 24, 15, 20, 42,     1159,     1166, 341,   6,   1.6,   0.8,   1.4,  0, 31, 29,  0,  0, 36,  0,  0,  0,  0, 33, 34, 30, 27,  0,  0, 26,  0, 27, 27,  0,  0,  0, 34,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   206.31, 7,    main,   -5.39,  85194.00, 1438.70,  108.90,   -5.38, 32.0, 1.46, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.41, 7,    main,   -2.94,  85206.00, 1437.55,  107.75,   -5.39, 31.9, 1.46, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.42, 7,    main,   -2.94,  85206.00, 1437.55,  107.75,   -5.39, 31.9, 1.47, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  23.44,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.51, 7,    main,   -3.92,  85216.00, 1436.59,  106.79,   -5.40, 32.0, 1.47, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.61, 7,    main,   -2.94,  85218.00, 1436.40,  106.60,   -5.42, 32.0, 1.47, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.71, 7,    main,   -1.47,  85216.00, 1436.59,  106.79,   -5.45, 32.0, 1.47, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.74, 7,    main,   -1.47,  85216.00, 1436.59,  106.79,   -5.45, 32.0, 1.49, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  23.74,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.81, 7,    main,   -2.94,  85230.00, 1435.25,  105.45,   -5.46, 32.0, 1.49, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   206.91, 7,    main,   -1.47,  85233.00, 1434.96,  105.16,   -5.49, 32.0, 1.49, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.01, 7,    main,   -0.00,  85238.00, 1434.49,  104.68,   -5.52, 32.0, 1.49, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.06, 7,    main,   -0.00,  85238.00, 1434.49,  104.68,   -5.52, 32.0, 1.50, 3.87, 3.99,   0.00,   0.00,   0.00,  62.14,  23.93,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.11, 7,    main,   -2.45,  85241.00, 1434.20,  104.40,   -5.55, 32.0, 1.50, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.21, 7,    main,   -5.88,  85249.00, 1433.43,  103.63,   -5.58, 32.0, 1.50, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.30, 7,    main,   -5.88,  85249.00, 1433.43,  103.63,   -5.58, 32.0, 1.50, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.30, 7,    main,   -5.88,  85249.00, 1433.43,  103.63,   -5.58, 32.0, 1.50, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494071,-106.9155344,  1508.0, 2022,  6, 24, 15, 20, 43,     1165,     1171, 341,   6,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 32,  0,  0,  0,  0, 22, 35, 31, 25,  0,  0, 37,  0, 37, 29,  0,  0,  0, 27,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   207.31, 7,    main,   -3.43,  85254.00, 1432.95,  103.15,   -5.61, 31.9, 1.50, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.38, 7,    main,   -3.43,  85254.00, 1432.95,  103.15,   -5.61, 31.9, 1.50, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.41, 7,    main,   -2.94,  85268.00, 1431.61,  101.81,   -5.64, 32.0, 1.50, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.51, 7,    main,   -0.98,  85262.00, 1432.19,  102.39,   -5.67, 32.0, 1.50, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.61, 7,    main,   -4.41,  85262.00, 1432.19,  102.39,   -5.69, 31.9, 1.50, 3.86, 3.99,   0.08,   0.00,   0.00,  62.14,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.70, 7,    main,   -4.41,  85262.00, 1432.19,  102.39,   -5.69, 31.9, 1.50, 3.87, 3.98,   0.08,   0.00,   0.00,  62.14,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.71, 7,    main,   -1.96,  85287.00, 1429.79,   99.99,   -5.72, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.81, 7,    main,   -1.96,  85274.00, 1431.04,  101.24,   -5.74, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   207.91, 7,    main,   -1.96,  85290.00, 1429.51,   99.71,   -5.76, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.01, 7,    main,   -1.47,  85304.00, 1428.17,   98.37,   -5.78, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.00,  62.32,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.02, 7,    main,   -1.47,  85304.00, 1428.17,   98.37,   -5.78, 32.0, 1.50, 3.86, 3.98,   0.08,   0.00,   0.00,  62.32,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.11, 7,    main,   -1.96,  85308.00, 1427.79,   97.98,   -5.79, 32.0, 1.50, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.21, 7,    main,   -4.41,  85310.00, 1427.59,   97.79,   -5.81, 31.9, 1.50, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.30, 7,    main,   -4.41,  85310.00, 1427.59,   97.79,   -5.81, 31.9, 1.50, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.30, 7,    main,   -4.41,  85310.00, 1427.59,   97.79,   -5.81, 31.9, 1.50, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1,  9,  32.9494496,-106.9155220,  1502.0, 2022,  6, 24, 15, 20, 44,     1169,     1174, 341,   5,   1.7,   0.8,   1.4,  0, 34, 36,  0,  0, 38,  0,  0,  0,  0, 33, 32, 34, 25,  0,  0, 24,  0, 35, 29,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   208.31, 7,    main,   -3.43,  85318.00, 1426.83,   97.03,   -5.82, 32.0, 1.50, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.01, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.34, 7,    main,   -3.43,  85318.00, 1426.83,   97.03,   -5.82, 32.0, 1.50, 3.86, 3.98,   0.01,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.41, 7,    main,   -5.88,  85321.00, 1426.54,   96.74,   -5.85, 32.0, 1.50, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.51, 7,    main,   -1.47,  85339.00, 1424.82,   95.02,   -5.87, 32.0, 1.50, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.61, 7,    main,   -4.41,  85335.00, 1425.20,   95.40,   -5.89, 32.0, 1.50, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.66, 7,    main,   -4.41,  85335.00, 1425.20,   95.40,   -5.89, 32.0, 1.50, 3.87, 3.98,   0.09,   0.00,   0.00,  62.20,  24.11,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.01, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.71, 7,    main,   -5.88,  85342.00, 1424.53,   94.73,   -5.92, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.01,  62.32,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.01, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.81, 7,    main,   -4.41,  85339.00, 1424.82,   95.02,   -5.95, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.01,  62.32,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.01, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.91, 7,    main,   -3.43,  85349.00, 1423.86,   94.06,   -5.98, 32.0, 1.50, 3.87, 3.98,   0.08,   0.00,   0.01,  62.32,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.01, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   208.98, 7,    main,   -3.43,  85349.00, 1423.86,   94.06,   -5.98, 32.0, 1.51, 3.86, 3.98,   0.08,   0.00,   0.01,  62.32,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   209.01, 7,    main,   -5.39,  85363.00, 1422.52,   92.72,   -6.00, 32.0, 1.51, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   209.11, 7,    main,   -3.43,  85359.00, 1422.91,   93.11,   -6.03, 32.0, 1.51, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   209.21, 7,    main,   -2.45,  85370.00, 1421.85,   92.05,   -6.06, 32.0, 1.51, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   209.28, 7,    main,   -2.45,  85370.00, 1421.85,   92.05,   -6.06, 32.0, 1.51, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   209.28, 7,    main,   -2.45,  85370.00, 1421.85,   92.05,   -6.06, 32.0, 1.51, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494784,-106.9154916,  1497.0, 2022,  6, 24, 15, 20, 45,     1171,     1176, 341,   5,   1.7,   0.8,   1.4,  0, 26, 34,  0,  0, 37,  0,  0,  0,  0, 23, 35, 30, 25,  0,  0, 36,  0, 35, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   209.30, 7,    main,   -2.45,  85370.00, 1421.85,   92.05,   -6.06, 32.0, 1.51, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  24.35,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.31, 7,    main,   -0.49,  85374.00, 1421.47,   91.67,   -6.08, 32.0, 1.51, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.41, 7,    main,   -1.96,  85387.00, 1420.23,   90.43,   -6.11, 32.0, 1.51, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.51, 7,    main,   -4.41,  85392.00, 1419.75,   89.95,   -6.13, 32.0, 1.51, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.61, 7,    main,   -4.41,  85393.00, 1419.66,   89.85,   -6.14, 31.9, 1.51, 3.87, 3.99,   0.08,   0.00,   0.00,  62.26,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.62, 7,    main,   -4.41,  85393.00, 1419.66,   89.85,   -6.14, 31.9, 1.50, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  24.29,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.71, 7,    main,   -3.92,  85400.00, 1418.99,   89.19,   -6.17, 31.9, 1.50, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.81, 7,    main,   -0.98,  85402.00, 1418.79,   88.99,   -6.18, 31.9, 1.50, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.91, 7,    main,   -1.47,  85409.00, 1418.13,   88.32,   -6.19, 32.0, 1.50, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   209.94, 7,    main,   -1.47,  85409.00, 1418.13,   88.32,   -6.19, 32.0, 1.50, 3.85, 3.98,   0.09,   0.00,   0.00,  62.20,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.01, 7,    main,   -4.90,  85430.00, 1416.12,   86.32,   -6.21, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.11, 7,    main,   -3.92,  85425.00, 1416.60,   86.80,   -6.21, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.21, 7,    main,   -4.90,  85440.00, 1415.16,   85.36,   -6.22, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.26, 7,    main,   -4.90,  85440.00, 1415.16,   85.36,   -6.22, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.30, 7,    main,   -4.90,  85440.00, 1415.16,   85.36,   -6.22, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.30, 7,    main,   -4.90,  85440.00, 1415.16,   85.36,   -6.22, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.17,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494929,-106.9154455,  1490.0, 2022,  6, 24, 15, 20, 46,     1171,     1175, 341,   5,   1.7,   0.8,   1.4,  0, 25, 33,  0,  0, 37,  0,  0,  0,  0, 23, 35, 31, 26,  0,  0, 38,  0, 33, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   210.31, 7,    main,   -3.92,  85451.00, 1414.11,   84.31,   -6.22, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.41, 7,    main,   -3.43,  85466.00, 1412.68,   82.88,   -6.22, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.51, 7,    main,   -4.90,  85462.00, 1413.06,   83.26,   -6.24, 32.0, 1.50, 3.85, 3.98,   0.00,   0.00,   0.00,  61.95,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.58, 7,    main,   -4.90,  85462.00, 1413.06,   83.26,   -6.24, 32.0, 1.53, 3.86, 3.98,   0.00,   0.00,   0.00,  61.95,  24.23,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.61, 7,    main,   -6.37,  85458.00, 1413.44,   83.64,   -6.24, 31.9, 1.53, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.71, 7,    main,   -5.88,  85476.00, 1411.72,   81.92,   -6.26, 31.9, 1.53, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.81, 7,    main,   -1.47,  85478.00, 1411.53,   81.73,   -6.26, 32.0, 1.53, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.90, 7,    main,   -1.47,  85478.00, 1411.53,   81.73,   -6.26, 32.0, 1.53, 3.85, 3.98,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   210.91, 7,    main,   -2.94,  85465.00, 1412.77,   82.97,   -6.28, 31.9, 1.53, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.01, 7,    main,    1.47,  85485.00, 1410.86,   81.06,   -6.30, 31.9, 1.53, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.11, 7,    main,    2.94,  85492.00, 1410.19,   80.39,   -6.32, 32.0, 1.53, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.21, 7,    main,   -2.94,  85487.00, 1410.67,   80.87,   -6.34, 31.9, 1.53, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.22, 7,    main,   -2.94,  85487.00, 1410.67,   80.87,   -6.34, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.30, 7,    main,   -2.94,  85487.00, 1410.67,   80.87,   -6.34, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.30, 7,    main,   -2.94,  85487.00, 1410.67,   80.87,   -6.34, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.00,  62.07,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494979,-106.9153939,  1483.0, 2022,  6, 24, 15, 20, 47,     1170,     1174, 342,   4,   1.7,   0.8,   1.4,  0, 30, 32,  0,  0, 37,  0,  0,  0,  0, 30, 37, 31, 28,  0,  0, 33,  0, 34, 30,  0,  0,  0, 35,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   211.31, 7,    main,   -0.00,  85503.00, 1409.14,   79.34,   -6.37, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.41, 7,    main,   -2.45,  85518.00, 1407.71,   77.91,   -6.40, 32.0, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.51, 7,    main,    1.47,  85523.00, 1407.23,   77.43,   -6.43, 32.0, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.54, 7,    main,    1.47,  85523.00, 1407.23,   77.43,   -6.43, 32.0, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.61, 7,    main,    0.49,  85526.00, 1406.95,   77.15,   -6.45, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.71, 7,    main,   -2.45,  85539.00, 1405.71,   75.90,   -6.48, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.81, 7,    main,   -0.49,  85547.00, 1404.94,   75.14,   -6.50, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.86, 7,    main,   -0.49,  85547.00, 1404.94,   75.14,   -6.50, 31.9, 1.54, 3.85, 3.98,   0.00,   0.00,   0.04,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   211.91, 7,    main,   -1.96,  85546.00, 1405.04,   75.24,   -6.53, 32.0, 1.54, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.01, 7,    main,   -0.00,  85556.00, 1404.08,   74.28,   -6.55, 31.9, 1.54, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.11, 7,    main,   -0.00,  85560.00, 1403.70,   73.90,   -6.56, 32.0, 1.54, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.02, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.18, 7,    main,   -0.00,  85560.00, 1403.70,   73.90,   -6.56, 32.0, 1.54, 3.86, 3.99,   0.00,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.21, 7,    main,    0.98,  85572.00, 1402.56,   72.75,   -6.57, 31.9, 1.54, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.30, 7,    main,    0.98,  85572.00, 1402.56,   72.75,   -6.57, 31.9, 1.54, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.30, 7,    main,    0.98,  85572.00, 1402.56,   72.75,   -6.57, 31.9, 1.54, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9494918,-106.9153443,  1475.0, 2022,  6, 24, 15, 20, 48,     1168,     1171, 342,   4,   1.7,   0.8,   1.4,  0, 37, 27,  0,  0, 39,  0,  0,  0,  0, 37, 29, 30, 24,  0,  0, 28,  0, 23, 24,  0,  0,  0, 27,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   212.31, 7,    main,   -0.98,  85578.00, 1401.98,   72.18,   -6.59, 31.9, 1.54, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.41, 7,    main,   -0.98,  85583.00, 1401.51,   71.70,   -6.59, 31.9, 1.54, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.50, 7,    main,   -0.98,  85583.00, 1401.51,   71.70,   -6.59, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.51, 7,    main,   -1.96,  85596.00, 1400.27,   70.46,   -6.58, 31.9, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.61, 7,    main,   -6.86,  85591.00, 1400.74,   70.94,   -6.56, 31.9, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.71, 7,    main,   -6.86,  85611.00, 1398.83,   69.03,   -6.55, 32.0, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.81, 7,    main,   -5.39,  85605.00, 1399.41,   69.61,   -6.54, 31.9, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.82, 7,    main,   -5.39,  85605.00, 1399.41,   69.61,   -6.54, 31.9, 1.52, 3.84, 3.98,   0.08,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   212.91, 7,    main,   -3.92,  85619.00, 1398.07,   68.27,   -6.52, 32.0, 1.52, 3.84, 3.98,   0.00,   0.00,   0.00,  61.83,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.01, 7,    main,   -2.45,  85620.00, 1397.98,   68.17,   -6.51, 32.0, 1.52, 3.84, 3.98,   0.00,   0.00,   0.00,  61.83,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.11, 7,    main,   -1.47,  85628.00, 1397.21,   67.41,   -6.51, 31.9, 1.52, 3.84, 3.98,   0.00,   0.00,   0.00,  61.83,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.14, 7,    main,   -1.47,  85628.00, 1397.21,   67.41,   -6.51, 31.9, 1.53, 3.86, 3.99,   0.00,   0.00,   0.00,  61.83,  24.41,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.21, 7,    main,    1.47,  85629.00, 1397.12,   67.32,   -6.50, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.30, 7,    main,    1.47,  85629.00, 1397.12,   67.32,   -6.50, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.30, 7,    main,    1.47,  85629.00, 1397.12,   67.32,   -6.50, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494694,-106.9152996,  1467.0, 2022,  6, 24, 15, 20, 49,     1165,     1167, 342,   4,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 37,  0,  0,  0,  0, 25, 36, 30, 30,  0,  0, 35,  0, 34, 25,  0,  0,  0, 28,  0,  0,  0,  0,  0, 34,  0,  0
+6, 6583, 3,VE3LIC,   213.31, 7,    main,   -1.47,  85646.00, 1395.49,   65.69,   -6.49, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.41, 7,    main,   -0.00,  85657.00, 1394.45,   64.64,   -6.49, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.46, 7,    main,   -0.00,  85657.00, 1394.45,   64.64,   -6.49, 31.9, 1.53, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.60,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.51, 7,    main,   -0.49,  85663.00, 1393.87,   64.07,   -6.48, 32.0, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.61, 7,    main,   -0.00,  85667.00, 1393.49,   63.69,   -6.47, 31.9, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.71, 7,    main,   -1.96,  85677.00, 1392.54,   62.74,   -6.47, 32.0, 1.53, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.78, 7,    main,   -1.96,  85677.00, 1392.54,   62.74,   -6.47, 32.0, 1.52, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  24.66,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.81, 7,    main,   -0.98,  85688.00, 1391.49,   61.69,   -6.47, 31.9, 1.52, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   213.91, 7,    main,   -1.96,  85687.00, 1391.59,   61.78,   -6.46, 31.9, 1.52, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.01, 7,    main,    1.96,  85685.00, 1391.78,   61.97,   -6.48, 31.9, 1.52, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.10, 7,    main,    1.96,  85685.00, 1391.78,   61.97,   -6.48, 31.9, 1.54, 3.86, 3.99,   0.08,   0.00,   0.00,  62.32,  24.54,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.11, 7,    main,   -1.96,  85696.00, 1390.73,   60.93,   -6.49, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.21, 7,    main,   -1.47,  85699.00, 1390.44,   60.64,   -6.51, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.30, 7,    main,   -1.47,  85699.00, 1390.44,   60.64,   -6.51, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.30, 7,    main,   -1.47,  85699.00, 1390.44,   60.64,   -6.51, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494211,-106.9152883,  1457.0, 2022,  6, 24, 15, 20, 50,     1159,     1161, 342,   3,   1.6,   0.8,   1.4,  0, 24, 29,  0,  0, 39,  0,  0,  0,  0, 24, 29, 30, 26,  0,  0, 35,  0, 25, 33,  0,  0,  0, 26,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.31, 7,    main,   -0.98,  85722.00, 1388.25,   58.45,   -6.54, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.41, 7,    main,   -1.96,  85711.00, 1389.30,   59.50,   -6.57, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.42, 7,    main,   -1.96,  85711.00, 1389.30,   59.50,   -6.57, 31.9, 1.54, 3.85, 3.98,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.51, 7,    main,   -5.39,  85714.00, 1389.01,   59.21,   -6.61, 31.9, 1.54, 3.85, 3.98,   0.09,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.61, 7,    main,   -0.49,  85731.00, 1387.39,   57.59,   -6.65, 31.9, 1.54, 3.85, 3.98,   0.09,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.71, 7,    main,   -1.96,  85746.00, 1385.96,   56.16,   -6.70, 31.9, 1.54, 3.85, 3.98,   0.09,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.74, 7,    main,   -1.96,  85746.00, 1385.96,   56.16,   -6.70, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.07,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.81, 7,    main,   -2.45,  85747.00, 1385.87,   56.07,   -6.75, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   214.91, 7,    main,   -1.47,  85761.00, 1384.53,   54.73,   -6.80, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.01, 7,    main,   -0.98,  85773.00, 1383.39,   53.59,   -6.86, 31.9, 1.54, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.06, 7,    main,   -0.98,  85773.00, 1383.39,   53.59,   -6.86, 31.9, 1.54, 3.85, 3.97,   0.09,   0.00,   0.00,  62.20,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.11, 7,    main,   -0.00,  85774.00, 1383.29,   53.49,   -6.91, 31.9, 1.54, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.21, 7,    main,   -2.45,  85765.00, 1384.15,   54.35,   -6.95, 31.9, 1.54, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.30, 7,    main,   -2.45,  85765.00, 1384.15,   54.35,   -6.95, 31.9, 1.54, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.30, 7,    main,   -2.45,  85765.00, 1384.15,   54.35,   -6.95, 31.9, 1.54, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493701,-106.9153058,  1449.0, 2022,  6, 24, 15, 20, 51,     1154,     1156, 342,   3,   1.6,   0.8,   1.4,  0, 24, 32,  0,  0, 38,  0,  0,  0,  0, 25, 33, 29, 35,  0,  0, 34,  0, 23, 23,  0,  0,  0, 25,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.31, 7,    main,   -3.92,  85768.00, 1383.87,   54.06,   -7.00, 31.9, 1.54, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.38, 7,    main,   -3.92,  85768.00, 1383.87,   54.06,   -7.00, 31.9, 1.57, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  24.72,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.41, 7,    main,    1.47,  85791.00, 1381.67,   51.87,   -7.04, 32.0, 1.57, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.51, 7,    main,   -0.00,  85787.00, 1382.06,   52.25,   -7.08, 31.9, 1.57, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.61, 7,    main,   -0.98,  85795.00, 1381.29,   51.49,   -7.10, 31.9, 1.57, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.70, 7,    main,   -0.98,  85795.00, 1381.29,   51.49,   -7.10, 31.9, 1.59, 3.87, 3.98,   0.00,   0.00,   0.00,  61.95,  25.33,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.71, 7,    main,   -5.88,  85810.00, 1379.86,   50.06,   -7.13, 31.9, 1.59, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  25.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.81, 7,    main,   -3.43,  85821.00, 1378.82,   49.02,   -7.14, 31.9, 1.59, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  25.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   215.91, 7,    main,   -0.00,  85819.00, 1379.01,   49.21,   -7.15, 31.9, 1.59, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  25.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.01, 7,    main,   -0.49,  85854.00, 1375.68,   45.87,   -7.15, 31.9, 1.59, 3.87, 3.98,   0.09,   0.00,   0.00,  62.32,  25.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.02, 7,    main,   -0.49,  85854.00, 1375.68,   45.87,   -7.15, 31.9, 1.59, 3.86, 3.98,   0.09,   0.00,   0.00,  62.32,  25.64,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.11, 7,    main,   -0.00,  85860.00, 1375.10,   45.30,   -7.16, 31.9, 1.59, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.21, 7,    main,   -2.45,  85848.00, 1376.25,   46.45,   -7.15, 31.9, 1.59, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.30, 7,    main,   -2.45,  85848.00, 1376.25,   46.45,   -7.15, 31.9, 1.59, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.30, 7,    main,   -2.45,  85848.00, 1376.25,   46.45,   -7.15, 31.9, 1.59, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493265,-106.9153354,  1442.0, 2022,  6, 24, 15, 20, 52,     1151,     1152, 342,   2,   1.7,   0.9,   1.4,  0, 33, 28,  0,  0, 37,  0,  0,  0,  0, 37, 28, 33, 35,  0,  0, 36,  0, 23, 34,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.31, 7,    main,   -0.49,  85862.00, 1374.91,   45.11,   -7.14, 31.9, 1.59, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.34, 7,    main,   -0.49,  85862.00, 1374.91,   45.11,   -7.14, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  25.57,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.41, 7,    main,    1.47,  85864.00, 1374.72,   44.92,   -7.12, 31.9, 1.60, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.51, 7,    main,    0.98,  85874.00, 1373.77,   43.97,   -7.09, 31.9, 1.60, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.61, 7,    main,   -0.49,  85887.00, 1372.53,   42.73,   -7.07, 31.9, 1.60, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.66, 7,    main,   -0.49,  85887.00, 1372.53,   42.73,   -7.07, 31.9, 1.60, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.71, 7,    main,   -0.49,  85885.00, 1372.72,   42.92,   -7.05, 31.9, 1.60, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.81, 7,    main,   -1.47,  85899.00, 1371.39,   41.59,   -7.02, 31.9, 1.60, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.91, 7,    main,    0.49,  85899.00, 1371.39,   41.59,   -6.98, 32.0, 1.60, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   216.98, 7,    main,    0.49,  85899.00, 1371.39,   41.59,   -6.98, 32.0, 1.60, 3.87, 3.99,   0.08,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   217.01, 7,    main,   -2.94,  85908.00, 1370.54,   40.74,   -6.95, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   217.11, 7,    main,   -3.92,  85919.00, 1369.49,   39.69,   -6.91, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   217.21, 7,    main,   -5.88,  85917.00, 1369.68,   39.88,   -6.87, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  8,  32.9493059,-106.9153868,  1435.0, 2022,  6, 24, 15, 20, 53,     1150,     1151, 341,   2,   2.3,   1.5,   1.7,  0, 34, 33,  0,  0, 38,  0,  0,  0,  0, 34, 27, 26, 25,  0,  0, 30,  0, 36, 22,  0,  0,  0, 23,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   217.30, 7,    main,   -5.88,  85917.00, 1369.68,   39.88,   -6.87, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.30, 7,    main,   -5.88,  85917.00, 1369.68,   39.88,   -6.87, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.30, 7,    main,   -5.88,  85917.00, 1369.68,   39.88,   -6.87, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.31, 7,    main,   -2.45,  85922.00, 1369.20,   39.40,   -6.82, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.41, 7,    main,   -2.45,  85943.00, 1367.21,   37.41,   -6.79, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.51, 7,    main,   -1.47,  85948.00, 1366.73,   36.93,   -6.75, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.61, 7,    main,   -0.49,  85947.00, 1366.83,   37.03,   -6.72, 31.9, 1.60, 3.86, 3.99,   0.09,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.62, 7,    main,   -0.49,  85947.00, 1366.83,   37.03,   -6.72, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.71, 7,    main,   -0.49,  85970.00, 1364.64,   34.84,   -6.68, 31.9, 1.60, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.81, 7,    main,   -0.49,  85971.00, 1364.54,   34.74,   -6.65, 31.9, 1.60, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.91, 7,    main,   -1.47,  85988.00, 1362.93,   33.13,   -6.62, 31.9, 1.60, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   217.94, 7,    main,   -1.47,  85988.00, 1362.93,   33.13,   -6.62, 31.9, 1.61, 3.85, 3.98,   0.08,   0.00,   0.00,  62.20,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.01, 7,    main,   -0.00,  85983.00, 1363.40,   33.60,   -6.60, 31.9, 1.61, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.11, 7,    main,   -2.94,  86008.00, 1361.03,   31.23,   -6.58, 31.9, 1.61, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.21, 7,    main,   -1.47,  85990.00, 1362.74,   32.94,   -6.53, 31.9, 1.61, 3.85, 3.98,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.26, 7,    main,   -1.47,  85990.00, 1362.74,   32.94,   -6.53, 31.9, 1.60, 3.86, 3.98,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.30, 7,    main,   -1.47,  85990.00, 1362.74,   32.94,   -6.53, 31.9, 1.60, 3.86, 3.98,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.30, 7,    main,   -1.47,  85990.00, 1362.74,   32.94,   -6.53, 31.9, 1.60, 3.86, 3.98,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493052,-106.9154366,  1429.0, 2022,  6, 24, 15, 20, 54,     1151,     1152, 341,   2,   1.6,   0.8,   1.4,  0, 37, 32,  0,  0, 26,  0,  0,  0,  0, 37, 38, 28, 30,  0,  0, 29,  0, 33, 28,  0,  0,  0, 35,  0,  0,  0,  0,  0, 23,  0,  0
+6, 6583, 3,VE3LIC,   218.31, 7,    main,   -0.98,  85995.00, 1362.26,   32.46,   -6.50, 31.9, 1.60, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.41, 7,    main,   -0.49,  86014.00, 1360.46,   30.65,   -6.47, 31.9, 1.60, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.51, 7,    main,   -2.94,  86006.00, 1361.22,   31.42,   -6.43, 31.9, 1.60, 3.86, 3.98,   0.08,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.58, 7,    main,   -2.94,  86006.00, 1361.22,   31.42,   -6.43, 31.9, 1.61, 3.85, 3.98,   0.08,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.61, 7,    main,   -1.47,  86024.00, 1359.51,   29.70,   -6.40, 31.9, 1.61, 3.85, 3.98,   0.01,   0.00,   0.00,  62.07,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.71, 7,    main,   -4.90,  86027.00, 1359.22,   29.42,   -6.36, 31.9, 1.61, 3.85, 3.98,   0.01,   0.00,   0.00,  62.07,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.81, 7,    main,   -2.94,  86023.00, 1359.60,   29.80,   -6.32, 31.9, 1.61, 3.85, 3.98,   0.01,   0.00,   0.00,  62.07,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.01, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.90, 7,    main,   -2.94,  86023.00, 1359.60,   29.80,   -6.32, 31.9, 1.62, 3.86, 3.98,   0.01,   0.00,   0.00,  62.07,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   218.91, 7,    main,   -3.43,  86033.00, 1358.65,   28.85,   -6.28, 31.9, 1.62, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.01, 7,    main,   -5.39,  86048.00, 1357.22,   27.42,   -6.24, 31.9, 1.62, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.11, 7,    main,   -2.94,  86064.00, 1355.70,   25.90,   -6.20, 31.9, 1.62, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.21, 7,    main,   -0.98,  86077.00, 1354.47,   24.67,   -6.16, 31.9, 1.62, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.22, 7,    main,   -0.98,  86077.00, 1354.47,   24.67,   -6.16, 31.9, 1.62, 3.85, 3.99,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.30, 7,    main,   -0.98,  86077.00, 1354.47,   24.67,   -6.16, 31.9, 1.62, 3.85, 3.99,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.30, 7,    main,   -0.98,  86077.00, 1354.47,   24.67,   -6.16, 31.9, 1.62, 3.85, 3.99,   0.00,   0.00,   0.00,  62.14,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493180,-106.9154824,  1422.0, 2022,  6, 24, 15, 20, 55,     1154,     1155, 341,   1,   1.6,   0.8,   1.4,  0, 36, 28,  0,  0, 27,  0,  0,  0,  0, 36, 35, 32, 29,  0,  0, 26,  0, 37, 18,  0,  0,  0, 37,  0,  0,  0,  0,  0, 24,  0,  0
+6, 6583, 3,VE3LIC,   219.31, 7,    main,   -0.00,  86067.00, 1355.42,   25.62,   -6.12, 31.9, 1.62, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.41, 7,    main,   -2.94,  86081.00, 1354.09,   24.29,   -6.08, 31.9, 1.62, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.51, 7,    main,   -0.00,  86085.00, 1353.71,   23.91,   -6.05, 31.9, 1.62, 3.85, 3.99,   0.09,   0.00,   0.00,  62.07,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.54, 7,    main,   -0.00,  86085.00, 1353.71,   23.91,   -6.05, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.07,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.61, 7,    main,   -2.45,  86100.00, 1352.28,   22.48,   -6.03, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.71, 7,    main,   -1.96,  86089.00, 1353.33,   23.53,   -6.01, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.81, 7,    main,   -2.94,  86100.00, 1352.28,   22.48,   -5.99, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.86, 7,    main,   -2.94,  86100.00, 1352.28,   22.48,   -5.99, 31.9, 1.61, 3.84, 3.97,   0.09,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   219.91, 7,    main,   -2.94,  86117.00, 1350.67,   20.87,   -5.99, 31.9, 1.61, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.01, 7,    main,   -3.43,  86112.00, 1351.14,   21.34,   -5.98, 31.9, 1.61, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.11, 7,    main,   -6.37,  86119.00, 1350.48,   20.68,   -5.99, 31.9, 1.61, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.18, 7,    main,   -6.37,  86119.00, 1350.48,   20.68,   -5.99, 31.9, 1.62, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.21, 7,    main,   -1.47,  86115.00, 1350.86,   21.06,   -6.00, 31.9, 1.62, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.30, 7,    main,   -1.47,  86115.00, 1350.86,   21.06,   -6.00, 31.9, 1.62, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.30, 7,    main,   -1.47,  86115.00, 1350.86,   21.06,   -6.00, 31.9, 1.62, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9493584,-106.9155176,  1415.0, 2022,  6, 24, 15, 20, 56,     1160,     1160, 341,   1,   1.7,   0.8,   1.4,  0, 29, 28,  0,  0, 36,  0,  0,  0,  0, 27, 31, 31, 28,  0,  0, 26,  0, 29, 29,  0,  0,  0, 33,  0,  0,  0,  0,  0, 31,  0,  0
+6, 6583, 3,VE3LIC,   220.31, 7,    main,   -1.96,  86136.00, 1348.87,   19.07,   -6.02, 31.9, 1.62, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.41, 7,    main,   -1.47,  86139.00, 1348.58,   18.78,   -6.06, 31.9, 1.62, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.50, 7,    main,   -1.47,  86139.00, 1348.58,   18.78,   -6.06, 31.9, 1.63, 3.86, 3.99,   0.00,   0.00,   0.00,  61.83,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.01, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.51, 7,    main,   -4.90,  86143.00, 1348.20,   18.40,   -6.10, 31.9, 1.63, 3.86, 3.99,   0.08,   0.00,   0.01,  62.14,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.01, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.61, 7,    main,   -8.34,  86148.00, 1347.73,   17.93,   -6.16, 31.9, 1.63, 3.86, 3.99,   0.08,   0.00,   0.01,  62.14,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.01, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.71, 7,    main,   -3.92,  86151.00, 1347.44,   17.64,   -6.22, 31.9, 1.63, 3.86, 3.99,   0.08,   0.00,   0.01,  62.14,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.01, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.81, 7,    main,   -5.88,  86156.00, 1346.97,   17.17,   -6.29, 31.9, 1.63, 3.86, 3.99,   0.08,   0.00,   0.01,  62.14,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.01, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.82, 7,    main,   -5.88,  86156.00, 1346.97,   17.17,   -6.29, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.01,  62.14,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   220.91, 7,    main,   -1.47,  86167.00, 1345.92,   16.12,   -6.35, 31.9, 1.64, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.01, 7,    main,   -3.92,  86173.00, 1345.35,   15.55,   -6.43, 31.9, 1.64, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.11, 7,    main,   -1.47,  86178.00, 1344.88,   15.08,   -6.49, 31.9, 1.64, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.14, 7,    main,   -1.47,  86178.00, 1344.88,   15.08,   -6.49, 31.9, 1.64, 3.86, 3.99,   0.09,   0.00,   0.00,  62.14,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.21, 7,    main,   -1.96,  86194.00, 1343.36,   13.56,   -6.55, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.30, 7,    main,   -1.96,  86194.00, 1343.36,   13.56,   -6.55, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.30, 7,    main,   -1.96,  86194.00, 1343.36,   13.56,   -6.55, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9493975,-106.9155325,  1409.0, 2022,  6, 24, 15, 20, 57,     1164,     1164, 341,   1,   1.6,   0.8,   1.4,  0, 30, 33,  0,  0, 36,  0,  0,  0,  0, 24, 36, 31, 27,  0,  0, 37,  0, 36, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   221.31, 7,    main,   -1.96,  86203.00, 1342.51,   12.71,   -6.59, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.41, 7,    main,   -1.96,  86197.00, 1343.08,   13.28,   -6.63, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.46, 7,    main,   -1.96,  86197.00, 1343.08,   13.28,   -6.63, 31.9, 1.64, 3.87, 3.98,   0.08,   0.00,   0.00,  62.20,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.51, 7,    main,   -1.47,  86214.00, 1341.46,   11.66,   -6.65, 31.9, 1.64, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.61, 7,    main,   -3.92,  86232.00, 1339.76,    9.95,   -6.65, 31.9, 1.64, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.71, 7,    main,   -5.39,  86224.00, 1340.51,   10.71,   -6.63, 31.9, 1.64, 3.87, 3.98,   0.09,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.07, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.78, 7,    main,   -5.39,  86224.00, 1340.51,   10.71,   -6.63, 31.9, 1.65, 3.88, 3.98,   0.09,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.81, 7,    main,   -2.45,  86221.00, 1340.80,   11.00,   -6.59, 31.9, 1.65, 3.88, 3.98,   0.08,   0.00,   0.00,  62.44,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   221.91, 7,    main,   -2.45,  86245.00, 1338.52,    8.72,   -6.54, 31.9, 1.65, 3.88, 3.98,   0.08,   0.00,   0.00,  62.44,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.01, 7,    main,   -2.94,  86243.00, 1338.71,    8.91,   -6.45, 31.9, 1.65, 3.88, 3.98,   0.08,   0.00,   0.00,  62.44,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.10, 7,    main,   -2.94,  86243.00, 1338.71,    8.91,   -6.45, 31.9, 1.65, 3.86, 3.98,   0.08,   0.00,   0.00,  62.44,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.11, 7,    main,   -0.00,  86250.00, 1338.05,    8.25,   -6.35, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.21, 7,    main,   -0.98,  86265.00, 1336.63,    6.83,   -6.22, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.30, 7,    main,   -0.98,  86265.00, 1336.63,    6.83,   -6.22, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.30, 7,    main,   -0.98,  86265.00, 1336.63,    6.83,   -6.22, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494362,-106.9155323,  1402.0, 2022,  6, 24, 15, 20, 58,     1168,     1168, 341,   0,   1.6,   0.8,   1.4,  0, 36, 34,  0,  0, 37,  0,  0,  0,  0, 34, 36, 30, 32,  0,  0, 29,  0, 29, 30,  0,  0,  0, 32,  0,  0,  0,  0,  0, 32,  0,  0
+6, 6583, 3,VE3LIC,   222.31, 7,    main,   -1.96,  86273.00, 1335.87,    6.07,   -6.08, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.41, 7,    main,    3.92,  86288.00, 1334.45,    4.64,   -5.91, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.42, 7,    main,    3.92,  86288.00, 1334.45,    4.64,   -5.91, 31.9, 1.64, 3.85, 3.99,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.51, 7,    main,    6.37,  86287.00, 1334.54,    4.74,   -5.72, 31.9, 1.64, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.61, 7,    main,    1.47,  86290.00, 1334.26,    4.45,   -5.51, 31.9, 1.64, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.71, 7,    main,    0.98,  86296.00, 1333.69,    3.89,   -5.27, 31.9, 1.64, 3.85, 3.99,   0.08,   0.00,   0.00,  62.07,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.74, 7,    main,    0.98,  86296.00, 1333.69,    3.89,   -5.27, 31.9, 1.64, 3.86, 3.98,   0.08,   0.00,   0.00,  62.07,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.81, 7,    main,    3.43,  86307.00, 1332.64,    2.84,   -5.02, 31.9, 1.64, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   222.91, 7,    main,    3.43,  86310.00, 1332.36,    2.56,   -4.76, 31.9, 1.64, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.01, 7,    main,   -1.96,  86316.00, 1331.79,    1.99,   -4.47, 31.9, 1.64, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.06, 7,    main,   -1.96,  86316.00, 1331.79,    1.99,   -4.47, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.11, 7,    main,   -2.94,  86319.00, 1331.51,    1.71,   -4.18, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.21, 7,    main,    6.86,  86315.00, 1331.89,    2.08,   -3.88, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.30, 7,    main,    6.86,  86315.00, 1331.89,    2.08,   -3.88, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.30, 7,    main,    6.86,  86315.00, 1331.89,    2.08,   -3.88, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494705,-106.9155097,  1394.0, 2022,  6, 24, 15, 20, 59,     1171,     1171, 341,   0,   1.6,   0.8,   1.4,  0, 30, 34,  0,  0, 39,  0,  0,  0,  0, 29, 35, 34, 27,  0,  0, 27,  0, 23, 34,  0,  0,  0, 35,  0,  0,  0,  0,  0, 33,  0,  0
+6, 6583, 3,VE3LIC,   223.31, 7,    main,    8.34,  86333.00, 1330.18,    0.38,   -3.58, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.38, 7,    main,    8.34,  86333.00, 1330.18,    0.38,   -3.58, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.41, 7,    main,    6.37,  86339.00, 1329.61,   -0.19,   -3.26, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.51, 7,    main,   -1.96,  86344.00, 1329.14,   -0.66,   -2.97, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.61, 7,    main,  -12.26,  86336.00, 1329.90,    0.09,   -2.67, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.70, 7,    main,  -12.26,  86336.00, 1329.90,    0.09,   -2.67, 31.9, 1.65, 3.87, 3.99,   0.02,   0.00,   0.00,  62.20,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.71, 7,    main,  -31.38,  86352.00, 1328.38,   -1.42,   -2.37, 31.9, 1.65, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.81, 7,    main,  -16.18,  86344.00, 1329.14,   -0.66,   -2.08, 31.9, 1.65, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   223.91, 7,    main,  -15.20,  86341.00, 1329.42,   -0.38,   -1.82, 31.9, 1.65, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.01, 7,    main,  -10.79,  86346.00, 1328.95,   -0.85,   -1.57, 31.9, 1.65, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.02, 7,    main,  -10.79,  86346.00, 1328.95,   -0.85,   -1.57, 31.9, 1.64, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.11, 7,    main,  -10.79,  86350.00, 1328.57,   -1.23,   -1.35, 31.9, 1.64, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.21, 7,    main,  -10.30,  86364.00, 1327.24,   -2.56,   -1.14, 31.9, 1.64, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.30, 7,    main,  -10.30,  86364.00, 1327.24,   -2.56,   -1.14, 31.9, 1.64, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.30, 7,    main,  -10.30,  86364.00, 1327.24,   -2.56,   -1.14, 31.9, 1.64, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494907,-106.9154801,  1388.0, 2022,  6, 24, 15, 21,  0,     1172,     1172, 341,  -0,   1.6,   0.8,   1.4,  0, 33, 30,  0,  0, 26,  0,  0,  0,  0, 27, 34, 28, 27,  0,  0, 38,  0, 34, 29,  0,  0,  0, 35,  0,  0,  0,  0,  0, 29,  0,  0
+6, 6583, 3,VE3LIC,   224.31, 7,    main,  -12.75,  86351.00, 1328.47,   -1.33,   -0.96, 31.9, 1.64, 3.87, 3.99,   0.02,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.34, 7,    main,  -12.75,  86351.00, 1328.47,   -1.33,   -0.96, 31.9, 1.65, 3.86, 4.00,   0.02,   0.00,   0.00,  62.26,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.41, 7,    main,   -8.83,  86341.00, 1329.42,   -0.38,   -0.80, 31.9, 1.65, 3.86, 4.00,   0.03,   0.00,   0.00,  62.14,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.51, 7,    main,  -11.77,  86356.00, 1328.00,   -1.80,   -0.65, 31.9, 1.65, 3.86, 4.00,   0.03,   0.00,   0.00,  62.14,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.61, 7,    main,  -12.26,  86346.00, 1328.95,   -0.85,   -0.52, 31.9, 1.65, 3.86, 4.00,   0.03,   0.00,   0.00,  62.14,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.66, 7,    main,  -12.26,  86346.00, 1328.95,   -0.85,   -0.52, 31.9, 1.65, 3.86, 3.99,   0.03,   0.00,   0.00,  62.14,  26.55,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.71, 7,    main,  -11.77,  86346.00, 1328.95,   -0.85,   -0.42, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.81, 7,    main,  -11.28,  86343.00, 1329.23,   -0.57,   -0.33, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.91, 7,    main,   -7.85,  86354.00, 1328.19,   -1.61,   -0.27, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   224.98, 7,    main,   -7.85,  86354.00, 1328.19,   -1.61,   -0.27, 31.9, 1.65, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.61,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   225.01, 7,    main,  -13.24,  86339.00, 1329.61,   -0.19,   -0.22, 31.9, 1.65, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   225.11, 7,    main,  -10.79,  86351.00, 1328.47,   -1.33,   -0.18, 31.9, 1.65, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   225.21, 7,    main,  -10.79,  86354.00, 1328.19,   -1.61,   -0.15, 31.9, 1.65, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1, 10,  32.9494984,-106.9154714,  1386.0, 2022,  6, 24, 15, 21,  1,     1173,     1173, 341,  -0,   1.6,   0.8,   1.4,  0, 37, 30,  0,  0, 35,  0,  0,  0,  0, 38, 33, 27, 38,  0,  0, 22,  0, 31, 28,  0,  0,  0, 31,  0,  0,  0,  0,  0, 27,  0,  0
+6, 6583, 3,VE3LIC,   225.30, 7,    main,  -10.79,  86354.00, 1328.19,   -1.61,   -0.15, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.30, 7,    main,  -10.79,  86354.00, 1328.19,   -1.61,   -0.15, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.30, 7,    main,  -10.79,  86354.00, 1328.19,   -1.61,   -0.15, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  62.14,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.31, 7,    main,  -12.26,  86346.00, 1328.95,   -0.85,   -0.13, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.41, 7,    main,   -9.32,  86347.00, 1328.85,   -0.95,   -0.12, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.51, 7,    main,  -10.30,  86361.00, 1327.53,   -2.27,   -0.10, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.61, 7,    main,  -12.26,  86338.00, 1329.71,   -0.09,   -0.09, 31.9, 1.63, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.62, 7,    main,  -12.26,  86338.00, 1329.71,   -0.09,   -0.09, 31.9, 1.64, 3.86, 3.99,   0.00,   0.00,   0.00,  61.95,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.71, 7,    main,  -11.77,  86350.00, 1328.57,   -1.23,   -0.08, 31.9, 1.64, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.81, 7,    main,  -11.28,  86355.00, 1328.10,   -1.71,   -0.07, 31.9, 1.64, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.91, 7,    main,  -12.26,  86356.00, 1328.00,   -1.80,   -0.07, 31.9, 1.64, 3.86, 3.99,   0.00,   0.00,   0.00,  62.14,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   225.94, 7,    main,  -12.26,  86356.00, 1328.00,   -1.80,   -0.07, 31.9, 1.65, 3.86, 3.98,   0.00,   0.00,   0.00,  62.14,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.01, 7,    main,  -10.30,  86345.00, 1329.04,   -0.76,   -0.06, 31.9, 1.65, 3.86, 3.98,   0.06,   0.00,   0.00,  62.20,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.11, 7,    main,  -13.24,  86363.00, 1327.34,   -2.46,   -0.04, 31.9, 1.65, 3.86, 3.98,   0.06,   0.00,   0.00,  62.20,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.21, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,   -0.03, 31.9, 1.65, 3.86, 3.98,   0.06,   0.00,   0.00,  62.20,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.05, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.26, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,   -0.03, 31.9, 1.64, 3.86, 3.99,   0.06,   0.00,   0.00,  62.20,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.30, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,   -0.03, 31.9, 1.64, 3.86, 3.99,   0.06,   0.00,   0.00,  62.20,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.30, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,   -0.03, 31.9, 1.64, 3.86, 3.99,   0.06,   0.00,   0.00,  62.20,  26.49,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495006,-106.9154745,  1386.0, 2022,  6, 24, 15, 21,  2,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 30,  0,  0, 23,  0,  0,  0,  0, 39, 32, 24, 28,  0,  0, 34,  0, 37, 16,  0,  0,  0, 30,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.31, 7,    main,  -12.75,  86353.00, 1328.28,   -1.52,   -0.02, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.41, 7,    main,   -9.81,  86348.00, 1328.76,   -1.04,    0.00, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.51, 7,    main,  -11.77,  86353.00, 1328.28,   -1.52,    0.01, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.58, 7,    main,  -11.77,  86353.00, 1328.28,   -1.52,    0.01, 31.9, 1.64, 3.87, 3.99,   0.08,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.61, 7,    main,   -9.81,  86336.00, 1329.90,    0.09,    0.02, 31.9, 1.64, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.71, 7,    main,  -12.26,  86354.00, 1328.19,   -1.61,    0.03, 31.9, 1.64, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.81, 7,    main,  -10.79,  86355.00, 1328.10,   -1.71,    0.04, 31.9, 1.64, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.90, 7,    main,  -10.79,  86355.00, 1328.10,   -1.71,    0.04, 31.9, 1.63, 3.86, 3.98,   0.03,   0.00,   0.00,  62.32,  26.43,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   226.91, 7,    main,  -13.73,  86352.00, 1328.38,   -1.42,    0.04, 31.9, 1.63, 3.86, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.01, 7,    main,   -8.83,  86362.00, 1327.43,   -2.37,    0.05, 31.9, 1.63, 3.86, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.11, 7,    main,  -11.77,  86350.00, 1328.57,   -1.23,    0.05, 31.9, 1.63, 3.86, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.21, 7,    main,  -12.75,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.63, 3.86, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.22, 7,    main,  -12.75,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.63, 3.87, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.30, 7,    main,  -12.75,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.63, 3.87, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.30, 7,    main,  -12.75,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.63, 3.87, 3.98,   0.03,   0.00,   0.00,  62.14,  26.18,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495014,-106.9154756,  1386.0, 2022,  6, 24, 15, 21,  3,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 23,  0,  0,  0,  0, 39, 33, 22, 27,  0,  0, 34,  0, 36, 19,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.31, 7,    main,  -10.30,  86352.00, 1328.38,   -1.42,    0.05, 31.9, 1.63, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.41, 7,    main,  -12.26,  86341.00, 1329.42,   -0.38,    0.05, 31.9, 1.63, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.51, 7,    main,  -12.26,  86339.00, 1329.61,   -0.19,    0.04, 31.9, 1.63, 3.87, 3.98,   0.08,   0.00,   0.00,  62.26,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.06, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.54, 7,    main,  -12.26,  86339.00, 1329.61,   -0.19,    0.04, 31.9, 1.64, 3.86, 3.99,   0.08,   0.00,   0.00,  62.26,  26.31,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.61, 7,    main,  -11.28,  86352.00, 1328.38,   -1.42,    0.05, 31.9, 1.64, 3.86, 3.99,   0.03,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.71, 7,    main,  -11.77,  86349.00, 1328.66,   -1.14,    0.04, 31.9, 1.64, 3.86, 3.99,   0.03,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.81, 7,    main,  -10.79,  86354.00, 1328.19,   -1.61,    0.03, 31.9, 1.64, 3.86, 3.99,   0.03,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.86, 7,    main,  -10.79,  86354.00, 1328.19,   -1.61,    0.03, 31.9, 1.63, 3.87, 3.99,   0.03,   0.00,   0.00,  62.20,  26.37,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   227.91, 7,    main,  -11.28,  86357.00, 1327.91,   -1.90,    0.02, 31.9, 1.63, 3.87, 3.99,   0.02,   0.00,   0.00,  62.38,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.01, 7,    main,   -9.32,  86349.00, 1328.66,   -1.14,    0.03, 31.9, 1.63, 3.87, 3.99,   0.02,   0.00,   0.00,  62.38,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.11, 7,    main,  -10.30,  86343.00, 1329.23,   -0.57,    0.02, 31.9, 1.63, 3.87, 3.99,   0.02,   0.00,   0.00,  62.38,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.18, 7,    main,  -10.30,  86343.00, 1329.23,   -0.57,    0.02, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.38,  26.25,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.21, 7,    main,  -10.79,  86347.00, 1328.85,   -0.95,    0.03, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.30, 7,    main,  -10.79,  86347.00, 1328.85,   -0.95,    0.03, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.30, 7,    main,  -10.79,  86347.00, 1328.85,   -0.95,    0.03, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495024,-106.9154750,  1387.0, 2022,  6, 24, 15, 21,  4,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 22,  0,  0,  0,  0, 39, 33, 19, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.31, 7,    main,  -12.26,  86346.00, 1328.95,   -0.85,    0.03, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.41, 7,    main,  -10.79,  86355.00, 1328.10,   -1.71,    0.04, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.50, 7,    main,  -10.79,  86355.00, 1328.10,   -1.71,    0.04, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.51, 7,    main,  -11.28,  86351.00, 1328.47,   -1.33,    0.04, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.61, 7,    main,  -11.28,  86355.00, 1328.10,   -1.71,    0.05, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.71, 7,    main,  -11.77,  86352.00, 1328.38,   -1.42,    0.06, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.81, 7,    main,  -10.30,  86350.00, 1328.57,   -1.23,    0.06, 31.9, 1.62, 3.87, 3.98,   0.02,   0.00,   0.00,  62.26,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.82, 7,    main,  -10.30,  86350.00, 1328.57,   -1.23,    0.06, 31.9, 1.62, 3.86, 3.99,   0.02,   0.00,   0.00,  62.26,  26.12,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   228.91, 7,    main,  -12.26,  86357.00, 1327.91,   -1.90,    0.07, 31.9, 1.62, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.01, 7,    main,  -11.28,  86340.00, 1329.52,   -0.28,    0.07, 31.9, 1.62, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.11, 7,    main,  -10.79,  86343.00, 1329.23,   -0.57,    0.08, 31.9, 1.62, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.14, 7,    main,  -10.79,  86343.00, 1329.23,   -0.57,    0.08, 31.9, 1.62, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.21, 7,    main,  -11.77,  86344.00, 1329.14,   -0.66,    0.10, 31.9, 1.62, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.30, 7,    main,  -11.77,  86344.00, 1329.14,   -0.66,    0.10, 31.9, 1.62, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.30, 7,    main,  -11.77,  86344.00, 1329.14,   -0.66,    0.10, 31.9, 1.62, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9495026,-106.9154760,  1387.0, 2022,  6, 24, 15, 21,  5,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.31, 7,    main,  -11.28,  86348.00, 1328.76,   -1.04,    0.11, 31.9, 1.62, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.41, 7,    main,  -11.77,  86352.00, 1328.38,   -1.42,    0.11, 31.9, 1.62, 3.86, 3.99,   0.00,   0.00,   0.04,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.03, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.46, 7,    main,  -11.77,  86352.00, 1328.38,   -1.42,    0.11, 31.9, 1.61, 3.87, 3.99,   0.00,   0.00,   0.04,  62.20,  26.06,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.51, 7,    main,  -10.30,  86346.00, 1328.95,   -0.85,    0.12, 31.9, 1.61, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.61, 7,    main,  -10.30,  86352.00, 1328.38,   -1.42,    0.12, 31.9, 1.61, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.71, 7,    main,  -12.26,  86355.00, 1328.10,   -1.71,    0.11, 31.9, 1.61, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.78, 7,    main,  -12.26,  86355.00, 1328.10,   -1.71,    0.11, 31.9, 1.61, 3.86, 3.99,   0.03,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.81, 7,    main,  -13.24,  86352.00, 1328.38,   -1.42,    0.10, 31.9, 1.61, 3.86, 3.99,   0.03,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   229.91, 7,    main,  -12.75,  86356.00, 1328.00,   -1.80,    0.09, 31.9, 1.61, 3.86, 3.99,   0.03,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.01, 7,    main,  -12.75,  86338.00, 1329.71,   -0.09,    0.09, 31.9, 1.61, 3.86, 3.99,   0.03,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.10, 7,    main,  -12.75,  86338.00, 1329.71,   -0.09,    0.09, 31.9, 1.61, 3.85, 3.97,   0.03,   0.00,   0.00,  62.14,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.11, 7,    main,  -13.24,  86347.00, 1328.85,   -0.95,    0.09, 31.9, 1.61, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.21, 7,    main,  -12.26,  86353.00, 1328.28,   -1.52,    0.08, 31.9, 1.61, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.30, 7,    main,  -12.26,  86353.00, 1328.28,   -1.52,    0.08, 31.9, 1.61, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.30, 7,    main,  -12.26,  86353.00, 1328.28,   -1.52,    0.08, 31.9, 1.61, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495035,-106.9154759,  1387.0, 2022,  6, 24, 15, 21,  6,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.31, 7,    main,  -12.26,  86340.00, 1329.52,   -0.28,    0.07, 31.9, 1.61, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.41, 7,    main,   -9.81,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.61, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.42, 7,    main,   -9.81,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.60, 3.85, 3.97,   0.00,   0.00,   0.00,  62.07,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.51, 7,    main,  -12.75,  86348.00, 1328.76,   -1.04,    0.04, 31.9, 1.60, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.61, 7,    main,  -11.77,  86340.00, 1329.52,   -0.28,    0.03, 31.9, 1.60, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.71, 7,    main,  -11.28,  86345.00, 1329.04,   -0.76,    0.02, 31.9, 1.60, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.74, 7,    main,  -11.28,  86345.00, 1329.04,   -0.76,    0.02, 31.9, 1.61, 3.87, 3.98,   0.00,   0.00,   0.00,  61.95,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.81, 7,    main,  -12.75,  86348.00, 1328.76,   -1.04,    0.01, 31.9, 1.61, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   230.91, 7,    main,  -11.77,  86350.00, 1328.57,   -1.23,    0.00, 31.9, 1.61, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.01, 7,    main,   -6.86,  86355.00, 1328.10,   -1.71,    0.00, 31.9, 1.61, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.06, 7,    main,   -6.86,  86355.00, 1328.10,   -1.71,    0.00, 31.9, 1.60, 3.84, 3.97,   0.02,   0.00,   0.00,  62.32,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.11, 7,    main,  -12.26,  86341.00, 1329.42,   -0.38,    0.00, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.21, 7,    main,   -9.81,  86348.00, 1328.76,   -1.04,    0.01, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.30, 7,    main,   -9.81,  86348.00, 1328.76,   -1.04,    0.01, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.30, 7,    main,   -9.81,  86348.00, 1328.76,   -1.04,    0.01, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495044,-106.9154755,  1387.0, 2022,  6, 24, 15, 21,  7,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 19, 25,  0,  0, 35,  0, 35, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.31, 7,    main,  -13.24,  86335.00, 1329.99,    0.19,    0.01, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.89,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.38, 7,    main,  -13.24,  86335.00, 1329.99,    0.19,    0.01, 31.9, 1.61, 3.87, 3.99,   0.00,   0.00,   0.00,  61.89,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.41, 7,    main,   -9.32,  86363.00, 1327.34,   -2.46,    0.01, 31.9, 1.61, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.51, 7,    main,  -13.24,  86349.00, 1328.66,   -1.14,    0.02, 31.9, 1.61, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.61, 7,    main,  -10.30,  86352.00, 1328.38,   -1.42,    0.03, 31.9, 1.61, 3.87, 3.99,   0.03,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.70, 7,    main,  -10.30,  86352.00, 1328.38,   -1.42,    0.03, 31.9, 1.61, 3.86, 3.98,   0.03,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.71, 7,    main,  -11.28,  86354.00, 1328.19,   -1.61,    0.03, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.81, 7,    main,   -8.83,  86350.00, 1328.57,   -1.23,    0.05, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   231.91, 7,    main,  -12.26,  86334.00, 1330.09,    0.28,    0.07, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.01, 7,    main,  -10.79,  86344.00, 1329.14,   -0.66,    0.08, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.02, 7,    main,  -10.79,  86344.00, 1329.14,   -0.66,    0.08, 31.9, 1.61, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.11, 7,    main,  -10.30,  86346.00, 1328.95,   -0.85,    0.09, 31.9, 1.61, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.21, 7,    main,  -11.77,  86338.00, 1329.71,   -0.09,    0.10, 31.9, 1.61, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.30, 7,    main,  -11.77,  86338.00, 1329.71,   -0.09,    0.10, 31.9, 1.61, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.30, 7,    main,  -11.77,  86338.00, 1329.71,   -0.09,    0.10, 31.9, 1.61, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495037,-106.9154752,  1387.0, 2022,  6, 24, 15, 21,  8,     1173,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 33, 19, 25,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.31, 7,    main,  -12.26,  86354.00, 1328.19,   -1.61,    0.12, 31.9, 1.61, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 3.99, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.34, 7,    main,  -12.26,  86354.00, 1328.19,   -1.61,    0.12, 31.9, 1.60, 3.85, 3.99,   0.00,   0.00,   0.00,  62.20,  26.00,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.41, 7,    main,   -8.34,  86359.00, 1327.72,   -2.08,    0.13, 31.9, 1.60, 3.85, 3.99,   0.02,   0.00,   0.00,  62.07,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.51, 7,    main,  -11.28,  86351.00, 1328.47,   -1.33,    0.14, 31.9, 1.60, 3.85, 3.99,   0.02,   0.00,   0.00,  62.07,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.61, 7,    main,   -9.81,  86344.00, 1329.14,   -0.66,    0.15, 31.9, 1.60, 3.85, 3.99,   0.02,   0.00,   0.00,  62.07,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.66, 7,    main,   -9.81,  86344.00, 1329.14,   -0.66,    0.15, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.07,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.71, 7,    main,  -11.28,  86344.00, 1329.14,   -0.66,    0.15, 31.9, 1.61, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.81, 7,    main,  -12.26,  86349.00, 1328.66,   -1.14,    0.14, 31.9, 1.61, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.91, 7,    main,   -8.34,  86347.00, 1328.85,   -0.95,    0.13, 31.9, 1.61, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   232.98, 7,    main,   -8.34,  86347.00, 1328.85,   -0.95,    0.13, 31.9, 1.61, 3.87, 3.99,   0.00,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.01, 7,    main,  -12.26,  86349.00, 1328.66,   -1.14,    0.12, 31.9, 1.61, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.11, 7,    main,  -10.30,  86340.00, 1329.52,   -0.28,    0.11, 31.9, 1.61, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.21, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,    0.09, 31.9, 1.61, 3.87, 3.99,   0.00,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495018,-106.9154757,  1386.0, 2022,  6, 24, 15, 21,  9,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 20,  0,  0,  0,  0, 39, 32, 19, 26,  0,  0, 35,  0, 36, 21,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.30, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,    0.09, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.30, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,    0.09, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.30, 7,    main,  -10.79,  86341.00, 1329.42,   -0.38,    0.09, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.32,  25.94,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.31, 7,    main,  -12.26,  86346.00, 1328.95,   -0.85,    0.08, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.41, 7,    main,  -11.77,  86339.00, 1329.61,   -0.19,    0.06, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.51, 7,    main,  -11.28,  86348.00, 1328.76,   -1.04,    0.05, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.61, 7,    main,  -12.75,  86346.00, 1328.95,   -0.85,    0.03, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.62, 7,    main,  -12.75,  86346.00, 1328.95,   -0.85,    0.03, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.71, 7,    main,  -11.77,  86350.00, 1328.57,   -1.23,    0.02, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.81, 7,    main,  -11.28,  86340.00, 1329.52,   -0.28,   -0.00, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.91, 7,    main,  -11.28,  86341.00, 1329.42,   -0.38,   -0.00, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   233.94, 7,    main,  -11.28,  86341.00, 1329.42,   -0.38,   -0.00, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.01, 7,    main,  -11.28,  86352.00, 1328.38,   -1.42,   -0.01, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.11, 7,    main,   -8.83,  86352.00, 1328.38,   -1.42,   -0.03, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.21, 7,    main,   -9.32,  86340.00, 1329.52,   -0.28,   -0.02, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.26, 7,    main,   -9.32,  86340.00, 1329.52,   -0.28,   -0.02, 31.9, 1.60, 3.87, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.31, 7,    main,  -15.69,  86339.00, 1329.61,   -0.19,   -0.03, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.31, 7,    main,  -15.69,  86339.00, 1329.61,   -0.19,   -0.03, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.31, 7,    main,  -15.69,  86339.00, 1329.61,   -0.19,   -0.03, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495002,-106.9154760,  1386.0, 2022,  6, 24, 15, 21, 10,     1173,     1173, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 18, 25,  0,  0, 35,  0, 36, 20,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.41, 7,    main,  -10.30,  86342.00, 1329.33,   -0.47,   -0.04, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.51, 7,    main,  -12.75,  86350.00, 1328.57,   -1.23,   -0.05, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.58, 7,    main,  -12.75,  86350.00, 1328.57,   -1.23,   -0.05, 31.9, 1.61, 3.86, 3.99,   0.09,   0.00,   0.00,  62.32,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.61, 7,    main,  -11.28,  86345.00, 1329.04,   -0.76,   -0.05, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.71, 7,    main,  -11.77,  86341.00, 1329.42,   -0.38,   -0.05, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.81, 7,    main,  -11.77,  86354.00, 1328.19,   -1.61,   -0.05, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.90, 7,    main,  -11.77,  86354.00, 1328.19,   -1.61,   -0.05, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   234.91, 7,    main,  -11.28,  86352.00, 1328.38,   -1.42,   -0.04, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.01, 7,    main,   -9.81,  86349.00, 1328.66,   -1.14,   -0.04, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.11, 7,    main,  -11.77,  86348.00, 1328.76,   -1.04,   -0.04, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.21, 7,    main,  -11.28,  86347.00, 1328.85,   -0.95,   -0.04, 31.9, 1.61, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.22, 7,    main,  -11.28,  86347.00, 1328.85,   -0.95,   -0.04, 31.9, 1.58, 3.85, 3.97,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.30, 7,    main,  -11.28,  86347.00, 1328.85,   -0.95,   -0.04, 31.9, 1.58, 3.85, 3.97,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.30, 7,    main,  -11.28,  86347.00, 1328.85,   -0.95,   -0.04, 31.9, 1.58, 3.85, 3.97,   0.02,   0.00,   0.00,  62.20,  25.88,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495056,-106.9154724,  1388.0, 2022,  6, 24, 15, 21, 11,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 19,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.31, 7,    main,  -13.24,  86342.00, 1329.33,   -0.47,   -0.04, 31.9, 1.58, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.41, 7,    main,   -9.81,  86336.00, 1329.90,    0.09,   -0.04, 31.9, 1.58, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.51, 7,    main,  -10.30,  86341.00, 1329.42,   -0.38,   -0.06, 31.9, 1.58, 3.85, 3.97,   0.00,   0.00,   0.00,  61.95,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.54, 7,    main,  -10.30,  86341.00, 1329.42,   -0.38,   -0.06, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.95,  25.51,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.61, 7,    main,  -11.77,  86346.00, 1328.95,   -0.85,   -0.06, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.71, 7,    main,  -11.77,  86348.00, 1328.76,   -1.04,   -0.07, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.81, 7,    main,  -11.77,  86353.00, 1328.28,   -1.52,   -0.07, 31.9, 1.60, 3.84, 3.97,   0.00,   0.00,   0.00,  61.83,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 3.98, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.86, 7,    main,  -11.77,  86353.00, 1328.28,   -1.52,   -0.07, 31.9, 1.60, 3.86, 3.98,   0.00,   0.00,   0.00,  61.83,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   235.91, 7,    main,  -10.79,  86344.00, 1329.14,   -0.66,   -0.08, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.01, 7,    main,  -11.28,  86346.00, 1328.95,   -0.85,   -0.09, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.11, 7,    main,  -10.79,  86352.00, 1328.38,   -1.42,   -0.11, 31.9, 1.60, 3.86, 3.98,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.18, 7,    main,  -10.79,  86352.00, 1328.38,   -1.42,   -0.11, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.21, 7,    main,   -8.34,  86334.00, 1330.09,    0.28,   -0.11, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.30, 7,    main,   -8.34,  86334.00, 1330.09,    0.28,   -0.11, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.30, 7,    main,   -8.34,  86334.00, 1330.09,    0.28,   -0.11, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495055,-106.9154701,  1388.0, 2022,  6, 24, 15, 21, 12,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.31, 7,    main,  -11.77,  86343.00, 1329.23,   -0.57,   -0.12, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.41, 7,    main,   -9.81,  86354.00, 1328.19,   -1.61,   -0.13, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.50, 7,    main,   -9.81,  86354.00, 1328.19,   -1.61,   -0.13, 31.9, 1.60, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.51, 7,    main,  -12.26,  86356.00, 1328.00,   -1.80,   -0.15, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.61, 7,    main,  -11.77,  86350.00, 1328.57,   -1.23,   -0.16, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.71, 7,    main,   -9.81,  86342.00, 1329.33,   -0.47,   -0.16, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.81, 7,    main,   -9.81,  86347.00, 1328.85,   -0.95,   -0.17, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.82, 7,    main,   -9.81,  86347.00, 1328.85,   -0.95,   -0.17, 31.9, 1.60, 3.87, 3.98,   0.09,   0.00,   0.00,  62.20,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   236.91, 7,    main,  -10.30,  86343.00, 1329.23,   -0.57,   -0.18, 31.9, 1.60, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.01, 7,    main,  -11.28,  86342.00, 1329.33,   -0.47,   -0.18, 31.9, 1.60, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.11, 7,    main,  -10.79,  86352.00, 1328.38,   -1.42,   -0.18, 31.9, 1.60, 3.87, 3.98,   0.02,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.02, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.14, 7,    main,  -10.79,  86352.00, 1328.38,   -1.42,   -0.18, 31.9, 1.60, 3.86, 3.99,   0.02,   0.00,   0.00,  62.32,  25.70,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.21, 7,    main,   -8.83,  86354.00, 1328.19,   -1.61,   -0.17, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.30, 7,    main,   -8.83,  86354.00, 1328.19,   -1.61,   -0.17, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.30, 7,    main,   -8.83,  86354.00, 1328.19,   -1.61,   -0.17, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495059,-106.9154695,  1388.0, 2022,  6, 24, 15, 21, 13,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 26,  0,  0, 35,  0, 36, 18,  0,  0,  0, 29,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.31, 7,    main,  -11.28,  86346.00, 1328.95,   -0.85,   -0.16, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.41, 7,    main,  -11.28,  86344.00, 1329.14,   -0.66,   -0.15, 31.9, 1.60, 3.86, 3.99,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.01, 0.00, 0.00, 0.00, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.46, 7,    main,  -11.28,  86344.00, 1329.14,   -0.66,   -0.15, 31.9, 1.60, 3.86, 3.98,   0.00,   0.00,   0.00,  62.20,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.51, 7,    main,  -10.30,  86355.00, 1328.10,   -1.71,   -0.14, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.61, 7,    main,  -12.26,  86348.00, 1328.76,   -1.04,   -0.14, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.71, 7,    main,  -11.28,  86339.00, 1329.61,   -0.19,   -0.13, 31.9, 1.60, 3.86, 3.98,   0.09,   0.00,   0.00,  62.14,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.78, 7,    main,  -11.28,  86339.00, 1329.61,   -0.19,   -0.13, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.14,  25.76,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.81, 7,    main,  -12.26,  86351.00, 1328.47,   -1.33,   -0.13, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
+6, 6583, 3,VE3LIC,   237.94, 8,  landed,  -12.26,  86351.00, 1328.47,   -1.33,   -0.13, 31.9, 1.60, 3.87, 3.99,   0.09,   0.00,   0.00,  62.26,  25.82,   0.00,   0.00,   0.00,   0.00,    NaN, 4.00, 0.00, 0.00, 0.07, 0.00, 1, 1,  9,  32.9495063,-106.9154694,  1388.0, 2022,  6, 24, 15, 21, 14,     1174,     1174, 341,  -0,   1.9,   0.8,   1.6,  0, 39, 29,  0,  0, 21,  0,  0,  0,  0, 39, 32, 17, 25,  0,  0, 35,  0, 36, 18,  0,  0,  0, 28,  0,  0,  0,  0,  0,  0,  0,  0
diff --git a/docs/conf.py b/docs/conf.py
index 75f7a18a7..1253a268b 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -13,18 +13,19 @@
 import os
 import sys
 
-sys.path.insert(0, os.path.abspath("../"))
-
+package_path = os.path.abspath("../")
+sys.path.insert(0, package_path)
+os.environ["PYTHONPATH"] = ":".join((package_path, os.environ.get("PYTHONPATH", "")))
 
 # -- Project information -----------------------------------------------------
 
 project = "RocketPy"
-copyright = "2023, RocketPy Team"
+copyright = "2024, RocketPy Team"
 
 author = "RocketPy Team"
 
 # The full version, including alpha/beta/rc tags
-release = "1.2.2"
+release = "1.3.0.post1"
 
 
 # -- General configuration ---------------------------------------------------
@@ -40,7 +41,6 @@
     "sphinx_design",
     "jupyter_sphinx",
     "nbsphinx",
-    "m2r2",
 ]
 
 # source_suffix = '.rst'
@@ -95,7 +95,7 @@
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
 html_static_path = ["static"]
-html_css_files = ["notebooks.css"]
+html_css_files = ["rocketpy.css"]
 html_favicon = "static/favicon.ico"
 html_theme_options = {
     "logo_link": "index",
diff --git a/docs/examples/index.rst b/docs/examples/index.rst
index ca1a877c3..7632c429e 100644
--- a/docs/examples/index.rst
+++ b/docs/examples/index.rst
@@ -16,4 +16,5 @@ If you want to see your rocket here, please contact the maintainers!
    valetudo_flight_sim.ipynb
    SEB_liquid_motor.ipynb
    juno3_flight_sim.ipynb
+   prometheus_2022_flight_sim.ipynb
 
diff --git a/docs/examples/prometheus_2022_flight_sim.ipynb b/docs/examples/prometheus_2022_flight_sim.ipynb
new file mode 100644
index 000000000..f41fe9135
--- /dev/null
+++ b/docs/examples/prometheus_2022_flight_sim.ipynb
@@ -0,0 +1,696 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Prometheus - Western Engineering Rocketry Team 2022\n",
+    "\n",
+    "Launched at Spaceport America Cup 2022 edition.  \n",
+    "Western Engineering Rocketry Team is a rocket design team from Western University in London, Ontario (Canada).\n",
+    "Permission to use flight data given by Giorgio Chassikos, 2024.\n",
+    "\n",
+    "Website: [https://www.werocketry.com/](https://www.werocketry.com/)\n",
+    "\n",
+    "## Team Information:\n",
+    "The Western Engineering Rocketry Team is a student-led engineering design team founded in 2016 at Western University in London, Ontario.  \n",
+    "Comprised of engineering students from a variety of disciplines, the team's goal is to develop and launch rockets through the Intercollegiate Rocket Engineering Competition.\n",
+    "\n",
+    "## Flight Card Results:\n",
+    "1. **Launch Date:** June 24th, 2022, 9:17am local time\n",
+    "2. **Last Simulated Apogee:** 4190.05 m\n",
+    "3. **Official Recorded Apogee:** 3898.37 m\n",
+    "\n",
+    "If we calculate the simulation error and divide it by the actual apogee, we get a relative error of 7.48%.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from rocketpy import Function, Rocket, GenericMotor, Flight, Environment\n",
+    "from rocketpy.simulation.flight_data_importer import FlightDataImporter\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "plt.style.use(\"seaborn-v0_8-colorblind\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define the Environment"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "env = Environment(\n",
+    "    latitude=32.939377,\n",
+    "    longitude=-106.911986,\n",
+    "    elevation=1401,\n",
+    ")\n",
+    "env.set_date(date=(2023, 6, 24, 9), timezone=\"America/Denver\")\n",
+    "\n",
+    "env.set_atmospheric_model(\n",
+    "    type=\"Reanalysis\",\n",
+    "    file=\"../../data/weather/spaceport_america_pressure_levels_2023_hourly.nc\",\n",
+    "    dictionary=\"ECMWF\",\n",
+    ")\n",
+    "\n",
+    "env.max_expected_height = 6000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Gravity Details\n",
+      "\n",
+      "Acceleration of gravity at surface level:    9.7913 m/s²\n",
+      "Acceleration of gravity at   6.000 km (ASL): 9.7771 m/s²\n",
+      "\n",
+      "\n",
+      "Launch Site Details\n",
+      "\n",
+      "Launch Date: 2023-06-24 15:00:00 UTC | 2023-06-24 09:00:00 America/Denver\n",
+      "Launch Site Latitude: 32.93938°\n",
+      "Launch Site Longitude: -106.91199°\n",
+      "Reference Datum: SIRGAS2000\n",
+      "Launch Site UTM coordinates: 321254.52 W    3646188.36 N\n",
+      "Launch Site UTM zone: 13S\n",
+      "Launch Site Surface Elevation: 1401.0 m\n",
+      "\n",
+      "\n",
+      "Atmospheric Model Details\n",
+      "\n",
+      "Atmospheric Model Type: Reanalysis\n",
+      "Reanalysis Maximum Height: 6.000 km\n",
+      "Reanalysis Time Period: From  2023-06-19 00:00:00  to  2023-06-24 23:00:00  UTC\n",
+      "Reanalysis Hour Interval: 1  hrs\n",
+      "Reanalysis Latitude Range: From  36.75 ° To  29.0 °\n",
+      "Reanalysis Longitude Range: From  -108.87999725341797 ° To  -105.12999725341797 °\n",
+      "\n",
+      "\n",
+      "Surface Atmospheric Conditions\n",
+      "\n",
+      "Surface Wind Speed: 0.20 m/s\n",
+      "Surface Wind Direction: 304.58°\n",
+      "Surface Wind Heading: 124.58°\n",
+      "Surface Pressure: 861.95 hPa\n",
+      "Surface Temperature: 299.96 K\n",
+      "Surface Air Density: 1.001 kg/m³\n",
+      "Surface Speed of Sound: 347.20 m/s\n",
+      "\n",
+      "\n",
+      "Earth Model Details\n",
+      "\n",
+      "Earth Radius at Launch site: 6371.85 km\n",
+      "Semi-major Axis: 6378.14 km\n",
+      "Semi-minor Axis: 6356.75 km\n",
+      "Flattening: 0.0034\n",
+      "\n",
+      "\n",
+      "Atmospheric Model Plots\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x450 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "env.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define the motor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Motor Details\n",
+      "Total Burning Time: 4.897 s\n",
+      "Total Propellant Mass: 3.737 kg\n",
+      "Average Propellant Exhaust Velocity: 2028.119 m/s\n",
+      "Average Thrust: 1547.699 N\n",
+      "Maximum Thrust: 1827.113 N at 1.652 s after ignition.\n",
+      "Total Impulse: 7579.081 Ns\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "motor_M1520 = GenericMotor(\n",
+    "    # burn specs: https://www.thrustcurve.org/simfiles/5f4294d20002e900000006b1/\n",
+    "    thrust_source=\"../../data/motors/cesaroni/Cesaroni_7579M1520-P.eng\",\n",
+    "    burn_time=4.897,\n",
+    "    propellant_initial_mass=3.737,\n",
+    "    dry_mass=2.981,\n",
+    "    # casing specs: Pro98 3G Gen2 casing\n",
+    "    chamber_radius=0.064,\n",
+    "    chamber_height=0.548,\n",
+    "    chamber_position=0.274,\n",
+    "    nozzle_radius=0.027,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "motor_M1520.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define the Rocket"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def prometheus_cd_at_ma(mach):\n",
+    "    \"\"\"Gives the drag coefficient of the rocket at a given mach number.\"\"\"\n",
+    "    if mach <= 0.15:\n",
+    "        return 0.422\n",
+    "    elif mach <= 0.45:\n",
+    "        return 0.422 + (mach - 0.15) * (0.38 - 0.422) / (0.45 - 0.15)\n",
+    "    elif mach <= 0.77:\n",
+    "        return 0.38 + (mach - 0.45) * (0.32 - 0.38) / (0.77 - 0.45)\n",
+    "    elif mach <= 0.82:\n",
+    "        return 0.32 + (mach - 0.77) * (0.3 - 0.32) / (0.82 - 0.77)\n",
+    "    elif mach <= 0.88:\n",
+    "        return 0.3 + (mach - 0.82) * (0.3 - 0.3) / (0.88 - 0.82)\n",
+    "    elif mach <= 0.94:\n",
+    "        return 0.3 + (mach - 0.88) * (0.32 - 0.3) / (0.94 - 0.88)\n",
+    "    elif mach <= 0.99:\n",
+    "        return 0.32 + (mach - 0.94) * (0.37 - 0.32) / (0.99 - 0.94)\n",
+    "    elif mach <= 1.04:\n",
+    "        return 0.37 + (mach - 0.99) * (0.44 - 0.37) / (1.04 - 0.99)\n",
+    "    elif mach <= 1.24:\n",
+    "        return 0.44 + (mach - 1.04) * (0.43 - 0.44) / (1.24 - 1.04)\n",
+    "    elif mach <= 1.33:\n",
+    "        return 0.43 + (mach - 1.24) * (0.42 - 0.43) / (1.33 - 1.24)\n",
+    "    elif mach <= 1.49:\n",
+    "        return 0.42 + (mach - 1.33) * (0.39 - 0.42) / (1.49 - 1.33)\n",
+    "    else:\n",
+    "        return 0.39\n",
+    "\n",
+    "\n",
+    "prometheus = Rocket(\n",
+    "    radius=0.06985,  # 5.5\" diameter circle\n",
+    "    mass=13.93,\n",
+    "    inertia=(\n",
+    "        4.87,\n",
+    "        4.87,\n",
+    "        0.05,\n",
+    "    ),\n",
+    "    power_off_drag=prometheus_cd_at_ma,\n",
+    "    power_on_drag=lambda x: prometheus_cd_at_ma(x) * 1.02,  # 5% increase in drag\n",
+    "    center_of_mass_without_motor=0.9549,\n",
+    "    coordinate_system_orientation=\"tail_to_nose\",\n",
+    ")\n",
+    "\n",
+    "prometheus.set_rail_buttons(0.69, 0.21, 60)\n",
+    "\n",
+    "prometheus.add_motor(motor=motor_M1520, position=0)\n",
+    "nose_cone = prometheus.add_nose(length=0.742, kind=\"Von Karman\", position=2.229)\n",
+    "fin_set = prometheus.add_trapezoidal_fins(\n",
+    "    n=3,\n",
+    "    span=0.13,\n",
+    "    root_chord=0.268,\n",
+    "    tip_chord=0.136,\n",
+    "    position=0.273,\n",
+    "    sweep_length=0.066,\n",
+    ")\n",
+    "drogue = prometheus.add_parachute(\n",
+    "    \"Drogue\",\n",
+    "    cd_s=1.6 * np.pi * 0.3048**2,  # Cd = 1.6, D_chute = 24 in\n",
+    "    trigger=\"apogee\",\n",
+    ")\n",
+    "main = prometheus.add_parachute(\n",
+    "    \"Main\",\n",
+    "    cd_s=2.2 * np.pi * 0.9144**2,  # Cd = 2.2, D_chute = 72 in\n",
+    "    trigger=457.2,  # 1500 ft\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Inertia Details\n",
+      "\n",
+      "Rocket Mass: 13.930 kg (without motor)\n",
+      "Rocket Dry Mass: 16.911 kg (with unloaded motor)\n",
+      "Rocket Loaded Mass: 20.648 kg (with loaded motor)\n",
+      "Rocket Inertia (with unloaded motor) 11: 6.008 kg*m2\n",
+      "Rocket Inertia (with unloaded motor) 22: 6.008 kg*m2\n",
+      "Rocket Inertia (with unloaded motor) 33: 0.050 kg*m2\n",
+      "Rocket Inertia (with unloaded motor) 12: 0.000 kg*m2\n",
+      "Rocket Inertia (with unloaded motor) 13: 0.000 kg*m2\n",
+      "Rocket Inertia (with unloaded motor) 23: 0.000 kg*m2\n",
+      "\n",
+      "Geometrical Parameters\n",
+      "\n",
+      "Rocket Maximum Radius: 0.06985 m\n",
+      "Rocket Frontal Area: 0.015328 m2\n",
+      "\n",
+      "Rocket Distances\n",
+      "Rocket Center of Dry Mass - Center of Mass without Motor: 0.120 m\n",
+      "Rocket Center of Dry Mass - Nozzle Exit: 0.835 m\n",
+      "Rocket Center of Dry Mass - Center of Propellant Mass: 0.561 m\n",
+      "Rocket Center of Mass - Rocket Loaded Center of Mass: 0.102 m\n",
+      "\n",
+      "\n",
+      "Aerodynamics Lift Coefficient Derivatives\n",
+      "\n",
+      "Nose Cone Lift Coefficient Derivative: 2.000/rad\n",
+      "Fins Lift Coefficient Derivative: 6.406/rad\n",
+      "\n",
+      "Center of Pressure\n",
+      "\n",
+      "Nose Cone Center of Pressure position: 1.858 m\n",
+      "Fins Center of Pressure position: 0.191 m\n",
+      "\n",
+      "Stability\n",
+      "\n",
+      "Center of Mass position (time=0): 0.733 m\n",
+      "Center of Pressure position (time=0): 0.588 m\n",
+      "Initial Static Margin (mach=0, time=0): 1.042 c\n",
+      "Final Static Margin (mach=0, time=burn_out): 1.768 c\n",
+      "Rocket Center of Mass (time=0) - Center of Pressure (mach=0): 0.146 m\n",
+      "\n",
+      "\n",
+      "Parachute Details\n",
+      "\n",
+      "Parachute Drogue with a cd_s of 0.4670 m2\n",
+      "Ejection signal trigger: At Apogee\n",
+      "Ejection system refresh rate: 100.000 Hz\n",
+      "Time between ejection signal is triggered and the parachute is fully opened: 0.0 s\n",
+      "\n",
+      "\n",
+      "Parachute Details\n",
+      "\n",
+      "Parachute Main with a cd_s of 5.7789 m2\n",
+      "Ejection signal trigger: 457.2 m (AGL)\n",
+      "Ejection system refresh rate: 100.000 Hz\n",
+      "Time between ejection signal is triggered and the parachute is fully opened: 0.0 s\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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2bdqwZs0arX+H6myrJlxcXHj//ff54IMPmDZtGsXFxezYsYPOnTuzZcsW3njjDRYsWICtrS3Dhg2jS5cuWtO6AowdO5YzZ86wefNmVq1ahYeHR6WNhuoeb0IIIURt6aWmpsqZb0II1cTGxhIWFsbcuXOZOnWqrssRQgghRDXIOQ1CCCGEEEKIKkmjQQghhBBCCFElaTQIIYQQQgghqiTnNAghhBBCCCGqJD0NQgghhBBCiCrJlKu3odFoSEhIwNLSsk6upCuEEELc7UpKSsjOzsbNzQ19ffl+UQjRABsN69evZ/ny5SQmJhIcHMzixYtp27btbZ+3bds2xo0bp8xnX10JCQmEhITcSclCCCFEg/Tvv//StGlTXZchhLgLNKhGw/bt25k9ezbvv/8+bdu2ZfXq1QwdOpTjx4/j5ORU6fNiY2N58803eeCBB2q8T0tLS6D0jdPKyqrWtd8qIiKCFi1a1Mm2RNUka/VI1uqRrNXVGPPOysoiJCRE+RsohBANqtGwcuVKRo4cyVNPPQWUXsV1z549bNq0ienTp1f4nOLiYsaPH88rr7zC0aNHycjIqNE+y4YkWVlZlbuibW1ZWFjU2bZE1SRr9UjW6pGs1dWY85ZhuUKIMg1moGJhYSGnT5+ma9euyjJ9fX26du3KiRMnKn1eeHg4Tk5O/O9//6vWfgoKCsjMzFRuWVlZd1z7f7m7u9f5NkXFJGv1SNbqkazVJXkLIUQD6mlISUmhuLi43DAkJycnLl68WOFzjh49yhdffMGhQ4eqvZ+lS5cSHh5ebnlERAQWFhYEBgYSHR1Nfn4+FhYWNGnShMjISADc3NwoKSnh+vXrADRv3py4uDhyc3MxMzPD09OTCxcuUFBQgKenJ/r6+iQkJADg7+9PQkIC2dnZmJiY4OvrS0REhPIajY2NuXbtGgDNmjUjMTGRrKwsjI2N8ff35+zZswA4ODhgbm5OXFwcAD4+PqSmppKRkYGhoSGBgYGcPXuWkpIS7O3tsbKyIiYmBgAvLy8yMzNJS0tDX1+foKAgIiIiKC4uxtbWFjs7O65cuQKAh4cHubm5pKSkANCyZUsuXLjAzZs3sba2xsnJiaioKKD0D25BQQFJSUkABAUFERUVRUFBAZaWlri6unLp0iUAmjRpQlFREYmJiQAEBgYSExNDXl4e5ubmuLu7K//erq6uAEreAQEBXL16Vcnby8uLqKgoTExMcHZ2xtDQkPj4eAD8/Py4fv26knezZs04d+6ckreJiQlXr15V8k5KSiIzMxMjIyOaN2/OmTNnKs07LS2N9PR0DAwMaNGiBefOnUOj0WBnZ4e1tbVW3llZWaSmpqKnp0dwcDDnz5+nqKgIGxsb7O3tK807ODiYyMhICgsLsbKywtnZWcm7adOmFBYWKnm3aNGCy5cvK3m7ublpHbMajYYbN24ox2xsbKySt4eHBxcuXFDy1tPT0zpm4+PjycnJwdTUFAsLCyWzivK+ceOGcsz6+fkpeTs6OmJqaqo819fXl5SUlEqPWUtLS2JjYwHw9vYmPT1dK+9bj1lbW1uio6MB8PT0JDs7u9K8HRwcuHz5snLM5ufnk5ycrByzly5dUvJ2cXGp8pi90/cIABcXl0rfIzQaDVZWVvIeUQfvEefPn6/0mC17jyguLsba2rpRvUeUHVtCCFGmwVynISEhgeDgYH7++WfatWunLH/rrbf4/fff+fXXX7XWz8rK4sEHH+Tdd9+lR48eAEyePJmMjIwqT4QuKCigoKBAazshISFER0fXWff0mTNnaNmyZZ1sS1RNslaPZK0eyVpdjTHvzMxMvL296/RvnxCiYWswPQ0ODg4YGBgo34yUSUpKwsXFpdz60dHRxMbG8uSTTyrLNBoNUPot0fHjx/Hx8Sn3PBMTE0xMTOq4eiGEEEJUl0ajoaioSNdlCHFP09PTw9DQsNrnLjWYRoOxsTGhoaEcOnSIvn37AqVvKgcPHmTcuHHl1vf39+fw4cNayxYsWEB2djYLFizQ6RRyQUFBOtt3YyNZq0eyVo9krS7JWz0lJSWkp6eTm5srJ2ELoZKy4Zm302AaDQCTJk1i8uTJhIWF0aZNG1avXk1ubq7SmzBx4kTc3Nx48803MTU1LfdGb2NjA+j+D0BUVBT+/v46raGxkKzVI1mrR7JWl+StnvT0dPLy8nB2dsbMzEwaDkLUo5KSEhISEkhLS8PR0fG2/98aVKNh8ODBpKSksHDhQhITE2nZsiXffPMNzs7OAFy9erVBXLny1nMmRP2SrNUjWatHslaX5K0OjUZDbm4uzs7O2Nvb67ocIRoFR0dH4uPj0Wg0GBgYVLlug2o0AIwbN67C4UgAO3furPK5K1asqI+SakwulqMeyVo9krV6JGt1Sd7qKCoqQk9PDzMzM12XIkSjYWxsjJ6eHsXFxbdtNNz9X8vfg8qmART1T7JWj2StHslaXZK3umRIkhB3J2k06EDZfOOi/knW6pGs1SNZq0vyFkKIBjg8SQghhBCNS2xsrHKxxfrm6OiIp6enKvsSoiGRRoMONGnSRNclNBqStXoka/VI1uqSvHUrNjaW4OBg8vPzVdmfqakpZ8+ebVANh+joaPz9/Tlx4gRhYWG6Lkfco2R4kg7IBWvUI1mrR7JWj2StLslbt5KTk1VrMADk5+fXuFdjzJgxGBkZER4errX8+++/x8jIqC7LE0JnpNGgA4mJibouodGQrNUjWatHslaX5C2qw9TUlHfffZe0tDRdlyJEvZBGgxBCCCHEHerevTuurq4sXry40nW2b99OaGgoFhYW+Pn5sXTpUuWxgwcPYmRkVO42ZswYAPz8/Cp8vDJnzpyhX79+2Nra0rRpU0aNGqXaeSHi3iSNBh0IDAzUdQmNhmStHslaPZK1uiRvUR0GBgbMnz+fFStWcPXq1XKPnzx5khEjRjB8+HBOnTrFG2+8wVtvvcXGjRsBeOCBB4iLi1Nue/bswdTUlAcffBCAP/74Q3ksOjqa9u3b07lz5wprSU9Pp2fPnoSFhXH06FF++OEHEhMTGTFiRP0FIO550mjQgZiYGF2X0GhI1uqRrNUjWatL8hbVNXDgQEJDQ5k7d265xz744AMefvhhXn/9dQICAhg1ahSTJk1iyZIlQOlFtlxdXXF1dcXIyIgJEybwzDPPMHr0aACcnJyUx9977z2uX7/O119/XWEdK1euJCwsjLfffpvAwEBat27NunXrOHDgABcvXqy/AMQ9TRoNOpCXl6frEhoNyVo9krV6JGt1Sd6iJhYuXMjnn39ORESE1vLz58/TsWNHrWUdO3YkMjKS4uJiZdnNmzcZPnw4np6eWsOXyqxbt45PPvmE7du34+TkVGEN//zzDwcOHMDW1la5tWzZEoDLly/f6UsUjZRMuaoD5ubmui6h0ZCs1SNZq0eyVpfkLWriwQcfpGfPnsyePZuRI0fW+PmTJ0/m6tWrHDlyBEND7Y9pBw4cYPr06XzxxRe0atWq0m1kZ2fTr18/FixYUO4xNze3GtckBEijQSfc3d11XUKjIVmrR7JWj2StLslb1NQ777zDfffdR0BAgLIsMDCQI0eOaK135MgRAgICMDAwAGDp0qVs3bqVQ4cO4eDgoLXupUuXePzxx3nllVcYNGhQlftv3bo13377Ld7e3uUaHkLUlgxP0gEZT6geyVo9krV6JGt1Sd6ipkJCQhgxYgQfffSRsmzGjBns27ePd955h4sXL/LZZ5+xcuVKZsyYAcDevXt59dVXWbRoEY6Ojly/fp3r16+TkZFBXl4egwYNIiwsjGeffVZ57Pr16xXuf+LEiaSmpvL0009z4sQJoqKi+OWXXxg7dqzWUCghakIaDUIIIYS4azk6OmJqaqra/kxNTXF0dLzj7cyZMweNRqPcb9OmDVu2bOHrr78mLCyMuXPnMmfOHEaNGgXA77//TnFxMZMnT8bDw0O5zZgxgxs3bnD+/Hn27duHp6en1uMVadKkCQcPHqS4uJg+ffrQunVrXnjhBWxtbdHXl49+onb0UlNTS3RdxN0sMzMTb29voqOjsba2rpNtJicn18kbkrg9yVo9krV6JGt1Nca86+Nv3+0UFhaSnJyMl5dXuUZCbGysatcYcHR0xNPTU5V9CaFr+fn5xMTE4OjoiLGxcZXrykA3IYQQQtzVPD095YO8EDomfVQ6UNkYRFH3JGv1SNbqkazVJXkLIYQ0GoQQQgghhBC3UevhSTdv3uTGjRvk5eXh6OiInZ1dXdZ1T7t1CjZRvyRr9UjW6pGs1SV5CyFEDXsasrKy+Pjjj+nXrx9eXl6EhYXRoUMH/P39adWqFc8//zx//fVXfdV6z7h69aquS2g0JGv1SNbqkazVJXkLIUQNehpWrFjBkiVL8PHxoVevXsyYMQM3NzdMTU1JS0sjIiKCP/74gyFDhtC2bVsWL15Ms2bN6rP2Bis3N1fXJTQakrV6JGv1SNbqkryFEKIGjYZTp07xww8/0KJFiwofb9u2LU8//TQFBQVs3ryZP/74QxoNlTAzM9N1CY2GZK0eyVo9krW6JG8hhKhBo2H9+vXVWs/ExITRo0fXuqDGwMvLS9clNBqStXoka/VI1uqSvIUQQmZP0onz58/ruoRGQ7JWj2StHslaXZK3EELUcvak/Px81q5dy+HDh0lOTta6TDrAgQMH6qI2IYQQQghxFzl//jxjx47l9OnTNG/enJMnT+q6JKGSWvU0TJs2jeXLl+Ph4UHPnj159NFHtW6ias7OzrouodGQrNUjWatHslaX5C1u5/r16zz//PMEBARgYWGBj48PAwcOZN++fXW6n+7duzNz5sw63WZNzZs3DwsLC86ePcsvv/xS4TpjxozByMiISZMmlXts6tSpGBkZMWbMmPouVdSxWvU07N69m6+++ooOHTrUdT23tX79epYvX05iYiLBwcEsXryYtm3bVrjuxo0b+eqrr4iIiAAgLCyM2bNnV7q+WgwNa315DFFDkrV6JGv1SNbqkrxFVaKjo+natSu2trYsWrSIli1bcvPmTX755RemTZvGmTNndF1iOYWFhRgbG9fquVFRUfTp0+e25/p4eHjw9ddf8/777yuTCeTn5/Pll1/i6elZq30L3apVT4ObmxtWVlZ1Xcttbd++ndmzZzNr1iz2799Py5YtGTp0KElJSRWu//vvvzNkyBB27NjB7t27adKkCUOGDCE+Pl7lyrXpev+NiWStHslaPZK1uiTvhuevK1lsPZbIX1ey6n1fU6dORU9PjyNHjjB48GACAgIIDg5mxowZHD58WFkvPT2d8ePH4+bmhr29PT169OD06dPK4/PmzaNt27Z88cUX+Pn54eDgwFNPPUVWVulrGDNmDIcOHWL58uUYGRlhZGREdHQ0AGfOnKFfv37Y2trStGlTRo0aRXJysrLt7t27M23aNGbOnImrqyt9+vSp8LVoNBrefvttvL29sbCwoG3btuzevVt53MjIiL/++ou3334bIyMj5s2bV2kurVu3xt3dnW+//VZZ9u233+Lh4UFYWJjWurt376Zr1644Ojri4uLCgAEDiIqKUh4vLCxk2rRpeHh4YGlpSbNmzVi8eDEAJSUlzJs3D19fXywsLPD09GT69OmV1iVqr1Zfn8yfP585c+awZMkSPDw86rqmSq1cuZKRI0fy1FNPAbBkyRL27NnDpk2bKjxA1q5dq3X/ww8/ZOfOnRw6dIgnnniiwn0UFBRQUFCg3C/7z6pLKSkp/P777/W6D319fR5++GHMzc3rdT9CCCFEfXrn22hW7Lmm3J/coymvD/Kul32lpqaye/du5s+fj4WFRbnHbW1tld+feOIJzMzM2LlzJzY2Nqxbt45evXpx7tw57O3tAbh8+TI7duzgu+++Iz09nREjRhAeHs78+fNZunQpkZGRBAcHM2fOHACcnJxIT0+nZ8+ejBkzhvfee4+8vDxee+01RowYwZ49e5T9f/7550yYMIGDBw9W+no+/PBDli5dysqVKwkLC+PTTz9l0KBBnD59Gn9/f+Li4ujduzc9e/Zk5syZWFpaVpnPM888w8aNG3nyyScB+PTTTxk1ahSHDh3SWi8nJ4fp06cTEhJCdnY2c+fOZejQoZw8eRJ9fX0++ugjfvjhB7Zs2YKHhwdxcXHKRRe3b9/OsmXL2LRpE0FBQVy/fp1//vmnyrpE7dSq0dC6dWsKCgpo3bo15ubm5bpuL1++XCfF3aqwsJDTp08zY8YMZZm+vj5du3blxIkT1dpGbm4uRUVF2NnZVbrO0qVLCQ8PL7c8IiICCwsLAgMDiY6OJj8/HwsLC5o0aUJkZCRQ2gNTUlLC9evXAWjevDlxcXHk5uZiZmaGp6cnFy5cQKPRkJSUhL6+PgkJCQD4+/uTkJBAdnY2JiYm+Pr6EhERgUajYeLEicoQq/rUp08fFi9eTFpaGvr6+gQFBREREUFxcTG2trbY2dlx5coVoLTbMTc3l5SUFABatmzJhQsXuHnzJtbW1jg5OSnfEri7u1NQUKD0CAUFBREVFUVBQQGWlpa4urpy6dIlAJo0aUJRURGJiYkABAYGEhMTQ15eHubm5ri7u3Px4kUAXF1dAZS8AwICuHr1qpK3l5cXGo2GM2fO4OzsjKGhofKNoZ+fH9evX1fybtasGefOnQNK34RNTEyUN6RmzZqRlJREZmYmRkZGNG/eXOludnBwwNzcnLi4OAB8fHxIS0sjPT0dAwMDWrRowblz59BoNNjZ2WFtbU1MTAxQOo1jVlYWqamp6OnpERwczPnz5ykqKsLGxgZ7e/tK8w4ODiYyMpLCwkKsrKxwdnZW8m7atCmFhYVK3i1atODy5ctK3m5ublrHrEaj4caNG0DpMRsbG6vk7eHhwYULF5S89fT0tI7Z+Ph4cnJyMDU1xcfHR8mlorxv3LhBVlYWxsbG+Pn5KXk7Ojpiamqq5O3r60tKSgoZGRkYGhoSGBjI2bNnKSkpwd7eHktLS2JjYwHw9vYmPT1dK+9bj1lbW1vlmzhPT0+ys7MrzdvBwUF573J3dyc/P1/5pi4oKIhLly4pebu4uFR5zN7pewSAi4tLpe8RhoaGFBcXK+8LTk5OGBsbc+3aNeWYTUxMVPL29/fn7NmzlR6zqampleZtZWWldcxmZmbeU+8RZTMjVfUeYWhoiEajaVTvEWr8zakPf13J0mowAKzYc41Hwxxo41P3IyQuXbpESUkJzZs3r3K9w4cPc+LECeLj4zExMQEgPDycHTt2sG3bNsaNGweUftO/YcMGZTTHU089xb59+5g/fz42NjYYGxtjbm6uHNuA8gH/7bffVpatW7cOHx8fLl68SEBAAFB6TC9atKjKOpcuXcpLL73E448/DsDChQs5cOAAH374IcuXL8fV1RUDAwPl/+XtPPXUU8yePVs5po8cOcKmTZvKNRoGDx6sdX/dunW4ublx7tw5WrZsSWxsLH5+fnTq1Ak9PT2toVGxsbG4urrSvXt3jIyM8PT0pF27dretTdScXmpqaklNnzRo0CCuXr3K008/jZOTE3p6elqPjxgxos4KLJOQkEBwcDA///yz1sHw1ltv8fvvv/Prr7/edhsvvvgi+/bt48iRI5iamla4TkU9DSEhIURHR2NtbX3nL4TS8Y/e3t7VWnfnzp2MGjWKrVu30qZNmzrZf0W2bdvGSy+9xG+//UZwcHC97UdtNcla3BnJWj2StboaY96ZmZl4e3vX6d++2yksLCQ5ORkvL69K/0bfztZjiUzbGFlu+Yej/Bnavu5PaD927BidO3fmm2++YeDAgZWut3LlSmbMmFHuQoF5eXnMnDmThQsXMm/ePLZt26Y1ZOmDDz5g5cqVSkO4e/fuhIaGsmTJEmWdJ554gh07dpQ7RyEnJ4edO3fSu3dvunfvjp+fH2vWrKm0xszMTBwcHNi7dy9dunRRlr/wwgv8888/Sq9F27ZtGTBgAG+++Wal2xozZgwZGRls27aN4cOHExISQklJCWfPnuWrr75iyJAh2NjY8PHHHwMQGRnJ3LlzOX78uDIrZ05ODjt27ODRRx/lr7/+4tFHH8XBwYGePXvSt29fevToAUBcXBxdu3alpKREmZynX79+ci5SNeXn5xMTE4Ojo+Ntz3OpVaLHjx9n9+7dtGzZslYF6sIHH3zA9u3b2blzZ5VvRiYmJsq3APUlOzu7WutpNBoWLVpEt27dePjhh+u1ppEjR7JixQoWL17MZ599Vq/7UlN1sxZ3TrJWj2StLsm74fB1rvjq3ZUtv1P+/v7o6ekpPYSVycnJwc3NrcIvOG8dwvTfD7p6enrlprX/r+zsbPr168eCBQvKPebm5qb8XtHwKTU888wzPP/880Dp8KeKDBo0CE9PT1avXq30gIeFhVFYWAhAmzZtiIyM5Oeff2bv3r2MGDGC7t2789VXX+Hh4cHZs2fZu3cvv/76K1OnTuX9999n3759GBkZqfY6G4NanQjt7+9PXl5eXddSJQcHBwwMDMqd9JyUlISLi0uVz12+fDkffPAB27Ztuyu+Ra9uo+T7778nIiKCV155pZ4rKj256aWXXuKHH37Q+pajoavvBqD4f5K1eiRrdUneDUcbHysm92iqtWxKz6b1MjQJwN7enp49e7Jq1SpycnLKPZ6eng6UDuu+fv06hoaG+Pn5ad0cHR2rvT9jY2OKi4u1lrVu3Zpz587h7e1dbts1aShYW1vTpEkTjhw5orX8yJEjtGjRotrb+a9evXpRWFjIzZs36dmzZ7nHU1JSuHDhAq+99hoPP/wwLVq0IC0trcL6hg8fzpo1a9i8eTPbt28nNTUVADMzM/r168cHH3zAr7/+ytGjR/n3339rXbOoWK0aDW+++SZvvPEGhw8fJjU1lczMTK1bfTA2NiY0NFRrHJxGo+HgwYPcf//9lT7vww8/5L333uObb76hdevW9VJbTTVr1uy26xQXF7N48WIeeeQR1cbmDRs2TGtGgntBdbIWdUOyVo9krS7Ju2F5fZA3P7zUig9H+fPDS614baB3ve7vww8/pLi4mI4dO7J9+3YiIyOJiIhg+fLlPPjgg0DpsKIOHTowZMgQ9uzZQ3R0NEeOHOGNN97gzz//rPa+vLy8OH78ONHR0cownokTJ5KamsrTTz/NiRMniIqK4pdffmHs2LHlGhi3M3PmTN59912+/vpr5YP86dOnmTp1ao22cysDAwP+/fdf/vnnHwwMDMo9bmdnh4ODA+vWrePSpUvs37+fl156SWudpUuX8uWXX3L+/HkuXrzI1q1bcXV1xdbWlo0bN/Lxxx9z5swZLl++zObNm5VzlkTdqtXwpGHDhgGUG79XUlKCnp6e1jRfdWnSpElMnjyZsLAw2rRpw+rVq8nNzVXOyp84cSJubm7KOLtly5axcOFC1q5di6enp3Kyp4WFxW3P+K9PZSf2VOXbb7/l4sWLrFy5UqWqSrtFZ82axYQJE/jrr7/q9RwKtVQna1E3JGv1SNbqkrwbnjY+VvXWu/Bfvr6+HD9+nIULFzJr1iwSEhJwcnKiTZs2fPTRR0DpMKOdO3fyxhtv8Oyzz5KUlISrqyudO3e+7WiJW82cOZMxY8bQqlUr8vLyiIyMxNvbm4MHD/Laa6/Rp08fCgoK8PLyomfPnujr1+y74alTp5KZmcmsWbNITEykRYsWfPvtt/j7+9doO/9V1Xkx+vr6bNq0iRkzZhAWFkZAQAAffPAB3bt3V9axsrLivffe49KlSxgYGHDfffexY8cO9PX1sbW1JTw8nJdeeoni4mJatmzJd999h4ODwx3VLMqr1YnQt5v+s1OnTrUu6HbWrVunXNytZcuWLFq0iPvuuw+A/v374+npyYoVKwAIDQ1VZqy41axZs6o95Kc+TgY7c+ZMlX+AioqK6NixI35+fmzevLlO9lldZd+WeHl58fXXX6u67/pwu6xF3ZGs1SNZq6sx5t1QT4QWQtRMvZ8IXZ+NgtsZN26cMjXZf+3cuVPr/t06Nt/JyanKx7du3cqlS5dYt26dShX9PwMDA15++WWeffZZjh8/3uCnLbtd1qLuSNbqkazVJXkLIUQNzmkom4+6uuQKmpWr6qS6mzdv8u6779K3b19CQ0NVrOr/DRw4kMDAwNvO59wQyAmM6pGs1SNZq0vyFkKIGjQaunfvzowZM/jrr78qXSczM5ONGzfSsWPHct/6i/9XVQPsq6++4sqVK7z88ssqVqRNX1+fV155hQMHDvDHH3/orI66UNPGrqg9yVo9krW6JG8hhKjB8KQ//viD999/n8GDB2NqakpoaCiurq6YmpqSnp7OhQsXOH/+PK1atWLu3LnKRTdE9RUWFvLee+/x2GOP6Xz8bL9+/ZRzRr7//nud1iKEEEIIIXSr2j0N9vb2vPPOO0RERLB48WJ8fX1JTU1VLks/dOhQ9u3bxy+//CINhtuobPq+zZs3ExcXx6xZs1SuqLyy3obffvuN3377Tdfl1JpMlageyVo9krW6JG8hhKjFidBmZmYMGDCAAQMG1Ec9jUJSUhKenp5aywoKCnj//fcZNGgQQUFBOqpM26OPPkpoaCiLFi2ic+fO6Onp6bqkGqsoa1E/JGv1SNbqkryFEKKWF3cTd6aiC+B98cUXJCQk3BW9DGX09PR49dVX+eOPPzh48KCuy6mV+rrYoChPslaPZK0uyVsIIaTRoBNGRkZa9/Pz81myZAlDhw4lICBAR1VVrEePHrRp04aFCxdSUlLjS3ro3H+zFvVHslaPZK0uyVsIIaTRoBPNmzfXur9x40YSExPLXTb9blDW23DixAn27t2r63Jq7L9Zi/ojWatHslaX5C2EENJo0IkzZ84ov+fm5vLBBx8wfPjwu/Zku4cffph27dqxaNGiBtfbcGvWon5J1uqRrNUleYu7ycaNG3F0dNR1GQ1Gbm4uw4cPx97eHiMjI9LT03VdUoMljQYd++STT0hOTr4rexnKlPU2/PXXX/zyyy+6LkcIIYS4ayQlJTF58mR8fX2xsLDA3d2dPn368PvvvyvrGBkZ1Wr6cj8/P5YtW6a1bPjw4Zw7d+6Oai6b4r1NmzZYW1vj6upKly5d+PTTT7l58+YdbftW8+bNo23btnW2vdr47LPPOHz4MIcOHSIuLg4bG5ty62zcuBEjIyOMjIwwNjbG29ubsWPHkpiYqIOK7141nj0JYMuWLTg4ONCzZ08A3nrrLTZu3Ejz5s1Zv349Hh4edVrkvcbBwQGAnJwcli1bxpNPPom3t7dui7qNLl260LFjRxYuXEjPnj0bzExKZVmL+idZq0eyVpfkLaoyfPhwCgsL+fjjj/Hx8eHGjRvs37+f1NTUetmfmZkZZmZmtX5+YWEhffr04Z9//mHOnDl07NgRa2trjh07xpIlSwgLCyMsLKzuCq4DhYWFGBsb1+q5ly9fJjAw8LbXv7K2tubs2bNoNBr++ecfnn32WRISEvjxxx/LrVtcXIyenh76+nfPd+9q1FSrLS9duhRTU1MAjh8/zoYNG5gzZw4ODg68/vrrdVrgvcjc3ByADRs2kJGRwQsvvKDjim6vrLfhn3/+qfA/0N2qLGtR/yRr9UjW6pK8G6Bjx9D74gs4dqxed5Oens7hw4dZuHAh3bp1w8vLi3bt2vHyyy/Tv39/oLS3AEqvZ2VkZKTcj4qKYvDgwTRt2hRbW1s6dOigde5g9+7diYmJ4cUXX1S+BYeKhyf98MMPdOjQAUtLS1xdXRk6dGilNX/44Yf89ttv7N69m0mTJhEWFoavry8jRozgyJEj+Pv7A6DRaFi8eDH+/v5YWVnRpk0btm3bpmzn4MGDGBkZsW/fPtq3b4+1tTUPPvggFy5cUOqcP38+//zzj1L/xo0bldzGjx+Pm5sb9vb29OjRg9OnTyvbLuuh2LBhA/7+/lhaWlb6erZv305oaCgWFhb4+fmxdOlSrQyXLl3Kb7/9hpGREd27d690O3p6eri6utKkSRN69+7NlClT2Lt3L3l5eUrmO3fupFWrVlhYWBAbG0tBQQGzZs3Cy8sLGxsbOnbsqDXbZExMDAMHDsTJyQkbGxtCQ0P56aefAEhLS+N///sfbm5uWFlZ0aJFCz799FOtbG8dSvX3339jZGREdHS0km9taroTteppuHbtGr6+vgD8+OOP9O/fn2eeeYb27dvz2GOP1Ulh97K4uDj09fX58MMPefrppxvM/N+dOnWiS5cuLF68mEcfffSuamFXprKuSFH3JGv1SNbqkrwbFv1XX0X/vfeU+5oXX0SzcGG97MvS0hJLS0u+//572rdvj4mJSbl1/vjjD5o0acL69evp1asXBgYGAGRnZ9O7d2/mzZuHiYkJX3zxBQMHDuTs2bN4enryzTff0LZtW5599lnGjh1baQ0//vgjQ4cO5dVXX+WTTz6hsLCQn3/+udL1N2/eTPfu3WndunW5x25tnCxevJjNmzezYsUK/Pz8+O233xg1ahROTk506dJFec4bb7zBu+++i6OjI5MnT2bcuHEcOnSI4cOHc/bsWX755RelnrL/R0888QRmZmbs3LkTGxsb1q1bR69evTh37hz29vZAaaPq22+/5euvv1Yy+6+TJ08yYsQI3nzzTYYNG8Yff/zB1KlTsbe3Z9SoUXzzzTe89tprnD17lm+++aZGvRWmpqZoNBqKioqA0nMj3n33XVavXo2DgwPOzs5MmzaNiIgINm3ahJubG99//z19+/bl1KlT+Pv7M23aNAoLC9m3bx8WFhZEREQoDaC33nqLiIgIdu7ciaOjI1FRUeTl5VW7vtrWdCdq1WiwsLAgNTUVd3d39u/fz6RJk4DSgPPz8++ooMZi/fr1ZGdnM2PGDF2XUiOvvPIKffr04YcffpAGohBCiLvLsWNaDQYA/ffeQzNwILRvX+e7MzQ0ZMOGDTz33HOsXbuW1q1b06VLF4YPH06rVq0AcHJyAsDW1hZXV1fluaGhoYSGhir3586dy/fff8/OnTuZPHky9vb2GBgYKL0HlVm4cCHDhw/nrbfe0tp2ZS5dukTXrl2rfF0FBQUsWrSIn3/+mQceeAAAX19ffv/9d9atW6fVaJg/f75yf9asWTz22GPk5+djZmaGpaUlBgYGWvUfPnyYEydOEB8frzSywsPD2bFjB9u2bWPcuHFA6ZCkTz75RMmvIh988AEPP/ywMsolICCAiIgIlixZwqhRo7C3t8fc3BxjY+MqM/yvyMhI1q1bR9u2bbGysgLg5s2bLF++XMk2NjaWjRs3cvnyZZo0aQLAzJkz2b17Nxs3buTtt98mNjaWwYMHExISomRYJi4ujrCwMO677z6AWg1Tr01Nd6JWjYZu3brx/PPPExISQlRUFD169ADg/Pnzcj5DNTg6OrJ8+XJGjRqFu7u7rsupkQ4dOvDQQw+xaNEi+vXrd9f3Nvj4+Oi6hEZDslaPZK0uybvh0IuMrHR5ST00GgAGDx5Mnz59OHz4MMeOHePnn3/mvffeY82aNYwaNarS52VnZzNv3jx++uknEhISKCoqIi8vj7i4uBrt//Tp01X2RPxXdWZBvHTpErm5uTz66KNaywsLC8ud71D2gRhQPpgnJiZWOorin3/+ITs7GxcXF63leXl5XL58Wbnv5eVVZYMBSj93/vcLzI4dO/Lhhx9SXFxcaQ9FRTIyMrC1tUWj0ZCfn0+nTp1Ys2aN8rixsbHSEITSWdWKi4sJCgrS2k5BQYFyHtSUKVOYMmUKe/bsoXv37gwaNEjZxoQJExg+fDinTp2iR48ePPbYY3Ts2LHa9da2pjtRq0bDu+++yzvvvMO1a9f49NNPla6kv//+myFDhtxxUfey3NxcZs+eTXZ2Nl27dtUaw9dQDBkyhClTpvDKK68wZMgQ5fyWu9GNGzfKvTGJ+iFZ169du3Zx+PBh5dsjGxsbZaYPY2NjjIyMMDExwcTEBFNTU0xNTTExMcHc3BxTU1PMzMwwNzdXbhYWFpibm2NoWKs/A41KWloaFhYWui5DVENJJcMvKlteV0xNTXnkkUd45JFHeP311xk/fjzz5s2rstEwa9Ys9u7dy+LFi2nWrBlmZmY8/vjjFBYW1mjfNT0p2t/fXznvoDLZ2dkA7NixQ3nPKfPfIVi3XvywbJIUjUZT6bZzcnJwc3Pj119/LfeYra2t8rva5xJZWVlx/Phx9PX1cXNzK5ermZmZ1iQw2dnZGBgYcOzYsXKNk7IhSGPHjqVnz578+OOP/PrrryxevJjw8HCmTJlC7969iYqK4qeffuLXX3+lV69eTJw4kfDwcOUL2VsbeBXNalWbmu5Erf5a2NjYEB4eXm75q6++escF3esiIyPZvn07AE8//bSOq7kz69evZ/369bouQ4hGxcfHB1NTU4yNjbl58yY3b96koKCAwsJCCgoKKCgoID8/v8o/2rcyMTHBwsICCwsLLC0tlZ+WlpZYWVlp3aytrcv9tLGxwcbGBgsLiwYzq1pNpaenN7he4UarfXs0L76ofU7DSy/Vy9CkqrRo0YIdO3Yo942MjCguLtZa58iRI4wcOZKBAwcCpR/4YmJitNYxNja+7f/lkJAQ9u3bxzPPPFOt2kaMGMHs2bM5depUufMabt68SWFhIUFBQZiYmBAbG6s1FKmmjI2Ny73u1q1bc/36dQwNDe945sjAwECOHDmitezIkSMEBATUqJcBQF9fXzlJvTrCwsIoLi4mKSmJzp07V7qeh4cHEyZMYMKECbz++uts2LCBKVOmAKVD10aOHMnIkSNZu3Ytr7zyCuHh4cqJ7gkJCdjZ2QFU60vm6tZUW7VqNPz3H+i/atq90pj4+/uzatUq9PX18fT0vKu/pa9Kfn4+sbGxd/1ruHLligwtUIlkXb8uXrzIhAkTWLlyJdbW1rRo0aLSdUtKSrh58yb5+fnk5+eTl5dHbm4ueXl5yu85OTnKrex+VlYW2dnZyi0xMZGsrCytW2UfYAwMDJQGhK2tLdbW1tja2mJra4udnZ3W7/+93cn0kWqo6YcPoVuahQvRDBxYOiTJ379eGwwpKSk88cQTPPPMM4SEhGBlZcXJkyd5//33ldmToHS8+r59++jYsSMmJibY2dnh7+/Pt99+S9++fdHT02POnDnl/n95eXnx22+/MXz4cExMTCq8qNsbb7xBz549adasGcOHD6eoqIiff/650us/TZs2jR9//JFevXoxZ84cOnXqpNT97rvvsnbtWsLCwpg5cyYvvvgiGo2GTp06kZGRwZEjR7C2tmbkyJHVysfLy4vo6Gj+/vtv3N3dsbKyonv37nTo0IEhQ4awaNEi/P39iY+P56effmLAgAHKGP/qmDFjBg888ADvvPMOw4YN4+jRo6xcuZLly5dXexu1FRAQwIgRIxg9ejTh4eGEhYWRlJTE/v37CQkJoU+fPsycOZPevXvj7+9PWloaBw4cUN6758yZQ5s2bQgKCqKgoIAff/yRwMBAoHTGLQ8PD+bPn8+8efOIjIzkgw8+qJOa7kStGg23/kcoc+s3TMnJybWv6B5nbm7O448/rusy6kR7lb+5qY2qTgYTdUuyVoepqWmVDQYofT8uG7ZkbW1dZ/suKSkhJyeHzMxM5ZaRkaH8np6eTkZGhtbPmJgY0tPTSU1NJTMzs8LtmpubY2dnh729vXJzcHDA3t4eR0dH5aeDg4PyU81hVbfLW9yF2revt3MYbmVpaUm7du1YtmwZly9f5ubNm3h4eDB27FheeeUVZb3w8HBeeuklNmzYQNOmTbl06RLvvvsu48aNo0uXLjg6OvLiiy+W+z/y1ltvMWnSJJo3b05BQUGFQ1S6du3Kl19+yTvvvEN4eLgy9WllTExM+Pnnn1m2bBnr1q3j5ZdfxtzcnMDAQKZMmaJcz2Du3Lk4OjoSHh7O5cuXsbW1pXXr1lqv63YGDx7Md999R48ePUhPT2f9+vWMGjWKnTt38sYbb/Dss8+SlJSEq6srnTt3rvEQ1zZt2rBlyxbmzp3LO++8g5ubG3PmzKlyWFhd2rBhAwsWLGDWrFlcu3YNR0dH2rdvr3w4Ly4uZtq0aVy9ehVra2t69uzJ+++/D5T2wsyePZvo6GjMzMzo3LkzmzZtAkp7pj7//HOmTJlCmzZtuO+++5g7dy5PPPHEHdd0J/RSU1Nvf0bMf/z3oL558yb//PMPCxYsYPbs2bc9K78hyczMxNvbm+jo6Dr743vu3LlyJ6mI+iFZq0eyrl+nT5/moYceYv/+/RgZGTXIrIuLi8nIyCA1NZX09HTS0tJITU1VbmlpaaSkpJCWlkZycjKpqamkpKRU+EHJzs4OR0dH5ebs7Kz8dHJywsnJCRcXF5ycnO74fITGeGzXx9++2yksLCQ5ORkvL6+7ugdbiHtJfn4+MTExODo63nZK2lp9VVPRG8hDDz2ktJr2799fm802GtUdayzunGStHslaPQ01awMDA6UnobpKSkrIysoiOTmZ5ORkUlJSlN+Tk5NJSkoiOTmZy5cvK8v+O4ba0tISFxcXnJ2dcXZ2xsXFBVdXV+Vn2c3W1rbC8zIaat5CCFGX6rR/18nJiUuXLtXlJu9JZSe1iPonWatHslZPY8paT08Pa2trrK2tteY4r4xGoyE1NZXExESt240bN5Tfz58/z40bN7SutgqlQ79cXV1xc3NTbk2aNMHExITc3FyaNGmCq6urzDglhGiUavXOd/bsWa37JSUlXL9+nWXLlilj4UTl1OrqFZK1miRr9UjWldPX11eGLN1uSFF+fj6JiYnEx8dz/fp1rl+/TkJCgvLz9OnTxMfHa12lVV9fH1dXV5o2bYq7u7vWzcPDAw8PD7l6tBDinlSrRkOXLl3Q09Mrd4GQ++67T5Uz1huyEydOcO7cOdLS0ujatSutWrWq9swcsbGxfPfdd4waNUr+KFVTTEyMNGRVIlmrR7KuG6ampnh6elZ6ESoo/VLs6NGjWFtbc+3aNeLj47l27Zpy+/vvv7l27ZrW3PrW1tbKdj08PPD29sbb2xsvLy+8vLzu+tmihBCiIrVqNPz9999a9/X09HB0dJQTl6ph06ZNuLu7s2jRIubNm4eFhQXt27enXbt2PPjgg8oV+/T19TE2NiY/Px8ondZt9OjRJCYmYmVlxejRo3X5MoQQolHQ09PDysqK4OBggoODK1xHo9GQmJhIXFyccouNjSU2NpZ9+/YRGxtLQUGBsr6bmxu+vr74+Pjg6+tLs2bNaNasGb6+vo3672jZ+STVuWKxEKJu1OT/W60aDR4eHrV5Wp1Yv349y5cvJzExkeDgYBYvXkzbtm0rXf+7775j4cKFxMbG4uvry5w5c+jRo4eKFZe3detW5cS6nJwcDh48yP79+1m0aBFubm507tyZjh070r59e2xsbLh27RpjxoxRprItu1KguD0vLy9dl9BoSNbqkazVdbu8y4Ysubq6cv/995d7XKPRkJCQQExMDNHR0Vy5coXLly9z5swZvv/+e7KysoDSD82enp74+/vTvHlzmjdvTmBgIIGBgXVyNde7Xdm5IgkJCdWayUUIcWdKSkpITU0FqNa5WtVuNKxZs4ZRo0ZhamrKmjVrqlx3woQJ1d1sjWzfvp3Zs2fz/vvv07ZtW1avXs3QoUM5fvw4Tk5O5dY/duwY48aN44033qBXr15s3bqVp59+mv379+t0+jx/f38uXryo3L91po+EhAS2b9/ON998g56eHoGBgcrUg2UNjZpeYr4xy8rKwsrKqlbPNfjzTwyioihu1oziGlxspjZOx+ZyJbkAH0cTQj3N63Vf9eVOshY1I1mr607z1tfXp2nTpjRt2rTcxU9LSkpITk4mKiqKyMhIIiMjuXjxIrt27WLlypXKt4A+Pj60bNmSVq1aERYWRps2be65E+L19PRwdnYmLS2N+Pj4e/YK40Lcbezt7av1hXS1Gw2rVq1i2LBhmJqasmrVqkrX09PTq7dGw8qVKxk5ciRPPfUUAEuWLGHPnj1s2rSJ6dOnl1t/zZo1dO/enWnTpgHw+uuvc+DAAdavX8+SJUvqpcbqCAsLY9euXZU+XtaIKCkpISIiosLzR0T1pKam0qRJkxo/z2zOHEw//FC5nz9tGnlz5tRhZf/vvR8TWHcwSbk/rqsTL/Zxq5d91afaZi1qTrJWV33mraenp1xXokOHDlqP5ebmcuHCBSIiIjhz5gxnzpxh+fLlyrWSAgIC6NSpE927d6d79+6YmJjUS41qMjQ0xNHREY1GU27qXCFE3TM0NKz2CJZqNxpuPY/hv+c0qKGwsJDTp08zY8YMZZm+vj5du3blxIkTFT7nxIkTTJo0SWvZww8/zI8//ljpfgoKCrTGnpZ1G9elmr4R/rfBIN++VF9tsjL480+tBgOA6YcfUtivX533OJyOzdVqMACsO5hEj5Y2Da7HQY5L9UjW6tJV3ubm5rRu3ZrWrVsry0pKSrh8+TInT57k8OHD/Pzzz3zyyScYGBhw8uTJKk/qbij09PQwMDCo9iQhQgh1NJjJplNSUiguLi43DMnJyUlrqM+tEhMTcXZ21lrm7OxMYmJipftZunQp4eHh5ZZHRERgYWFBYGAg0dHR5OfnY2FhQZMmTYiMjARKT24rm34WoHnz5sTFxZGbm4uZmRmenp488MADXL16lY4dO1JQUECvXr2A0l6RXr164e3tTXJyMp9++ikvvvgiAL///jtpaWn069cPKJ3xIyYmhqysLIyNjfH391emwXVwcMDc3Jy4uDigtEs7NTWVjIwMDA0NCQwM5OzZs5SUlGBvb4+VlRUxMTFA6bjdzMxM0tLS0NfXJygoiIiICIqLi7G1tcXOzo4rV64Apee15ObmkpKSAkDLli25cOECN2/exNraGicnJ6KiogBwd3enoKCApKTSD8dBQUFERUVRUFCApaUlrq6uyvU9mjRpQlFRkfJvFBgYSExMDHl5eZibm+Pu7q78e7u6ugIoeQcEBHD16lUlby8vL0pKSjhz5gzOzs4YGhoSHx8PgJ+fH9evXyc7OxsTExOaNWvGuXPnAGj2119UNKFlwsGDpFlZ0bx5c86cOVNp3mlpaaSnp2NgYECLFi04d+4cGo0GOzs7rK2ttfKOj7/B5Puy0ZToseqkBWPDcjA1LCEh/ip+Dk0rzTs4OJjIyEgKCwuxsrLC2dlZybtp06YUFhYqebdo0YLLly8rebu5uWkdsxqNhhs3bijHbGxsrJK3h4cHFy5cUPLW09MjISEBKB1mFx8fT05ODqamplq5VJT3jRs3lGPWz89PybtsEoWrV68C4OvrS0pKSqXHrKWlJbGxsQB4e3uTnp6ulfetx6ytrS3R0dEAeHp6kp2dTWpqKnp6egQHB3P+/HmKioqwsbHBwcGBy5cvK8dsfn6+ch5RUFAQly5dUvJ2cXGp8pi9k/eIsrxdXFzQ19dX8i4blnjp0iVatWpFcXExERERQOn7oLGxMdeuXSs9hps1IzExUd4jqvEecf78+UqP2VvfIzQajXLMOjk5YWJiohyzzZo1IykpiczMTIyMjOr0PSIrK0sZnmpmZsZPP/3EuXPnuHjxIufOnaOwsBAbGxuCgoLIy8tT9nun7xFlx5YQQpTRS01Nrda4l9dff73aG33nnXdqXVBlEhISCA4O5ueff6Zdu3bK8rfeeovff/+dX3/9tdxzXFxcWLlyJUOGDFGWbdiwgfDwcOUP839V1NMQEhJCdHR0ncyNPn36dBwcHFi6dOlt1zUwMKiwV2Lx4sWMGzfujmtpDM6fP09gYGCNnmPw559Y9+xZbnnmL7/US0/D8BXlL4j49WS/BtfTUJusRfWdPn2ahx56iP3792NiYiJZq0jNY7ukpIT4+HguXLigDE06d+4c58+fJzc3FyhtALdt25Z27drRqVMngoOD67w3JDMzE29v7zr72yeEaPiq3dPw77//at0/ffo0xcXF+Pn5ARAVFYW+vj5hYWF1WmAZBwcHDAwMlG9GyiQlJeHi4lLhcyrqVaio9+FWJiYm9T4u1Ny84g+Denp66OnpodFosLGxoVOnTnTs2JF//vmHr7/+ul5rulcVFRXV+DnF991H/rRpWkOU8p5/vl5Ohg71NGdcVyftcxq6OTW4BgPULmtRO5K1uuoj74yMDKKiorhy5QqXLl0iKiqKS5cucenSJbKzs4HSXuWAgACCgoIYOHCgciK0vb19ndcjhBC3U+1Gw44dO5TfV6xYgaWlJStXrsTW1haA9PR0pkyZUu5ErrpibGxMaGgohw4dom/fvkDpNHYHDx6s9Fv3+++/n0OHDjFx4kRl2YEDByqcEk9NZV3c8P+9CcbGxtx333106tSJBx54AH9/f+XElIEDB6Knp8dXX30FgJGRkU7qbohqexG8vDlzKOzXT5XZk17s40aPljYNfvYkueCgeiRrddUm76KiIuLj44mJiVFuZdOtRkdHK9McQukQPT8/P4KDgxk4cCABAQEEBATg5eUl4/qFEHeNWp3TsHLlSrZu3ao0GABsbW157bXXGDp0KFOmTKmr+rRMmjSJyZMnK9PNrV69mtzcXJ588kkAJk6ciJubG2+++SZQOvVr//79+eijj+jZsyfbt2/n77//rtbQoPpiaWnJvn37lOlUH3zwQTp06EDr1q0rnZNaT0+PN954A4Bt27ZV2lMhyruTb+SK77uv3qdaLRPqad5gGwtl5NtP9UjW6qoo79zcXK5du8bVq1e5evUqcXFxys/Y2Fji4+OV4aV6enq4urri4+ND8+bN6d27t9aF3WT4jxCiIahVoyErK0s5ue1WKSkpSrdqfRg8eDApKSksXLiQxMREWrZsyTfffKMMN7p69arWtFHt27dn7dq1LFiwgLfffhtfX1+++OILnV6j4c033yQqKoq2bdvy6quvYmZmRl5eHgUFBRQXF6Ovr6+c8GhmZkZ+fr4ye9Krr77KmDFjKrwmhdpGjBhBz5497/orU1+5coWWLVvquoxGQbJWj2Rdv7Kzs4mPjychIYGEhAROnTql9BzEx8dz7do1rZ6CskZB06ZN8fT05P7778fT0xMPDw88PT3x9PS8J6ZDFUI0brVqNPTt25cpU6Ywf/582rRpA8DJkyd56623lBl+6su4ceMqHY60c+fOcssGDhzIwIED67WmmjA2Nubs2bNcvXoVR0dH3n333Ro9/26YTm/AgAH89ttv3Lx5865vNAghRJns7Gxu3LjBjRs3uH79OtevX9e6X9ZI+O+XXzY2Nri7u9O0aVPuu+8+BgwYoFyszcPDAzc3N7l6sRDinlerRsP777/Pm2++yfjx47l582bphgwNefrpp5k7d26dFngv2rt3L71792bDhg0UFxfr9EJzNaHRaOjfvz9//PEHXbt2ZevWrbou6bY8PDx0XUKjIVmrR7IuVVJSQnZ2NsnJySQmJpKUlKR1u3HjBklJSSQmJpKYmEhOTo7W883MzHB1dcXFxQVXV1eCgoJwc3OjSZMmuLm54ebmhqurqzKtqRBCNGa1ajSYm5vz3nvvMXfuXGUOdG9vbywsLOqytntWUVERx44do2PHjnz66acUFRXx4X8uJna30Wg09O3bl2PHjtG9e3e++eYbXZdULbm5ufLHXiWStXru1aw1Gg3p6emkpqaSkpKidUtOTi73Mzk5mfz8fK1t6Ovr4+joiJOTE87Oznh7e9O+fXucnJxwdXXF2dlZaSRYWVlVa6rS9PT0ezJvIYSoiTu6uJuFhQXBwcF1VUujkZKSgpubG0eOHKFz58588cUX3Lx5k1WrVqleS1RUVIXnoVhaWtKsWTOg9A95r169OHnyJL169WLLli1ql1lrZVnrSnXyvVfoOuvG5G7PuqioiIyMDOXCe7fe0tLSlIubpaamkpqaSlpamvKz7ByuW9na2uLg4ICjoyOOjo6EhoYqv5c1EBwdHXF2dsbOzq7OZxy62/MWQgg11LrRcOrUKb777juuXr2qDFEq89lnn91xYY2BoaEhR44coUuXLnz11VcUFxezdu1a1fYfFRVV5fSzJ06cwMfHh0ceeYS///6bPn368MUXX6hWX0NXnXzvtYaDaPgKCgrIzs5WbllZWWRlZZGZmVnuZ2ZmJhkZGcrP9PR0MjIyKp0Qw9DQEDs7O2xtbbG3t8fOzg4/Pz/s7e3L3ezs7HB0dMTOzk6mmRZCiLtArRoN27ZtY9KkSTz88MPs37+fhx56iKioKBITE5VrKIjK3do7o6+vz6FDh+jWrRtbt26lqKiIjz/+WJU6bjfTVWZmJt26dePMmTMMGDCATz75RJW66pIue8Jul299zjSmC9LrWL/KZqy7dOkSvr6+/PnnnxQVFVFYWMjNmzeVq9kXFBSQn59Pfn4+BQUF5OXlkZeXR35+Pjk5OeTl5ZGbm0tubi45OTlat+zs7HJfAt1KX18fKysrrKyssLa2Vm7u7u4EBwdjbW2NjY0NNjY22NraKjc7OztsbGywtLSs8ysXq0GObSGEqGWjYenSpbzzzjs8++yzeHp6snDhQry8vJgxY0alV2cWpXJzc/nxxx8pKSnB09MTU1NTAJYtW8Zzzz3Hd999R3JyMvPnz6/3Wi5evFjl4yNHjuTatWs89NBDTJ8+ndOnTyuP5efnExsbq/Ua7kYxMTF4eXnpZN+3y/d2jzc0usy6MVixYgVApbPH/ZeZmRkmJiaYmZlhZmaGqakp5ubmWFhYYGZmhrOzM+bm5pibm2NpaYmlpSUWFhbK75aWllhZWSk/ra2tsbCwaJAf+u9UZGQkAQEBui5DCCF0Si81NbX8ANLbcHd358iRI3h6etKsWTN27txJUFAQFy5cYODAgURERNRHrTqRmZmJt7c30dHRdXIBntOnT/PQQw/VQWVCiMbo1VdfxdfXl8DAQIyMjDA2NsbQ0BATExNMTEwwNjbGxMSkUX64ry9nzpxpdNfFqOu/fUKIhq9WPQ02NjbK0Ao3NzciIiIICgoiIyOD3NzcOi3wXuPv788nn3xCYWFhhd/SazQapk2bxtmzZ2nXrh2LFy+ut1ouXrzIhAkTKn38gQceYMGCBRU+1lB6GhISEnR2AuPt8l2zZs099e2lLrNuDMr+zz388MNkZ2dLr46KrKysdF2CEELoXK0aDR07dmT//v0EBQUxYMAAXn31VQ4dOsSBAwfo2rVrXdd4TzE3N6dnz56YmZlVus7BgweV6yHMnTuX7du3q1jh/1uwYAGhoaGVPt6+fXsVq6mdgICAKrPWpYCAgCrzbWju5qzvFWX/58zNzXVcSePi7Oys6xKEEELn9GvzpPDwcAYPHgzACy+8wKRJk0hKSqJ///53/fUG7gZRUVFVPq6vr8+uXbvo3LkzBw4cYMCAAfVSh6Wl5R093hDcLuv61BjyvZUus25sJGt1Sd5CCFHLngY7Ozvld319faZPn67cz8vLu+OiRKkdO3YwePBgDhw4gK+vLyYmJnW+D0dHRzQaDbm5ueTn5zN48GCmTp16T15HQG3NmjXjxIkTjeY6DUIIIYS4d93Rxd1uVVBQwPr161m+fDnnz5+vq83ek5o2bVrtdbdv38748eM5cOAAxcXF9VJP2TSKkyZNYvbs2fWyD12pSdb1oTE1DHSddWMiWatL8hZCiBo2GgoKCli8eDEHDhzAyMiIadOm0bdvXzZt2sQ777yDvr4+EydOrK9a7xmFhYU1Wl/NC77da2qatag9yVo9krW6JG8hhKjhOQ0LFy7k448/xsPDg7i4OEaPHs306dNZtWoV8+fP5/Tp0zz//PP1Ves9IykpSdclNBqStXoka/VI1uqSvIUQooY9Dd9//z2rVq3i0Ucf5dy5czz44IMUFRXx22+/yZzgQgghhBBC3KNq1NMQHx+vTBEZFBSEiYkJkyZNkgZDDbVo0ULXJTQakrV6JGv1SNbqkryFEKKGjYbi4mKMjY2V+4aGhlhYWNR5Ufe6y5cv67qERkOyVo9krR7JWl2StxBC1HB4UklJCZMnT1am/szPz2fmzJnlGg6fffZZ3VV4DyooKNB1CY2GZK0eyVo9krW6JG8hhKhho+GJJ57Quj9s2LA6LaaxuNcu6nU3k6zVI1mrR7JWl+QthBA1bDSsWLGivupoVNzc3HRdQqMhWatHslaPZK0uyVsIIWp4ToOoG5GRkbouodGQrNUjWatHslaX5C2EENJoEEIIIYQQQtyGNBp0QLq61SNZq0eyVo9krS7JWwghpNGgExqNRtclNBqStXoka/VI1uqSvIUQQhoNOnHjxg1dl9BoSNbqkazVI1mrS/IWQghpNAghhBBCCCFuo8E0GtLS0hg/fjyenp54e3szdepUsrOzq1z/5Zdfpl27djRp0oSQkBBeeeUVMjMzVay6Ys2bN9d1CY2GZK0eyVo9krW6JG8hhGhAjYbx48dz/vx5tm/fzpdffskff/zBjBkzKl0/ISGBhIQE5s2bx++//86KFSvYu3cvU6dOVbHqisXGxuq6hEZDslaPZK0eyVpdkrcQQtTw4m66cuHCBfbu3cvevXtp3bo1AIsWLeLxxx9n3rx5Fc5sERQUxGeffabc9/Hx4fXXX+e5556jqKgIQ8OKX3pBQQEFBQXK/aysrDp+NZCXl1fn2xQVk6zVI1mrR7JWl+QthBANpNFw4sQJbGxslAYDQLdu3dDX1+fkyZP069evWtvJzMzEysqq0gYDwNKlSwkPDy+3PCIiAgsLCwIDA4mOjiY/Px8LCwuaNGmiXPjHzc2NkpISrl+/DpR2acfFxZGbm4uZmRmenp5cuHCB3NxckpKS0NfXJyEhAQB/f38SEhLIzs7GxMQEX19fIiIiAHBycsLY2Jhr164B0KxZMxITE8nKysLY2Bh/f3/Onj0LgIODA+bm5sTFxQGljaXU1FQyMjIwNDQkMDCQs2fPUlJSgr29PVZWVsTExADg5eVFZmYmaWlp6OvrExQUREREBMXFxdja2mJnZ8eVK1cA8PDwIDc3l5SUFABatmzJhQsXuHnzJtbW1jg5OREVFQWAu7s7BQUFJCUlAaUNuqioKAoKCrC0tMTV1ZVLly4B0KRJE4qKikhMTAQgMDCQmJgY8vLyMDc3x93dnYsXLwLg6uoKoOQdEBDA1atXlby9vLzIzc3lzJkzODs7Y2hoSHx8PAB+fn5cv35dybtZs2acO3dOydvExISrV68qeSclJZGZmYmRkRHNmzfnzJkzleadlpZGeno6BgYGtGjRgnPnzqHRaLCzs8Pa2lor76ysLFJTU9HT0yM4OJjz589TVFSEjY0N9vb2leYdHBxMZGQkhYWFWFlZ4ezsrOTdtGlTCgsLlbxbtGjB5cuXlbzd3Ny0jlmNRqOc6Nm8eXNiY2OVvD08PLhw4YKSt56entYxGx8fT05ODqamppiamiq5VJT3jRs3lGPWz89PydvR0RFTU1Mlb19fX1JSUio9Zi0tLZVvfr29vUlPT9fK+9Zj1tbWlujoaAA8PT3Jzs6uNG8HBwcuX76sHLP5+fkkJycrx+ylS5eUvF1cXKo8Zu/0PQLAxcWl0veIgoICiouL5T2iDt4jzp8/X+kxW/YeUVBQgEajaVTvEWXHlhBClNFLTU0t0XURt7NkyRK+/PJLjh8/rrU8ICCAV155hTFjxtx2GykpKTz00EMMHz6c2bNnV7peRT0NISEhREdHY21tXfsXcYubN29iZGRUJ9sSVZOs1SNZq0eyVldjzDszMxNvb+86/dsnhGjYdHpOw9y5c7G3t6/yVvaN0Z3IzMzk8ccfp3nz5rz88stVrmtiYoK1tbVys7KyuuP9/1fZN4mi/knW6pGs1SNZq0vyFkIIHQ9Pmjx5MiNGjKhyHW9vb5ydnZVu1DJFRUWkpaXh7Oxc5fOzsrIYNmwYVlZWfP75543u2yIhhBBCCCHulE4bDY6Ojjg6Ot52vfvvv5+MjAz+/vtvwsLCADh06BAajYa2bdtW+rzMzEyGDh2KiYkJmzZtwtTUtK5KvyNl42xF/ZOs1SNZq0eyVpfkLYQQDWTK1ebNm9O9e3emT5/OyZMnOXr0KC+//DKDBw9WZk6Kj4+nffv2nDx5EihtMAwZMoTc3Fw+/PBDsrKyuHHjBjdu3KC4uFiXLwc9PT2d7r8xkazVI1mrR7JWl+QthBANpNEAsHbtWvz9/Rk0aBCPP/447du3Z+nSpcrjRUVFREZGKlPj/fPPP5w8eZJz587Rtm1bWrRoodzKZhjRlbLZUET9k6zVI1mrR7JWl+QthBANZMpVADs7O9atW1fp456enqSmpir3O3furHVfCCGEEEIIUTsNpqfhXuLv76/rEhoNyVo9krV6JGt1Sd5CCCGNBp0ou3iQqH+StXoka/VI1uqSvIUQQhoNOpGTk6PrEhoNyVo9krV6JGt1Sd5CCCGNBp24W6Z+bQwka/VI1uqRrNUleQshhDQadMLb21vXJTQakrV6JGv1SNbqkryFEEIaDTpx/vx5XZfQaEjW6pGs1SNZq0vyFkKIBjTlqq6UlJQAkJWVVWfbzMnJITMzs862JyonWatHslaPZK2uxph32d+8sr+BQgghjYbbyM7OBiAkJETHlQghhBDqys7OxsbGRtdlCCHuAnqpqanyNUIVNBoNCQkJWFpaoqend8fby8rKIiQkhH///RcrK6s6qFBURrJWj2StHslaXY0175KSErKzs3Fzc0NfX0YyCyGkp+G29PX1adq0aZ1v18rKCmtr6zrfrihPslaPZK0eyVpdjTFv6WEQQtxKvj4QQgghhBBCVEkaDUIIIYQQQogqSaNBZSYmJsyaNQsTExNdl3LPk6zVI1mrR7JWl+QthBCl5ERoIYQQQgghRJWkp0EIIYQQQghRJWk0CCGEEEIIIaokjQYhhBBCCCFElaTRIIQQQgghhKiSNBrqwfr16wkNDcXNzY1HHnmEkydPVrn+d999R/v27XFzc6NTp07s2bNHpUobvppkvXnzZuzt7bVubm5uKlbbcB05coQRI0YQFBSEvb09u3btuu1zDh8+TLdu3XB1daVt27Zs3rxZhUobvppmffjw4XLHtb29PTdu3FCp4oZr6dKldO/eHU9PTwICAnj66aeJjIy87fPkPVsI0RhJo6GObd++ndmzZzNr1iz2799Py5YtGTp0KElJSRWuf+zYMcaNG8dTTz3FgQMH6NOnD08//TTnzp1TufKGp6ZZQ+lVXSMiIpTb6dOnVay44crJyaFly5aEh4dXa/2YmBieeOIJOnfuzMGDB3nuued4/vnn2bt3bz1X2vDVNOsyx48f1zq2nZyc6qnCe8fvv//O2LFj2b17N9u3b+fmzZsMGTKEnJycSp8j79lCiMZKplytY4888ght2rRR/uBrNBpCQkIYN24c06dPL7f+mDFjyM3N5csvv1SW9ejRg5CQEJYsWaJW2Q1STbPevHkzr732GtHR0eoWeo+xt7fn888/p2/fvpWuM2fOHH755ReOHDmiLBs7diwZGRls3bpVjTLvCdXJ+vDhwzz22GNcuXIFGxsbFau79yQnJxMQEMAPP/xAx44dK1xH3rOFEI2V9DTUocLCQk6fPk3Xrl2VZfr6+nTt2pUTJ05U+JwTJ05orQ/w8MMPV7q+KFWbrKH0W9xWrVrRsmVLnnrqKSIiItQot9GR41p9Xbp0oUWLFgwaNIijR4/qupwGKTMzEwBbW9tK15FjWwjRWEmjoQ6lpKRQXFxcbliAk5NTpeOLExMTcXZ21lrm7OxMYmJivdV5L6hN1n5+fixfvpxNmzaxZs0aNBoNvXv35tq1a2qU3KhUdlxnZWWRl5eno6ruTS4uLixZsoSNGzfy6aef0rRpUx577DEZeldDGo2G1157jfbt2xMUFFTpevKeLYRorAx1XYAQamnXrh3t2rXTut+hQwc+/fRTXn/9dR1WJkTt+fv74+/vr9xv37490dHRrFq1itWrV+uwsoblpZdeIiIigh9//FHXpQghxF1JehrqkIODAwYGBuVOxE1KSsLFxaXC51T0DVVF32QJbbXJ+r+MjIwICQnhypUr9VFio1bZcW1lZYWZmZmOqmo82rRpw+XLl3VdRoMxa9Ysdu/ezY4dO2jatGmV68p7thCisZJGQx0yNjYmNDSUQ4cOKcs0Gg0HDx7k/vvvr/A5999/v9b6AAcOHKh0fVGqNln/V3FxMREREdVuZIjqk+Nat/79919cXV11XcZdr6SkhFmzZrFr1y6+//57vLy8bvscObaFEI2VDE+qY5MmTWLy5MmEhYXRpk0bVq9eTW5uLk8++SQAEydOxM3NjTfffBOACRMm0L9/fz766CN69uzJ9u3b+fvvv1m6dKkuX0aDUNOsw8PDue+++/D19SUjI4Ply5cTFxfH//73P12+jAYhOztbq0cmJiaGf//9Fzs7O9zd3Zk3bx4JCQmsWrUKgNGjR7N+/XreeustnnrqKX777Te+++47rRlnRMVqmvWqVavw8vIiMDCQ/Px8Pv/8c3777Te2bdumq5fQYLz00kts3bqVTZs2YWlpqZwPZW1trfSIyXu2EEKUkkZDHRs8eDApKSksXLiQxMREWrZsyTfffKN0XV+9ehV9/f/v4Gnfvj1r165lwYIFvP322/j6+vLFF19UeSKeKFXTrNPT05k+fTqJiYnY2toSGhrKzz//TGBgoK5eQoPx999/89hjjyn3Z8+eDcCIESNYsWIFN27c4OrVq8rjXl5efPnll7z++uusWbOGJk2asGzZMrp376567Q1NTbO+efMmb7zxBgkJCZiZmREcHMy3337Lgw8+qHrtDc3HH38MQP/+/bWWf/TRR8qXD/KeLYQQpeQ6DUIIIYQQQogqyTkNQgghhBBCiCpJo0EIIYQQQghRJWk0CCGEEEIIIaokjQYhhBBCCCFElaTRIIQQQgghhKiSNBqEEEIIIYQQVZJGgxBCCCGEEKJK0mgQQgghhBBCVEkaDUKIenH48GHs7e3JyMiocr3Q0FBWrVqlSk3PPfccS5YsuaNt/Prrr3Tp0gWNRlNHVQkhhBB3P2k0CNGITZ48GXt7e+zt7XFxcaFt27aEh4dTVFR0x9tu164dERERWFtbA7B582a8vb3Lrbd3715GjRp1x/u7nTNnzrBnzx7Gjx9/R9t55JFHMDIy4ptvvqmjyoQQQoi7nzQahGjkunfvTkREBH/++SeTJ09m8eLFLF++/I63a2xsjIuLC3p6elWu5+joiLm5+R3v73bWrl3LgAEDsLS0vONtjRgxgrVr19ZBVUIIIUTDII0GIRo5ExMTXFxc8PDwYMyYMXTt2pWffvoJgPT0dCZOnIiPjw9NmzZl2LBhREVFKc+Ni4tjxIgR+Pj44O7uzgMPPMCePXsA7eFJhw8fZsqUKWRmZio9G4sWLQLKD0+6evUqTz31FB4eHnh6ejJ69GgSExOVxxctWkSXLl346quvCA0NxcvLi7Fjx5KVlVXpaywuLmbHjh307t1ba3loaCjvvfceEydOxMPDg1atWvHTTz+RnJys1NC5c2dOnTql9bzevXtz6tQprly5UsvUhRBCiIZFGg1CCC1mZmbcvHkTKB2+dOrUKTZv3szu3bspKSnh8ccfVx5/6aWXKCgoYNeuXRw+fJg5c+ZgYWFRbpvt2rVjwYIFWFlZERERQUREBFOmTCm3nkaj4amnniItLY2dO3eyfft2YmJiGDt2rNZ60dHR7Nq1iy1btvDll19y5MgRli1bVulrOnv2LJmZmYSFhZV7bNWqVbRv354DBw7Qs2dPnnvuOSZOnMiwYcPYv38/Pj4+TJw4kZKSEuU57u7uODs788cff1QrUyGEEKKhM9R1AUKIu0NJSQkHDx5k3759jBs3jqioKH766Sd++ukn2rdvD5QO8QkJCWHXrl0MHDiQq1ev0r9/f4KCggAqPGcBSocqWVtbo6enh4uLS6U1HDx4kHPnznHq1Cnc3d0BWLlyJR07duSvv/6iTZs2QGnjYsWKFVhZWQEwfPhwDh48yOzZsyvcblxcHAYGBjg5OZV7rEePHjzzzDNAaSPo448/pnXr1gwcOBCAadOm0atXLxITE7Vqd3V1JS4urtLXIoQQQtxLpKdBiEZu9+7deHh44ObmxvDhwxk0aBAvv/wyFy9exNDQkPvuu09Z197eHj8/Py5evAjA+PHjef/99+nduzcLFy7k7Nmzd1TLxYsXadq0qdJgAAgMDMTGxkbZJ4CHh4fSYABwcXEhOTm50u3m5+djYmJS4fkVZQ0eAGdn50qX/Xf7pqam5OXlVfelCSGEEA2aNBqEaOQ6d+7MwYMH+fPPP4mPj2flypUVDjGqyMiRI/nrr794/PHHiYiI4OGHH1blBGEjIyOt+3p6elVOgWpvb09ubi6FhYVVbqusUVHRsv9uPy0tDQcHh5oXL4QQQjRA0mgQopGzsLDA19cXd3d3DA3/f8RiQEAARUVF/Pnnn8qy1NRULl26RPPmzZVl7u7ujB49ms8++4zJkyfz2WefVbgfY2Pj217bICAggGvXrnH16lVl2fnz58nIyNDaZ02FhIQAcOHChVpv41b5+flER0fTqlWrOtmeEEIIcbeTRoMQokLNmjWjT58+TJ8+naNHj3LmzBkmTJiAm5sbffr0AeDVV19l7969xMTEcPr0aX777TcCAgIq3J6HhwfZ2dkcPHiQlJQUcnNzy63TrVs3goKCmDBhAqdPn+bkyZNMmjSJTp060bp161q/FkdHR0JDQzl69Gitt3GrP//8ExMTE+6///462Z4QQghxt5NGgxCiUh999BFhYWE88cQT9OrVi5KSEr766itl+I5Go2HWrFl06NCBYcOG4efnx3vvvVfhttq3b8/o0aMZO3Ys/v7+fPjhh+XW0dPTY9OmTdja2tKvXz8GDRqEl5cXGzZsuOPX8r///a/OLsi2bds2hg4dqsr1JYQQQoi7gV5qamrJ7VcTQoiGLS8vj3bt2rFhwwbatWtX6+2kpKTQrl079u3bh5eXVx1WKIQQQty9pKdBCNEomJmZsWrVKlJTU+9oO7Gxsbz77rvSYBBCCNGoSE+DEEIIIYQQokrS0yCEEEIIIYSokjQahBBCCCGEEFWSRoMQQgghhBCiStJoEEIIIYQQQlRJGg1CCCGEEEKIKkmjQQghhBBCCFElaTQIIYQQQgghqiSNBiGEEEIIIUSVpNEghBBCCCGEqNL/Abu5CoryWglnAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prometheus.info()\n",
+    "prometheus.draw()\n",
+    "prometheus.plots.drag_curves()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulate the Flight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_flight = Flight(\n",
+    "    rocket=prometheus,\n",
+    "    environment=env,\n",
+    "    inclination=80,\n",
+    "    heading=75,\n",
+    "    rail_length=5.18,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Rail Departure State\n",
+      "\n",
+      "Rail Departure Time: 0.385 s\n",
+      "Rail Departure Velocity: 25.256 m/s\n",
+      "Rail Departure Stability Margin: 1.090 c\n",
+      "Rail Departure Angle of Attack: 0.455°\n",
+      "Rail Departure Thrust-Weight Ratio: 8.326\n",
+      "Rail Departure Reynolds Number: 1.911e+05\n",
+      "\n",
+      "Burn out State\n",
+      "\n",
+      "Burn out time: 4.897 s\n",
+      "Altitude at burn out: 2271.761 m (ASL) | 870.761 m (AGL)\n",
+      "Rocket speed at burn out: 328.201 m/s\n",
+      "Freestream velocity at burn out: 326.875 m/s\n",
+      "Mach Number at burn out: 0.950\n",
+      "Kinetic energy at burn out: 9.108e+05 J\n",
+      "\n",
+      "Apogee State\n",
+      "\n",
+      "Apogee Time: 29.113 s\n",
+      "Apogee Altitude: 5591.386 m (ASL) | 4190.386 m (AGL)\n",
+      "Apogee Freestream Speed: 35.967 m/s\n",
+      "Apogee X position: 1524.285 m\n",
+      "Apogee Y position: 427.117 m\n",
+      "Apogee latitude: 32.9432166°\n",
+      "Apogee longitude: -106.8956535°\n",
+      "\n",
+      "Stability Margin\n",
+      "\n",
+      "Initial Stability Margin: 1.042 c at 0.00 s\n",
+      "Out of Rail Stability Margin: 1.090 c at 0.38 s\n",
+      "Maximum Stability Margin: 1.886 c at 4.91 s\n",
+      "Minimum Stability Margin: 1.042 c at 0.00 s\n",
+      "\n",
+      "Maximum Values\n",
+      "\n",
+      "Maximum Speed: 330.240 m/s at 4.71 s\n",
+      "Maximum Mach Number: 0.955 Mach at 4.74 s\n",
+      "Maximum Reynolds Number: 2.339e+06 at 4.66 s\n",
+      "Maximum Dynamic Pressure: 5.021e+04 Pa at 4.69 s\n",
+      "Maximum Acceleration During Motor Burn: 82.803 m/s² at 1.67 s\n",
+      "Maximum Gs During Motor Burn: 8.444 g at 1.67 s\n",
+      "Maximum Acceleration After Motor Burn: 11.737 m/s² at 17.59 s\n",
+      "Maximum Gs After Motor Burn: 1.197 Gs at 17.59 s\n",
+      "Maximum Stability Margin: 1.886 c at 4.91 s\n",
+      "Maximum Upper Rail Button Normal Force: 0.191 N\n",
+      "Maximum Upper Rail Button Shear Force: 0.060 N\n",
+      "Maximum Lower Rail Button Normal Force: 0.119 N\n",
+      "Maximum Lower Rail Button Shear Force: 0.038 N\n"
+     ]
+    }
+   ],
+   "source": [
+    "# test_flight.prints.initial_conditions()\n",
+    "# test_flight.prints.surface_wind_conditions()\n",
+    "# test_flight.prints.launch_rail_conditions()\n",
+    "test_flight.prints.out_of_rail_conditions()\n",
+    "test_flight.prints.burn_out_conditions()\n",
+    "test_flight.prints.apogee_conditions()\n",
+    "# test_flight.prints.events_registered()\n",
+    "# test_flight.prints.impact_conditions()\n",
+    "test_flight.prints.stability_margin()\n",
+    "test_flight.prints.maximum_values()\n",
+    "# test_flight.prints.numerical_integration_settings()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Read the Telemetry Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The following attributes were create and are now available to be used:  ['time', 'z', 'altitude', 'acceleration', 'pressure', 'latitude', 'longitude']\n"
+     ]
+    }
+   ],
+   "source": [
+    "columns_map = {\n",
+    "    \"time\": \"time\",\n",
+    "    \"altitude\": \"z\",\n",
+    "    \"height\": \"altitude\",\n",
+    "    \"acceleration\": \"acceleration\",\n",
+    "    \"pressure\": \"pressure\",\n",
+    "    \"accel_x\": \"ax\",\n",
+    "    \"accel_y\": \"ay\",\n",
+    "    \"accel_z\": \"az\",\n",
+    "    \"latitude\": \"latitude\",\n",
+    "    \"longitude\": \"longitude\",\n",
+    "}\n",
+    "\n",
+    "\n",
+    "cots_altimeter_flight = FlightDataImporter(\n",
+    "    name=\"Telemetry Mega\",\n",
+    "    paths=\"../../data/prometheus/2022-06-24-serial-5115-flight-0001-TeleMetrum.csv\",\n",
+    "    columns_map=columns_map,\n",
+    "    units=None,\n",
+    "    interpolation=\"linear\",\n",
+    "    extrapolation=\"zero\",\n",
+    "    delimiter=\",\",\n",
+    "    encoding=\"utf-8\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compare Simulation and Telemetry Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RocketPy apogee: 4190.39 m\n",
+      "Real apogee: 3903.77 m\n",
+      "Absolute error: 286.62 m\n",
+      "Relative error: 7.34%\n"
+     ]
+    }
+   ],
+   "source": [
+    "real_apogee = cots_altimeter_flight.altitude.max\n",
+    "rocketpy_apogee = test_flight.apogee - test_flight.env.elevation\n",
+    "a_error = abs(real_apogee - rocketpy_apogee)\n",
+    "r_error = a_error / real_apogee * 100\n",
+    "\n",
+    "print(f\"RocketPy apogee: {rocketpy_apogee:.2f} m\")\n",
+    "print(f\"Real apogee: {real_apogee:.2f} m\")\n",
+    "print(f\"Absolute error: {a_error:.2f} m\")\n",
+    "print(f\"Relative error: {r_error:.2f}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Altitude comparison\n",
+    "Function.compare_plots(\n",
+    "    [\n",
+    "        (test_flight.altitude, \"RocketPy\"),\n",
+    "        (cots_altimeter_flight.altitude, \"Telemetry\"),\n",
+    "    ],\n",
+    "    title=\"Altitude Comparison\",\n",
+    "    xlabel=\"Time (s)\",\n",
+    "    ylabel=\"Altitude (m)\",\n",
+    "    lower=0,\n",
+    "    # upper=30,\n",
+    ")\n",
+    "\n",
+    "# Pressure comparison\n",
+    "Function.compare_plots(\n",
+    "    [\n",
+    "        (test_flight.pressure, \"RocketPy\"),\n",
+    "        (cots_altimeter_flight.pressure, \"Telemetry\"),\n",
+    "    ],\n",
+    "    title=\"Pressure Comparison\",\n",
+    "    xlabel=\"Time (s)\",\n",
+    "    ylabel=\"Pressure (Pa)\",\n",
+    "    lower=0,\n",
+    "    # upper=30,\n",
+    ")\n",
+    "\n",
+    "# Latitude comparison\n",
+    "# Function.compare_plots(\n",
+    "#     [\n",
+    "#         (test_flight.latitude, \"RocketPy\"),\n",
+    "#         (cots_altimeter_flight.latitude, \"Telemetry\"),\n",
+    "#     ],\n",
+    "#     title=\"Latitude Comparison\",\n",
+    "#     xlabel=\"Time (s)\",\n",
+    "#     ylabel=\"Latitude (deg)\",\n",
+    "#     lower=0,\n",
+    "#     # upper=30,\n",
+    "# )\n",
+    "\n",
+    "# Longitude comparison\n",
+    "# Function.compare_plots(\n",
+    "#     [\n",
+    "#         (test_flight.longitude, \"RocketPy\"),\n",
+    "#         (cots_altimeter_flight.longitude, \"Telemetry\"),\n",
+    "#     ],\n",
+    "#     title=\"Longitude Comparison\",\n",
+    "#     xlabel=\"Time (s)\",\n",
+    "#     ylabel=\"Longitude (deg)\",\n",
+    "#     lower=0,\n",
+    "#     # upper=30,\n",
+    "# )\n",
+    "\n",
+    "# Convert \"deceleration\" to \"acceleration\" for comparison\n",
+    "absolute_cots_acceleration = lambda x: abs(cots_altimeter_flight.acceleration(x))\n",
+    "\n",
+    "# Acceleration comparison\n",
+    "Function.compare_plots(\n",
+    "    [\n",
+    "        (test_flight.acceleration, \"RocketPy\"),\n",
+    "        (Function(absolute_cots_acceleration), \"Telemetry\"),\n",
+    "    ],\n",
+    "    title=\"Acceleration Comparison\",\n",
+    "    xlabel=\"Time (s)\",\n",
+    "    ylabel=\"Acceleration (m/s^2)\",\n",
+    "    lower=0,\n",
+    "    upper=30,\n",
+    ")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/index.rst b/docs/index.rst
index 0b5d754bd..773c26366 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -1,10 +1,92 @@
-.. RocketPy documentation master file, created by
-   sphinx-quickstart on Wed Mar  4 06:03:53 2020.
-   You can adapt this file completely to your liking, but it should at least
-   contain the root `toctree` directive.
+######################
+RocketPy Documentation
+######################
+
+**Version**: |release|
+
+**Useful links**:
+`Installation <https://docs.rocketpy.org/en/latest/user/installation.html>`_ |
+`Source Repository <https://github.com/RocketPy-Team/RocketPy>`_ |
+`Issue Tracker <https://github.com/RocketPy-Team/RocketPy/issues>`_ |
+`Q&A Support <https://discord.gg/b6xYnNh>`_ |
+
+RocketPy is the next-generation trajectory simulation solution for High-Power Rocketry. The code is written as a Python library and allows for a complete 6 degrees of freedom simulation of a rocket's flight trajectory, including high-fidelity variable mass effects as well as descent under parachutes. Weather conditions, such as wind profiles, can be imported from sophisticated datasets, allowing for realistic scenarios. Furthermore, the implementation facilitates complex simulations, such as multi-stage rockets, design and trajectory optimization and dispersion analysis.
+
+.. grid:: 2
+
+    .. grid-item-card::
+       :img-top: ./static/landing_images/getting_started.svg
+
+       Getting started
+       ^^^^^^^^^^^^^^^
+
+       Simulating your first rocket? Check out the Beginner's Guide. It contains an
+       introduction to RocketPy main concepts and walks you through the process of
+       setting up a simulation.
+
+       +++
+
+       .. button-ref:: user/first_simulation
+          :expand:
+          :color: secondary
+          :click-parent:
+
+          To the beginner's guide
+
+    .. grid-item-card::
+       :img-top: ./static/landing_images/user_guide.svg
+       
+       User guide
+       ^^^^^^^^^^
+
+       The user guide provides in-depth information on
+       RocketPy functionalities with useful background information and explanation.
+
+       +++
+
+       .. button-ref:: user/index
+          :expand:
+          :color: secondary
+          :click-parent:
+
+          To the user guide
+
+    .. grid-item-card::
+       :img-top: ./static/landing_images/api.svg
+
+       API reference
+       ^^^^^^^^^^^^^
+
+       The reference guide contains a detailed description of RocketPy modules. Here it is described how the methods work and which parameters can be used. It assumes that you already have an understanding of key concepts.
+
+       +++
+
+       .. button-ref:: reference/index
+          :expand:
+          :color: secondary
+          :click-parent:
+
+          To the reference guide
+
+    .. grid-item-card::
+       :img-top: ./static/landing_images/contributor.svg
+
+       Contributor's guide
+       ^^^^^^^^^^^^^^^^^^^
+
+       Want to contribute to RocketPy source code? The contributing guidelines will guide you through the process of improving RocketPy.
+
+       +++
+
+       .. button-ref:: development/index
+          :expand:
+          :color: secondary
+          :click-parent:
+
+          To the contributor's guide
 
 .. toctree::
-   :maxdepth: 4
+   :maxdepth: 1
    :hidden:
 
    User Guide <user/index>
@@ -13,11 +95,3 @@
    Technical <technical/index>
    Flight Examples <examples/index>
 
-.. mdinclude:: ../README.md
-
-Indices and tables
-==================
-
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`
diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis.ipynb
similarity index 99%
rename from docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb
rename to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis.ipynb
index fc4c8cf97..30b43f65b 100644
--- a/docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb
+++ b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis.ipynb
@@ -20,6 +20,13 @@
     "We hope you enjoy the flight(s) in this notebook just like everyone in LASC19 did it in real-time!"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**NOTE:** There is a new `MonteCarlo` class in RocketPy v1.2.0. This notebook is still here just for reference, but it is recommended to use the new class. See the `Monte Carlo class usage` page in the documentation for more information."
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -384,7 +391,7 @@
    ],
    "source": [
     "# Basic analysis info\n",
-    "filename = \"dispersion_analysis_outputs/valetudo_rocket_v0\"\n",
+    "filename = \"monte_carlo_analysis_outputs/valetudo_rocket_v0\"\n",
     "number_of_simulations = 100\n",
     "\n",
     "# Create data files for inputs, outputs and error logging\n",
@@ -404,7 +411,7 @@
     "Env.max_expected_height = 1500\n",
     "Env.set_atmospheric_model(\n",
     "    type=\"Ensemble\",\n",
-    "    file=\"dispersion_analysis_inputs/LASC2019_reanalysis.nc\",\n",
+    "    file=\"monte_carlo_analysis_inputs/LASC2019_reanalysis.nc\",\n",
     "    dictionary=\"ECMWF\",\n",
     ")\n",
     "\n",
@@ -428,7 +435,7 @@
     "\n",
     "    # Create motor\n",
     "    Keron = SolidMotor(\n",
-    "        thrust_source=\"dispersion_analysis_inputs/thrustCurve.csv\",\n",
+    "        thrust_source=\"monte_carlo_analysis_inputs/thrustCurve.csv\",\n",
     "        burn_time=5.274,\n",
     "        reshape_thrust_curve=(setting[\"burn_time\"], setting[\"impulse\"]),\n",
     "        nozzle_radius=setting[\"nozzle_radius\"],\n",
@@ -460,8 +467,8 @@
     "            setting[\"rocket_inertia_11\"],\n",
     "            setting[\"rocket_inertia_33\"],\n",
     "        ),\n",
-    "        power_off_drag=\"dispersion_analysis_inputs/Cd_PowerOff.csv\",\n",
-    "        power_on_drag=\"dispersion_analysis_inputs/Cd_PowerOn.csv\",\n",
+    "        power_off_drag=\"monte_carlo_analysis_inputs/Cd_PowerOff.csv\",\n",
+    "        power_on_drag=\"monte_carlo_analysis_inputs/Cd_PowerOn.csv\",\n",
     "        center_of_mass_without_motor=0,\n",
     "        coordinate_system_orientation=\"tail_to_nose\",\n",
     "    )\n",
@@ -574,7 +581,7 @@
     }
    ],
    "source": [
-    "filename = \"dispersion_analysis_outputs/valetudo_rocket_v0\"\n",
+    "filename = \"monte_carlo_analysis_outputs/valetudo_rocket_v0\"\n",
     "\n",
     "# Initialize variable to store all results\n",
     "dispersion_general_results = []\n",
@@ -20354,7 +20361,7 @@
     "from matplotlib.patches import Ellipse\n",
     "\n",
     "# Import background map\n",
-    "img = imread(\"dispersion_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
+    "img = imread(\"monte_carlo_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
     "\n",
     "# Retrieve dispersion data por apogee and impact XY position\n",
     "apogee_x = np.array(dispersion_results[\"apogee_x\"])\n",
diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Cd_PowerOff.csv b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Cd_PowerOff.csv
similarity index 100%
rename from docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Cd_PowerOff.csv
rename to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Cd_PowerOff.csv
diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Cd_PowerOn.csv b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Cd_PowerOn.csv
similarity index 100%
rename from docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Cd_PowerOn.csv
rename to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Cd_PowerOn.csv
diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/LASC2019_reanalysis.nc b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/LASC2019_reanalysis.nc
similarity index 100%
rename from docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/LASC2019_reanalysis.nc
rename to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/LASC2019_reanalysis.nc
diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Valetudo_basemap_final.jpg b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Valetudo_basemap_final.jpg
similarity index 100%
rename from docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Valetudo_basemap_final.jpg
rename to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Valetudo_basemap_final.jpg
diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/thrustCurve.csv b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/thrustCurve.csv
similarity index 100%
rename from docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/thrustCurve.csv
rename to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/thrustCurve.csv
diff --git a/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.errors.txt b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.errors.txt
new file mode 100644
index 000000000..e69de29bb
diff --git a/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.inputs.txt b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.inputs.txt
new file mode 100644
index 000000000..9a890d126
--- /dev/null
+++ b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.inputs.txt
@@ -0,0 +1,1000 @@
+{"elevation": 113, "gravity": "'Function from R1 to R1 : (height (m)) \u2192 (gravity (m/s\u00b2))'", "latitude": 39.3897, "longitude": -8.288964, "wind_velocity_x_factor": 1.0, "wind_velocity_y_factor": 1.0, "datum": "SIRGAS2000", "timezone": "UTC", "ensemble_member": 4, "radius": 0.06349805737362968, "mass": 15.389343012059967, "I_11_without_motor": 6.321, "I_22_without_motor": 6.321735286465201, "I_33_without_motor": 0.03131376369351965, "I_12_without_motor": 0, "I_13_without_motor": 0, "I_23_without_motor": 0, "power_off_drag": "'Function from R1 to R1 : (Mach Number) \u2192 (Drag Coefficient with Power Off)'", "power_on_drag": "'Function from R1 to R1 : (Mach Number) \u2192 (Drag Coefficient with Power On)'", "power_off_drag_factor": 1.0, "power_on_drag_factor": 1.0, "center_of_mass_without_motor": 0.0, "coordinate_system_orientation": "tail_to_nose", "parachutes": [{"cd_s": 9.876119007794975, "trigger": 800, "sampling_rate": 105, "lag": 1.4039051334657628, "noise": [0, 8.3, 0.5], "name": "Main"}, {"cd_s": 1.1153330682349194, "trigger": "apogee", "sampling_rate": 105, "lag": 1.312010528474876, "noise": [0, 8.3, 0.5], "name": "Drogue"}], "motors": [{"thrust_source": [[0, 0], [0.055, 100.0], [0.092, 1500.0], [0.1, 2000.0], [0.15, 2200.0], [0.2, 1800.0], [0.5, 1950.0], [1.0, 2034.0], [1.5, 2000.0], [2.0, 1900.0], [2.5, 1760.0], [2.9, 1700.0], [3.0, 1650.0], [3.3, 530.0], [3.4, 350.0], [3.9, 0.0]], "total_impulse": 4108.051237022448, "burn_start_time": 0, "burn_out_time": 3.9, "dry_mass": 1.815, "dry_I_11": 0.125, "dry_I_22": 0.125, "dry_I_33": 0.002, "dry_I_12": 0, "dry_I_13": 0, "dry_I_23": 0, "nozzle_radius": 0.03311718353546555, "grain_number": 5, "grain_density": 1695.4913078620402, "grain_outer_radius": 0.03264948443697062, "grain_initial_inner_radius": 0.014555365817764128, "grain_initial_height": 0.11821009521651879, "grain_separation": 0.004583915578695257, "grains_center_of_mass_position": 0.3969572624428137, "center_of_dry_mass_position": 0.317, "nozzle_position": 0.00047102172569662396, "throat_radius": 0.010080872060816265, "interpolate": "linear", "coordinate_system_orientation": "nozzle_to_combustion_chamber", "position": -1.255619886341495}], "aerodynamic_surfaces": [{"length": 0.5576500216475931, "kind": "vonKarman", "base_radius": 0.0635, "bluffness": 0, "rocket_radius": 0.0635, "name": "Nose Cone", "position": 1.1352121042080896}, {"n": 4, "root_chord": 0.12021634187795194, "tip_chord": 0.06025703291533595, "span": 0.10918068131206991, "rocket_radius": 0.0635, "cant_angle": 0.5, "sweep_length": 0.06, "sweep_angle": null, "airfoil": ["../../../data/calisto/NACA0012-radians.csv", "radians"], "name": "Fins", "position": -1.0488626145273403}, {"top_radius": 0.0626865801265797, "bottom_radius": 0.04297830537127572, "length": 0.06011444931045156, "rocket_radius": 0.0635, "name": "Tail", "position": -1.194656}], "rail_buttons": [{"buttons_distance": 0.6992654977438861, "angular_position": 45, "name": "Rail Buttons", "lower_button_position": -0.6187574583936143, "upper_button_position": 0.08050803935027184}], "rail_length": 5, "inclination": 83.99566634839267, "heading": 53.47446847289658}
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index 000000000..2e3cf5fd4
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diff --git a/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.outputs.txt b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.outputs.txt
new file mode 100644
index 000000000..64c9f72ee
--- /dev/null
+++ b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example.outputs.txt
@@ -0,0 +1,1000 @@
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diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_outputs/parachute_drop_from_helicopter.disp_inputs.txt b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/parachute_drop_from_helicopter.disp_inputs.txt
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diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis_outputs/valetudo_rocket_v0.disp_errors.txt b/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/valetudo_rocket_v0.disp_errors.txt
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diff --git a/docs/notebooks/monte_carlo_analysis/monte_carlo_class_usage.ipynb b/docs/notebooks/monte_carlo_analysis/monte_carlo_class_usage.ipynb
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+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Monte Carlo class usage"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Landing point dispersion elipses](https://github.com/RocketPy-Team/RocketPy/raw/master/docs/notebooks/dispersion_analysis/dispersion_analysis_outputs/valetudo_rocket_v0.svg)\n",
+    "\n",
+    "This is an advanced use of RocketPy. This notebook runs a Monte Carlo analysis and predicts probability distributions of the rocket's landing point, apogee and other relevant information. \n",
+    "\n",
+    "The `MonteCarlo` class simplifies the process of performing Monte Carlo simulations. The idea is to take the already defined classes for a standard flight simulation, and create the so called ``Stochastic`` classes, which are used to run the Monte Carlo analysis.\n",
+    "\n",
+    "This class offers extensive capabilities, and this example notebook covers as many as possible.\n",
+    "For a deeper understanding, we recommend checking the class [documentation](https://docs.rocketpy.org/en/latest/).\n",
+    "\n",
+    "For a more comprehensive conceptual understanding of Monte Carlo Simulations, refer to RocketPy's main reference: [RocketPy: Six Degree-of-Freedom Rocket Trajectory Simulator](https://doi.org/10.1061/(ASCE)AS.1943-5525.0001331).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# We import these lines for debugging purposes, only works on Jupyter Notebook\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, let's import the necessary libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from rocketpy import Environment, SolidMotor, Rocket, Flight, MonteCarlo, Function\n",
+    "from rocketpy.stochastic import (\n",
+    "    StochasticEnvironment,\n",
+    "    StochasticSolidMotor,\n",
+    "    StochasticRocket,\n",
+    "    StochasticFlight,\n",
+    "    StochasticNoseCone,\n",
+    "    StochasticTail,\n",
+    "    StochasticTrapezoidalFins,\n",
+    "    StochasticParachute,\n",
+    "    StochasticRailButtons,\n",
+    ")\n",
+    "import datetime"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If you are using Jupyter Notebooks, it is recommended to run the following line to make matplotlib plots which will be shown later interactive and higher quality.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib widget"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 1: Standard Simulation\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will first create a standard RocketPy simulation objects (e.g. Environment, SolidMotor, etc.) to then create the Stochastic objects.\n",
+    "\n",
+    "The standard objects created here are the same as in the [First Simulation Page](https://docs.rocketpy.org/en/latest/user/first_simulation.html) of our documentation, so you can go through that if you want to understand what is done in more detail.\n",
+    "\n",
+    "The only difference here is that we will use a `Environment` with atmospheric model type `Ensemble`. This allows us to run the Monte Carlo analysis with different ensemble members, which are different atmospheric profiles.\n",
+    "\n",
+    "We will do it all in one single cell for simplicity."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total Impulse of the Solid Motor: 6026.35 Ns\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Environment\n",
+    "env = Environment(latitude=39.389700, longitude=-8.288964, elevation=113)\n",
+    "tomorrow = datetime.date.today() + datetime.timedelta(days=1)\n",
+    "env.set_date((tomorrow.year, tomorrow.month, tomorrow.day, 12))\n",
+    "env.set_atmospheric_model(type=\"Ensemble\", file=\"GEFS\")\n",
+    "\n",
+    "# Motor\n",
+    "motor = SolidMotor(\n",
+    "    thrust_source=\"../../../data/motors/Cesaroni_M1670.eng\",\n",
+    "    dry_mass=1.815,\n",
+    "    dry_inertia=(0.125, 0.125, 0.002),\n",
+    "    nozzle_radius=33 / 1000,\n",
+    "    grain_number=5,\n",
+    "    grain_density=1815,\n",
+    "    grain_outer_radius=33 / 1000,\n",
+    "    grain_initial_inner_radius=15 / 1000,\n",
+    "    grain_initial_height=120 / 1000,\n",
+    "    grain_separation=5 / 1000,\n",
+    "    grains_center_of_mass_position=0.397,\n",
+    "    center_of_dry_mass_position=0.317,\n",
+    "    nozzle_position=0,\n",
+    "    burn_time=3.9,\n",
+    "    throat_radius=11 / 1000,\n",
+    "    coordinate_system_orientation=\"nozzle_to_combustion_chamber\",\n",
+    ")\n",
+    "print(f\"Total Impulse of the Solid Motor: {motor.total_impulse} Ns\")\n",
+    "\n",
+    "# Rocket\n",
+    "rocket = Rocket(\n",
+    "    radius=127 / 2000,\n",
+    "    mass=14.426,\n",
+    "    inertia=(6.321, 6.321, 0.034),\n",
+    "    power_off_drag=\"../../../data/calisto/powerOffDragCurve.csv\",\n",
+    "    power_on_drag=\"../../../data/calisto/powerOnDragCurve.csv\",\n",
+    "    center_of_mass_without_motor=0,\n",
+    "    coordinate_system_orientation=\"tail_to_nose\",\n",
+    ")\n",
+    "\n",
+    "rail_buttons = rocket.set_rail_buttons(\n",
+    "    upper_button_position=0.0818,\n",
+    "    lower_button_position=-0.618,\n",
+    "    angular_position=45,\n",
+    ")\n",
+    "\n",
+    "rocket.add_motor(motor, position=-1.255)\n",
+    "\n",
+    "nose_cone = rocket.add_nose(length=0.55829, kind=\"vonKarman\", position=1.278)\n",
+    "\n",
+    "fin_set = rocket.add_trapezoidal_fins(\n",
+    "    n=4,\n",
+    "    root_chord=0.120,\n",
+    "    tip_chord=0.060,\n",
+    "    span=0.110,\n",
+    "    position=-1.04956,\n",
+    "    cant_angle=0.5,\n",
+    "    airfoil=(\"../../../data/calisto/NACA0012-radians.csv\", \"radians\"),\n",
+    ")\n",
+    "\n",
+    "tail = rocket.add_tail(\n",
+    "    top_radius=0.0635, bottom_radius=0.0435, length=0.060, position=-1.194656\n",
+    ")\n",
+    "Main = rocket.add_parachute(\n",
+    "    \"Main\",\n",
+    "    cd_s=10.0,\n",
+    "    trigger=800,\n",
+    "    sampling_rate=105,\n",
+    "    lag=1.5,\n",
+    "    noise=(0, 8.3, 0.5),\n",
+    ")\n",
+    "\n",
+    "Drogue = rocket.add_parachute(\n",
+    "    \"Drogue\",\n",
+    "    cd_s=1.0,\n",
+    "    trigger=\"apogee\",\n",
+    "    sampling_rate=105,\n",
+    "    lag=1.5,\n",
+    "    noise=(0, 8.3, 0.5),\n",
+    ")\n",
+    "\n",
+    "# Flight\n",
+    "test_flight = Flight(\n",
+    "    rocket=rocket,\n",
+    "    environment=env,\n",
+    "    rail_length=5,\n",
+    "    inclination=84,\n",
+    "    heading=133,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets check the trajectory of the Flight."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c66d0d4ff6d74269868eda1b66209fff",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=900.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_flight.plots.trajectory_3d()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The flight trajectory above represents the nominal trajectory of the rocket, without any uncertainties.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 2: Stochastic Objects"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For each RocketPy object, we will create a ``Stochastic`` counterpart that extends the initial model, allowing us to define the uncertainties of each input parameter.\n",
+    "\n",
+    "Please refer to the [Working with Stochastic Objects]() page on RocketPy`s documentation for a more detailed explanation."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Stochastic Environment"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "Starting with the `Environment` object, we will create a `StochasticEnvironment` to specify its uncertainties.\n",
+    "\n",
+    "In this first example, we will specify the ensemble member and wind velocities factor.\n",
+    "\n",
+    "Since the ensemble member is a discrete value, **only list type inputs are permitted**. The list will contain the ensemble numbers to be randomly selected during the Monte Carlo simulation. This means that in each iteration, a different ensemble member will be chosen.\n",
+    "\n",
+    "<!-- The wind velocities factor are also special inputs. They are used to scale the wind velocities in each axis. The factor inputs can only be tuples or lists, since it has no nominal value to get from the standard. Lets scale the wind by a factor of 1.00000 ± 0.2 -->"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reporting the attributes of the `StochasticEnvironment` object:\n",
+      "\n",
+      "Constant Attributes:\n",
+      "\tdatum                    SIRGAS2000\n",
+      "\televation                113\n",
+      "\tgravity                  Function from R1 to R1 : (height (m)) → (gravity (m/s²))\n",
+      "\tlatitude                 39.3897\n",
+      "\tlongitude                -8.288964\n",
+      "\ttimezone                 UTC\n",
+      "\n",
+      "Stochastic Attributes:\n",
+      "\twind_velocity_x_factor   1.00000 ± 0.00000 (normal)\n",
+      "\twind_velocity_y_factor   1.00000 ± 0.00000 (normal)\n",
+      "\n",
+      "Stochastic Attributes with choice of values:\n",
+      "\tensemble_member [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]\n"
+     ]
+    }
+   ],
+   "source": [
+    "stochastic_env = StochasticEnvironment(\n",
+    "    environment=env,\n",
+    "    ensemble_member=list(range(env.num_ensemble_members)),\n",
+    ")\n",
+    "\n",
+    "stochastic_env.visualize_attributes()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class=\"alert alert-block alert-info\"> \n",
+    "\n",
+    "#### NOTE\n",
+    "\n",
+    "Always check the `.visualize_attributes()` method of each stochastic object to verify the uncertainties were correctly set.\n",
+    "\n",
+    "</div>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Just to illustrate the potential of this technique, let's randomly generate 5 instances of the environment using the `create_object` method.\n",
+    "\n",
+    "For each instance, we will calculate the wind speed at 1km altitude and store the results in a list."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.3204824786686544, 0.8213012810128237, 0.5276783044255233, 1.7781228206802893, 1.7781228206802893]\n"
+     ]
+    }
+   ],
+   "source": [
+    "wind_speed_at_1000m = []\n",
+    "for i in range(5):\n",
+    "    rnd_env = stochastic_env.create_object()\n",
+    "    wind_speed_at_1000m.append(rnd_env.wind_velocity_x(1000))\n",
+    "\n",
+    "print(wind_speed_at_1000m)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, the wind speed varies between ensemble members.\n",
+    "This demonstrates how the Monte Carlo simulation can capture the variability in wind conditions due to different ensemble members.\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Motor\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now create a `StochasticSolidMotor` object to define the uncertainties associated with the motor.\n",
+    "In this example, we will apply more complex uncertainties to the motor parameters.\n",
+    "\n",
+    "The `StochasticSolidMotor` also has one special parameter which is the `total_impulse`. It lets us alter the total impulse of the motor while maintaining the thrust curve shape. This is particularly useful for motor uncertainties."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reporting the attributes of the `StochasticSolidMotor` object:\n",
+      "\n",
+      "Constant Attributes:\n",
+      "\tburn_out_time                    3.9\n",
+      "\tcenter_of_dry_mass_position      0.317\n",
+      "\tcoordinate_system_orientation    nozzle_to_combustion_chamber\n",
+      "\tdry_I_11                         0.125\n",
+      "\tdry_I_12                         0\n",
+      "\tdry_I_13                         0\n",
+      "\tdry_I_22                         0.125\n",
+      "\tdry_I_23                         0\n",
+      "\tdry_I_33                         0.002\n",
+      "\tdry_mass                         1.815\n",
+      "\tgrain_number                     5\n",
+      "\tinterpolate                      linear\n",
+      "\tthrust_source                    [[0, 0], [0.055, 100.0], [0.092, 1500.0], [0.1, 2000.0], [0.15, 2200.0], [0.2, 1800.0], [0.5, 1950.0], [1.0, 2034.0], [1.5, 2000.0], [2.0, 1900.0], [2.5, 1760.0], [2.9, 1700.0], [3.0, 1650.0], [3.3, 530.0], [3.4, 350.0], [3.9, 0.0]]\n",
+      "\n",
+      "Stochastic Attributes:\n",
+      "\tburn_start_time                  0.00000 ± 0.10000 (binomial)\n",
+      "\tgrain_density                    1815.00000 ± 50.00000 (normal)\n",
+      "\tgrain_initial_height             0.12000 ± 0.00100 (normal)\n",
+      "\tgrain_initial_inner_radius       0.01500 ± 0.00038 (normal)\n",
+      "\tgrain_outer_radius               0.03300 ± 0.00038 (normal)\n",
+      "\tgrain_separation                 0.00500 ± 0.00100 (normal)\n",
+      "\tgrains_center_of_mass_position   0.39700 ± 0.00100 (normal)\n",
+      "\tnozzle_position                  0.00000 ± 0.00100 (normal)\n",
+      "\tnozzle_radius                    0.03300 ± 0.00050 (normal)\n",
+      "\tthroat_radius                    0.01100 ± 0.00050 (normal)\n",
+      "\ttotal_impulse                    6500.00000 ± 1000.00000 (normal)\n"
+     ]
+    }
+   ],
+   "source": [
+    "stochastic_motor = StochasticSolidMotor(\n",
+    "    solid_motor=motor,\n",
+    "    burn_start_time=(0, 0.1, \"binomial\"),\n",
+    "    grains_center_of_mass_position=0.001,\n",
+    "    grain_density=50,\n",
+    "    grain_separation=1 / 1000,\n",
+    "    grain_initial_height=1 / 1000,\n",
+    "    grain_initial_inner_radius=0.375 / 1000,\n",
+    "    grain_outer_radius=0.375 / 1000,\n",
+    "    total_impulse=(6500, 1000),\n",
+    "    throat_radius=0.5 / 1000,\n",
+    "    nozzle_radius=0.5 / 1000,\n",
+    "    nozzle_position=0.001,\n",
+    ")\n",
+    "stochastic_motor.visualize_attributes()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class=\"alert alert-block alert-info\"> \n",
+    "\n",
+    "#### NOTE\n",
+    "\n",
+    "Pay special attention to how different input types are interpreted in the `StochasticSolidMotor` object by checking the printed object:\n",
+    "\n",
+    "\n",
+    "<!-- - ``thrust_source`` was given as a list of 3 items, and is saved as is. This means that the simulation will randomly chose one item of that list, as desired -->\n",
+    "\n",
+    "- ``burn_start_time`` was given as a tuple of 3 items, specifying the nominal value, the standard deviation and the distribuition type\n",
+    "\n",
+    "- ``total_impulse`` was given as a tuple of 2 numbers, so the distribuition type was set to the default: `normal`\n",
+    "\n",
+    "- All other values set for the other parameters in the constructor are simple values, which means they are interpreted as standard deviation and the nominal value is taken from the ``motor``\n",
+    "\n",
+    "- The remaining parameters that are printed are just the nominal values from the ``motor``. In the ``Stochastic`` object they are saved as a list of one item\n",
+    "\n",
+    " </div>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once again, we can illustrate the power of stochastic modeling by generating multiple instances of the `SolidMotor` class using the `StochasticSolidMotor` object.\n",
+    "For each instance, we will calculate the total impulse and store the results in a list. This will show how the uncertainties in the motor parameters affect the total impulse over multiple iterations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[7027.588437139979, 6191.531179311793, 6629.281021408857, 5157.516419345492, 6866.985893654466]\n"
+     ]
+    }
+   ],
+   "source": [
+    "total_impulse = []\n",
+    "for i in range(5):\n",
+    "    rnd_motor = stochastic_motor.create_object()\n",
+    "    total_impulse.append(rnd_motor.total_impulse)\n",
+    "\n",
+    "print(total_impulse)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Rocket\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now create a `StochasticRocket` object to define the uncertainties associated with the rocket."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reporting the attributes of the `StochasticRocket` object:\n",
+      "\n",
+      "Constant Attributes:\n",
+      "\tI_12_without_motor              0\n",
+      "\tI_13_without_motor              0\n",
+      "\tI_23_without_motor              0\n",
+      "\tcoordinate_system_orientation   tail_to_nose\n",
+      "\tpower_off_drag                  Function from R1 to R1 : (Mach Number) → (Drag Coefficient with Power Off)\n",
+      "\tpower_on_drag                   Function from R1 to R1 : (Mach Number) → (Drag Coefficient with Power On)\n",
+      "\n",
+      "Stochastic Attributes:\n",
+      "\tI_11_without_motor              6.32100 ± 0.00000 (normal)\n",
+      "\tI_22_without_motor              6.32100 ± 0.01000 (normal)\n",
+      "\tI_33_without_motor              0.03400 ± 0.01000 (normal)\n",
+      "\tcenter_of_mass_without_motor    0.00000 ± 0.00000 (normal)\n",
+      "\tmass                            15.42600 ± 0.50000 (normal)\n",
+      "\tpower_off_drag_factor           1.00000 ± 0.00000 (normal)\n",
+      "\tpower_on_drag_factor            1.00000 ± 0.00000 (normal)\n",
+      "\tradius                          0.06350 ± 0.00001 (normal)\n"
+     ]
+    }
+   ],
+   "source": [
+    "stochastic_rocket = StochasticRocket(\n",
+    "    rocket=rocket,\n",
+    "    radius=0.0127 / 2000,\n",
+    "    mass=(15.426, 0.5, \"normal\"),\n",
+    "    inertia_11=(6.321, 0),\n",
+    "    inertia_22=0.01,\n",
+    "    inertia_33=0.01,\n",
+    "    center_of_mass_without_motor=0,\n",
+    ")\n",
+    "stochastic_rocket.visualize_attributes()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `StochasticRocket` still needs to have its aerodynamic surfaces and parachutes added. \n",
+    "\n",
+    "We can also create stochastic models for each aerodynamic surface, although this is not mandatory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stochastic_nose_cone = StochasticNoseCone(\n",
+    "    nosecone=nose_cone,\n",
+    "    length=0.001,\n",
+    ")\n",
+    "\n",
+    "stochastic_fin_set = StochasticTrapezoidalFins(\n",
+    "    trapezoidal_fins=fin_set,\n",
+    "    root_chord=0.0005,\n",
+    "    tip_chord=0.0005,\n",
+    "    span=0.0005,\n",
+    ")\n",
+    "\n",
+    "stochastic_tail = StochasticTail(\n",
+    "    tail=tail,\n",
+    "    top_radius=0.001,\n",
+    "    bottom_radius=0.001,\n",
+    "    length=0.001,\n",
+    ")\n",
+    "\n",
+    "stochastic_rail_buttons = StochasticRailButtons(\n",
+    "    rail_buttons=rail_buttons, buttons_distance=0.001\n",
+    ")\n",
+    "\n",
+    "stochastic_main = StochasticParachute(\n",
+    "    parachute=Main,\n",
+    "    cd_s=0.1,\n",
+    "    lag=0.1,\n",
+    ")\n",
+    "\n",
+    "stochastic_drogue = StochasticParachute(\n",
+    "    parachute=Drogue,\n",
+    "    cd_s=0.07,\n",
+    "    lag=0.2,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we must add them to our stochastic rocket, much like we do in the normal Rocket.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stochastic_rocket.add_motor(stochastic_motor, position=0.001)\n",
+    "stochastic_rocket.add_nose(stochastic_nose_cone, position=(1.134, 0.001))\n",
+    "stochastic_rocket.add_trapezoidal_fins(stochastic_fin_set, position=(0.001, \"normal\"))\n",
+    "stochastic_rocket.add_tail(stochastic_tail)\n",
+    "stochastic_rocket.set_rail_buttons(\n",
+    "    stochastic_rail_buttons, lower_button_position=(0.001, \"normal\")\n",
+    ")\n",
+    "stochastic_rocket.add_parachute(stochastic_main)\n",
+    "stochastic_rocket.add_parachute(stochastic_drogue)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class=\"alert alert-block alert-info\"> \n",
+    "\n",
+    "#### NOTE\n",
+    "\n",
+    "The `position` arguments behave just like the other ``Stochastic`` classes parameters\n",
+    "\n",
+    " </div>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now lets check how the `StochasticRocket` handled all these additions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reporting the attributes of the `StochasticRocket` object:\n",
+      "\n",
+      "Constant Attributes:\n",
+      "\tI_12_without_motor              0\n",
+      "\tI_13_without_motor              0\n",
+      "\tI_23_without_motor              0\n",
+      "\tcoordinate_system_orientation   tail_to_nose\n",
+      "\tpower_off_drag                  Function from R1 to R1 : (Mach Number) → (Drag Coefficient with Power Off)\n",
+      "\tpower_on_drag                   Function from R1 to R1 : (Mach Number) → (Drag Coefficient with Power On)\n",
+      "\n",
+      "Stochastic Attributes:\n",
+      "\tI_11_without_motor              6.32100 ± 0.00000 (normal)\n",
+      "\tI_22_without_motor              6.32100 ± 0.01000 (normal)\n",
+      "\tI_33_without_motor              0.03400 ± 0.01000 (normal)\n",
+      "\tcenter_of_mass_without_motor    0.00000 ± 0.00000 (normal)\n",
+      "\tmass                            15.42600 ± 0.50000 (normal)\n",
+      "\tpower_off_drag_factor           1.00000 ± 0.00000 (normal)\n",
+      "\tpower_on_drag_factor            1.00000 ± 0.00000 (normal)\n",
+      "\tradius                          0.06350 ± 0.00001 (normal)\n"
+     ]
+    }
+   ],
+   "source": [
+    "stochastic_rocket.visualize_attributes()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "### Flight\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "After defining the `Flight`, we can create the corresponding `Stochastic` object to define the uncertainties of the input parameters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reporting the attributes of the `StochasticFlight` object:\n",
+      "\n",
+      "Constant Attributes:\n",
+      "\trail_length           5\n",
+      "\n",
+      "Stochastic Attributes:\n",
+      "\theading               53.00000 ± 2.00000 (normal)\n",
+      "\tinclination           84.70000 ± 1.00000 (normal)\n"
+     ]
+    }
+   ],
+   "source": [
+    "stochastic_flight = StochasticFlight(\n",
+    "    flight=test_flight,\n",
+    "    inclination=(84.7, 1),  # mean= 84.7, std=1\n",
+    "    heading=(53, 2),  # mean= 53, std=2\n",
+    ")\n",
+    "stochastic_flight.visualize_attributes()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Step 2: Starting the Monte Carlo Simulations\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, let's invoke the `MonteCarlo` class, we are going to need a filename to initialize it.\n",
+    "The filename will be used either to save the results of the simulations or to load them\n",
+    "from a previous ran simulation.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The following input file was imported: monte_carlo_analysis_outputs/monte_carlo_class_example.inputs.txt\n",
+      "A total of 1000 simulations results were loaded from the following output file: monte_carlo_analysis_outputs/monte_carlo_class_example.outputs.txt\n",
+      "\n",
+      "The following error file was imported: monte_carlo_analysis_outputs/monte_carlo_class_example.errors.txt\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\guiga\\Documents\\github\\RocketPy\\rocketpy\\simulation\\monte_carlo.py:105: UserWarning: This class is still under testing and some attributes may be changed in next versions\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_dispersion = MonteCarlo(\n",
+    "    filename=\"monte_carlo_analysis_outputs/monte_carlo_class_example\",\n",
+    "    environment=stochastic_env,\n",
+    "    rocket=stochastic_rocket,\n",
+    "    flight=stochastic_flight,\n",
+    ")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, let's simulate our flights. \n",
+    "We can run the simulations using the method `MonteCarlo.simulate()`.\n",
+    "\n",
+    "Set `append=False` to overwrite the previous results, or `append=True` to add the new results to the previous ones.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Completed 1000 iterations. Total CPU time: 1021.7 s. Total wall time: 1262.5 sme left: 0 s   \n",
+      "Saving results.\n",
+      "Results saved to monte_carlo_analysis_outputs/monte_carlo_class_example.outputs.txt\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_dispersion.simulate(number_of_simulations=1000, append=False)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualizing the results\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we finally have the results of our Monte Carlo simulations loaded!\n",
+    "Let's play with them.\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, we can print numerical information regarding the results of the simulations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# You only need to import results if you did not run the simulations\n",
+    "# test_dispersion.import_results()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1000"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_dispersion.num_of_loaded_sims"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Monte Carlo Simulation by RocketPy\n",
+      "Data Source:  monte_carlo_analysis_outputs/monte_carlo_class_example\n",
+      "Number of simulations:  1000\n",
+      "Results: \n",
+      "\n",
+      "                Parameter            Mean       Std. Dev.\n",
+      "------------------------------------------------------------\n",
+      "                   apogee        3406.545         643.312\n",
+      "out_of_rail_stability_margin           2.673           0.078\n",
+      "     lateral_surface_wind          -1.808           0.643\n",
+      "          impact_velocity          -5.440           0.083\n",
+      "                 x_impact         877.812         221.423\n",
+      "          max_mach_number           0.831           0.131\n",
+      "         out_of_rail_time           0.361           0.026\n",
+      "                 apogee_y         452.203         107.950\n",
+      "     out_of_rail_velocity          25.664           2.207\n",
+      "                 apogee_x         342.921         124.187\n",
+      " initial_stability_margin           2.600           0.079\n",
+      "                  t_final         300.315          35.615\n",
+      "              apogee_time          25.615           2.107\n",
+      "     frontal_surface_wind           0.793           0.410\n",
+      "                 y_impact         325.183         165.888\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_dispersion.prints.all()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Secondly, we can plot the results of the simulations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6637e2fc301847c786b94e55e1367974",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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width=1200.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_dispersion.plots.ellipses(xlim=(-200, 3500), ylim=(-200, 3500))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a76c44781f3c4823a5bd254b083af1e6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' 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+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0fed13c8dfd6431b9413e6ef7794a801",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "64a3d86674b342eb995b30e5373d6354",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7b11444e315f430aabba44f1e917017c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b141ce8032c8457994ec93b337219d9e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e2443183fd8d4c8ebb761a25be566fda",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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R8vT0VGxsrDp06KBWrVpp5MiROnz4sCIiIrR69Wp99tlnGjJkiOMXZWRkpLp06aIZM2bo9OnTatKkiTZu3Kh9+/ZJurbDqn5+fmrevLkmT56snJwcVa5cWatXr863cuQqERER6tWrl959913HYcxvvvlG77//vjp16uS222g89NBD+vDDD+Xv76969eopOTlZX375pcqXL+/ULzExUcuXL1dSUpJuu+02Sb+HiCeeeEJvv/12vgt0XOXee+9VuXLl1KtXLw0aNEg2m00ffvhhvtDi4eGht99+Wx06dFDDhg3Vp08fVapUST/++KN2796tVatWmVJvQe644w41adJEI0aM0JkzZxQYGKj58+fr8uXLLhszNTVVDz/8sNq2bavk5GR99NFHevzxxxURESHp91A6YcIEjRgxQocPH1anTp1UtmxZpaamasmSJerfv3++2/EAxR0BELgBgwYN0n/+8x+tXr1aWVlZqlKliiZMmKAXXnjB0adz584aOHCg5s+fr48++kiGYSg2NlYeHh76z3/+ozFjxmjBggVKTExU1apV9frrrzuujs3zwQcfKCQkRJ988omWLFmiNm3aaMGCBapdu7Z8fHyuqdZ58+Zp4MCBmj17tgzD0IMPPqgVK1YoNDS0SN+TK/nXv/6l6tWrKykpSUuWLFFISIhGjBihsWPHmjJ+Qd544w15enrq448/1qVLl9S0aVN9+eWXjlVXSfrf//6noUOHqkOHDurVq5ejvXv37vr000/14osvql27dgVeeFPUypcvr2XLlum5557TqFGjVK5cOT3xxBNq3bq1U83S7yvH69evV0JCgqZOnSq73a7w8HDHfSHd6eOPP9bTTz+tSZMmKSAgQH379lWrVq0c98wsagsWLHDcK7FEiRIaMGCAXn/9dac+w4cPV61atTR9+nQlJCRI+v2inAcffFAPP/ywS+oC3MlmuPt4AIDrsmPHDjVq1EgfffSRunfv7u5yAADFCOcAAsXAb7/9lq9txowZ8vDw+NtvygAA4K84BAwUA5MnT1ZKSopatWqlEiVKaMWKFVqxYoX69++f735oMF9ubq5+/fXXq/YpU6ZMvtuJFAdnzpxRdnb2Fbd7enrmu48ggJsfh4CBYmDNmjVKSEjQnj17lJmZqdtvv109evTQyJEjnb45Au5x+PDhvz0HcOzYsRo3bpw5BRWhli1bauPGjVfcXqVKFccNlQEUHwRAALhBly5d0ldffXXVPtWrV1f16tVNqqjopKSkXPVbQXx9fdW0aVMTKwJQFAiAAAAAFsNFIAAAABbDyUM3wG6369ixYypbtqxLvuMUAAAUPcMwdP78eYWGhsrDw5prYQTAG3Ds2DGuwAQAoJg6evSo49t9rIYAeAPKli0r6fcfID8/PzdXAwAArkVGRobCwsIcv8etiAB4A/IO+/r5+REAAQAoZqx8+pY1D3wDAABYGAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACymhLsLAICbVdXhy91dQqEdntTe3SUAKAZYAQQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZTLAPgxIkT9X//938qW7asKlasqE6dOumnn35y6nPp0iXFxcWpfPnyKlOmjLp06aITJ0449Tly5Ijat2+vUqVKqWLFinrhhRd0+fJlM6cCAABgumIZADdu3Ki4uDht2bJFa9asUU5Ojh588EFduHDB0Wfo0KH6/PPPtXDhQm3cuFHHjh1T586dHdtzc3PVvn17ZWdna/PmzXr//feVlJSkMWPGuGNKAAAAprEZhmG4u4gb9euvv6pixYrauHGjmjdvrvT0dAUFBWnevHn6xz/+IUn68ccfVbduXSUnJ6tJkyZasWKFHnroIR07dkzBwcGSpDlz5mjYsGH69ddf5eXl9bfjZmRkyN/fX+np6fLz83PpHAGYr+rw5e4uodAOT2rv7hKAmx6/v4vpCuBfpaenS5ICAwMlSSkpKcrJyVGbNm0cferUqaPbb79dycnJkqTk5GQ1aNDAEf4kKTo6WhkZGdq9e3eB42RlZSkjI8PpAQAAUNwU+wBot9s1ZMgQNW3aVPXr15ckpaWlycvLSwEBAU59g4ODlZaW5ujz5/CXtz1vW0EmTpwof39/xyMsLKyIZwMAAOB6xT4AxsXF6YcfftD8+fNdPtaIESOUnp7ueBw9etTlYwIAABS1Eu4u4EYMGDBAy5Yt06ZNm3Tbbbc52kNCQpSdna1z5845rQKeOHFCISEhjj7ffPON0/7yrhLO6/NX3t7e8vb2LuJZAAAAmKtYrgAahqEBAwZoyZIlWrdunapVq+a0PTIyUiVLltTatWsdbT/99JOOHDmiqKgoSVJUVJR27dqlkydPOvqsWbNGfn5+qlevnjkTAQAAcINiuQIYFxenefPm6bPPPlPZsmUd5+z5+/vL19dX/v7+6tu3r+Lj4xUYGCg/Pz8NHDhQUVFRatKkiSTpwQcfVL169dSjRw9NnjxZaWlpGjVqlOLi4ljlAwAAt7RiGQDffvttSVLLli2d2hMTE9W7d29J0vTp0+Xh4aEuXbooKytL0dHReuuttxx9PT09tWzZMj3zzDOKiopS6dKl1atXL40fP96saQAAALjFLXEfQHfhPkLArY37AAK3Jn5/F9NzAAEAAHD9CIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDHF8j6AAIqf4nhLFQC4VbECCAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwmBLuLgAAUHSqDl/u7hIK7fCk9u4uAbAcVgABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGJMC4Dbtm3Trl27HM8/++wzderUSS+99JKys7PNKgMAAMDyTAuATz/9tPbt2ydJOnTokGJjY1WqVCktXLhQL774olllAAAAWJ5pAXDfvn1q2LChJGnhwoVq3ry55s2bp6SkJH366admlQEAAGB5pgVAwzBkt9slSV9++aViYmIkSWFhYTp16pRZZQAAAFieaQHw7rvv1oQJE/Thhx9q48aNat++vSQpNTVVwcHBZpUBAABgeaYFwBkzZmjbtm0aMGCARo4cqRo1akiSFi1apHvvvdesMgAAACyvhFkD3XnnnU5XAed5/fXX5enpaVYZAAAAlmfqfQDPnTunf/3rXxoxYoTOnDkjSdqzZ49OnjxpZhkAAACWZtoK4M6dO9W6dWsFBATo8OHD6tevnwIDA7V48WIdOXJEH3zwgVmlAAAAWJppK4Dx8fHq06eP9u/fLx8fH0d7TEyMNm3aZFYZAAAAlmdaAPz222/19NNP52uvXLmy0tLSzCoDAADA8kwLgN7e3srIyMjXvm/fPgUFBZlVBgAAgOWZFgAffvhhjR8/Xjk5OZIkm82mI0eOaNiwYerSpYtZZQAAAFieaQFw6tSpyszMVMWKFfXbb7+pRYsWqlGjhsqWLatXXnnFrDIAAAAsz7SrgP39/bVmzRp9/fXX+v7775WZmam77rpLbdq0MasEAAAAyMQAmKdp06Zq2rSp2cMCAADgD6YdAh40aJBmzpyZr/3NN9/UkCFDzCoDAADA8kwLgJ9++mmBK3/33nuvFi1aZFYZAAAAlmdaADx9+rT8/f3ztfv5+enUqVOF2temTZvUoUMHhYaGymazaenSpU7be/fuLZvN5vRo27atU58zZ86oe/fu8vPzU0BAgPr27avMzMxCzwsAAKC4MS0A1qhRQytXrszXvmLFClWvXr1Q+7pw4YIiIiI0e/bsK/Zp27atjh8/7nh88sknTtu7d++u3bt3a82aNVq2bJk2bdqk/v37F6oOAACA4si0i0Di4+M1YMAA/frrr7r//vslSWvXrtXUqVM1Y8aMQu2rXbt2ateu3VX7eHt7KyQkpMBte/fu1cqVK/Xtt9/q7rvvliTNmjVLMTExmjJlikJDQwtVDwAAQHFiWgB88sknlZWVpVdeeUUvv/yyJKlq1ap6++231bNnzyIfb8OGDapYsaLKlSun+++/XxMmTFD58uUlScnJyQoICHCEP0lq06aNPDw8tHXrVj3yyCNFXg8AAMDNwtTbwDzzzDN65pln9Ouvv8rX11dlypRxyTht27ZV586dVa1aNR08eFAvvfSS2rVrp+TkZHl6eiotLU0VK1Z0ek2JEiUUGBh41e8lzsrKUlZWluN5QV9tBwAAcLMz/T6Aklz+3b+xsbGOPzdo0EB33nmnwsPDtWHDBrVu3fq69ztx4kQlJCQURYkAAABuY9pFICdOnFCPHj0UGhqqEiVKyNPT0+nhStWrV1eFChV04MABSVJISIhOnjzp1Ofy5cs6c+bMFc8blKQRI0YoPT3d8Th69KhL6wYAAHAF01YAe/furSNHjmj06NGqVKmSbDabWUPrf//7n06fPq1KlSpJkqKionTu3DmlpKQoMjJSkrRu3TrZ7XY1btz4ivvx9vaWt7e3KTUDAAC4imkB8KuvvtJ///tfNWzY8Ib3lZmZ6VjNk6TU1FTt2LFDgYGBCgwMVEJCgrp06aKQkBAdPHhQL774omrUqKHo6GhJUt26ddW2bVv169dPc+bMUU5OjgYMGKDY2FiuAAYAALc80w4Bh4WFyTCMItnXd999p0aNGqlRo0aSfr/FTKNGjTRmzBh5enpq586devjhh1WrVi317dtXkZGR+u9//+u0evfxxx+rTp06at26tWJiYtSsWTO9++67RVIfAADAzcxmFFUq+xurV6/W1KlT9c4776hq1apmDOlyGRkZ8vf3V3p6uvz8/NxdDnBTqzp8ubtLwE3q8KT27i4BFsPvbxMPAXfr1k0XL15UeHi4SpUqpZIlSzptP3PmjFmlAAAAWJppAbCw3/YBAAAA1zAtAPbq1cusoQAAAHAVpl0EIkkHDx7UqFGj9Nhjjznuw7dixQrt3r3bzDIAAAAszbQAuHHjRjVo0EBbt27V4sWLlZmZKUn6/vvvNXbsWLPKAAAAsDzTAuDw4cM1YcIErVmzRl5eXo72+++/X1u2bDGrDAAAAMszLQDu2rVLjzzySL72ihUr6tSpU2aVAQAAYHmmBcCAgAAdP348X/v27dtVuXJls8oAAACwPNMCYGxsrIYNG6a0tDTZbDbZ7XZ9/fXXev7559WzZ0+zygAAALA80wLgq6++qjp16igsLEyZmZmqV6+emjdvrnvvvVejRo0yqwwAAADLM+U+gIZhKC0tTTNnztSYMWO0a9cuZWZmqlGjRqpZs6YZJQAAAOAPpgXAGjVqaPfu3apZs6bCwsLMGBYAAAAFMOUQsIeHh2rWrKnTp0+bMRwAAACuwrRzACdNmqQXXnhBP/zwg1lDAgAAoACmfRdwz549dfHiRUVERMjLy0u+vr5O28+cOWNWKQAAAJZmWgCcMWOGWUMBt7yqw5e7uwQAQDFmSgDMycnRxo0bNXr0aFWrVs2MIQEAAHAFppwDWLJkSX366admDAUAAIC/YdpFIJ06ddLSpUvNGg4AAABXYNo5gDVr1tT48eP19ddfKzIyUqVLl3baPmjQILNKAQAAsDTTAuDcuXMVEBCglJQUpaSkOG2z2WwEQAAAAJOYFgBTU1PNGgoAAABXYdo5gAAAALg5mLYC+OSTT151+3vvvWdSJQAAANZmWgA8e/as0/OcnBz98MMPOnfunO6//36zygAAALA80wLgkiVL8rXZ7XY988wzCg8PN6sMAAAAy3PrOYAeHh6Kj4/X9OnT3VkGAACApbj9IpCDBw/q8uXL7i4DAADAMkw7BBwfH+/03DAMHT9+XMuXL1evXr3MKgMAAMDyTAuA27dvd3ru4eGhoKAgTZ069W+vEAYAAEDRMS0Arl+/3qyhAAAAcBWmnQOYmpqq/fv352vfv3+/Dh8+bFYZAAAAlmdaAOzdu7c2b96cr33r1q3q3bu3WWUAAABYnmkBcPv27WratGm+9iZNmmjHjh1mlQEAAGB5pgVAm82m8+fP52tPT09Xbm6uWWUAAABYnmkBsHnz5po4caJT2MvNzdXEiRPVrFkzs8oAAACwPNOuAn7ttdfUvHlz1a5dW/fdd58k6b///a8yMjK0bt06s8oAAACwPNNWAOvVq6edO3eqa9euOnnypM6fP6+ePXvqxx9/VP369c0qAwAAwPJMWwGUpNDQUL366qtmDgkAAIC/MG0FMDExUQsXLszXvnDhQr3//vtmlQEAAGB5pgXAiRMnqkKFCvnaK1asyKogAACAiUwLgEeOHFG1atXytVepUkVHjhwxqwwAAADLMy0AVqxYUTt37szX/v3336t8+fJmlQEAAGB5pgXAxx57TIMGDdL69euVm5ur3NxcrVu3ToMHD1ZsbKxZZQAAAFieaVcBv/zyyzp8+LBat26tEiV+H9Zut6tnz56cAwgAAGAi0wKgl5eXFixYoJdfflnff/+9fH191aBBA1WpUsWsEgAAACCT7wMoSYGBgWrVqlWBVwQDAADA9Uw5B/DcuXOKi4tThQoVFBwcrODgYFWoUEEDBgzQuXPnzCgBAAAAf3D5CuCZM2cUFRWlX375Rd27d1fdunUlSXv27FFSUpLWrl2rzZs3q1y5cq4uBQAAADIhAI4fP15eXl46ePCggoOD82178MEHNX78eE2fPt3VpQAAAEAmHAJeunSppkyZki/8SVJISIgmT56sJUuWuLoMAAAA/MHlAfD48eO64447rri9fv36SktLc3UZAAAA+IPLA2CFChV0+PDhK25PTU1VYGCgq8sAAADAH1weAKOjozVy5EhlZ2fn25aVlaXRo0erbdu2ri4DAAAAfzDlIpC7775bNWvWVFxcnOrUqSPDMLR371699dZbysrK0ocffujqMgAAAPAHlwfA2267TcnJyXr22Wc1YsQIGYYhSbLZbHrggQf05ptvKiwszNVlAAAA4A+mfBNItWrVtGLFCp09e1b79++XJNWoUYNz/wAAANzA1K+CK1eunO655x4zhwQAAMBfmPJVcAAAALh5EAABAAAshgAIAABgMS4NgHfddZfOnj0r6ffbwVy8eNGVwwEAAOAauDQA7t27VxcuXJAkJSQkKDMz05XDAQAA4Bq49Crghg0bqk+fPmrWrJkMw9CUKVNUpkyZAvuOGTPGlaUAAADgDy4NgElJSRo7dqyWLVsmm82mFStWqESJ/EPabDYCIAAAgElcGgBr166t+fPnS5I8PDy0du1aVaxY0ZVDAgAA4G+YdiNou91u1lAAAAC4ClO/CeTgwYOaMWOG9u7dK0mqV6+eBg8erPDwcDPLAAAAsDTT7gO4atUq1atXT998843uvPNO3Xnnndq6davuuOMOrVmzxqwyAAAALM+0FcDhw4dr6NChmjRpUr72YcOG6YEHHjCrFAAAAEszbQVw79696tu3b772J598Unv27CnUvjZt2qQOHTooNDRUNptNS5cuddpuGIbGjBmjSpUqydfXV23atNH+/fud+pw5c0bdu3eXn5+fAgIC1LdvX+5TCAAALMG0ABgUFKQdO3bka9+xY0ehrwy+cOGCIiIiNHv27AK3T548WTNnztScOXO0detWlS5dWtHR0bp06ZKjT/fu3bV7926tWbNGy5Yt06ZNm9S/f/9C1QEAAFAcmXYIuF+/furfv78OHTqke++9V5L09ddf67XXXlN8fHyh9tWuXTu1a9euwG2GYWjGjBkaNWqUOnbsKEn64IMPFBwcrKVLlyo2NlZ79+7VypUr9e233+ruu++WJM2aNUsxMTGaMmWKQkNDb2CmAAAANzfTAuDo0aNVtmxZTZ06VSNGjJAkhYaGaty4cRo0aFCRjZOamqq0tDS1adPG0ebv76/GjRsrOTlZsbGxSk5OVkBAgCP8SVKbNm3k4eGhrVu36pFHHimyegAAAG42pgVAm82moUOHaujQoTp//rwkqWzZskU+TlpamiQpODjYqT04ONixLS0tLd9h5xIlSigwMNDRpyBZWVnKyspyPM/IyCiqsgEAAExj2jmAf1a2bFmXhD9Xmzhxovz9/R2PsLAwd5cEAABQaG4JgK4UEhIiSTpx4oRT+4kTJxzbQkJCdPLkSaftly9f1pkzZxx9CjJixAilp6c7HkePHi3i6gEAAFzvlguA1apVU0hIiNauXetoy8jI0NatWxUVFSVJioqK0rlz55SSkuLos27dOtntdjVu3PiK+/b29pafn5/TAwAAoLgx9avgikpmZqYOHDjgeJ6amqodO3YoMDBQt99+u4YMGaIJEyaoZs2aqlatmkaPHq3Q0FB16tRJklS3bl21bdtW/fr105w5c5STk6MBAwYoNjaWK4ABAMAtz5QVwJycHLVu3TrfzZiv13fffadGjRqpUaNGkqT4+Hg1atRIY8aMkSS9+OKLGjhwoPr376//+7//U2ZmplauXCkfHx/HPj7++GPVqVNHrVu3VkxMjJo1a6Z33323SOoDAAC4mdkMwzDMGCgoKEibN29WzZo1zRjOFBkZGfL391d6ejqHg2GqqsOXu7sEoMgcntTe3SXAYvj9beI5gE888YTmzp1r1nAAAAC4AtPOAbx8+bLee+89ffnll4qMjFTp0qWdtk+bNs2sUgAAACzNtAD4ww8/6K677pIk7du3z2mbzWYzqwwAAADLMy0Arl+/3qyhAAAAcBWm3wfwwIEDWrVqlX777TdJkknXoAAAAOAPpgXA06dPq3Xr1qpVq5ZiYmJ0/PhxSVLfvn313HPPmVUGAACA5ZkWAIcOHaqSJUvqyJEjKlWqlKO9W7duWrlypVllAAAAWJ5p5wCuXr1aq1at0m233ebUXrNmTf38889mlQEAAGB5pgXACxcuOK385Tlz5oy8vb3NKgMAcJMpjjc25+bVKO5MOwR833336YMPPnA8t9lsstvtmjx5slq1amVWGQAAAJZn2grg5MmT1bp1a3333XfKzs7Wiy++qN27d+vMmTP6+uuvzSoDAADA8kxbAaxfv7727dunZs2aqWPHjrpw4YI6d+6s7du3Kzw83KwyAAAALM+0FUBJ8vf318iRI80cEgAAAH9hagA8e/as5s6dq71790qS6tWrpz59+igwMNDMMgAAACzNtEPAmzZtUtWqVTVz5kydPXtWZ8+e1cyZM1WtWjVt2rTJrDIAAAAsz7QVwLi4OHXr1k1vv/22PD09JUm5ubl69tlnFRcXp127dplVCgAAgKWZtgJ44MABPffcc47wJ0menp6Kj4/XgQMHzCoDAADA8kwLgHfddZfj3L8/27t3ryIiIswqAwAAwPJcegh4586djj8PGjRIgwcP1oEDB9SkSRNJ0pYtWzR79mxNmjTJlWUAAADgT2yGYRiu2rmHh4dsNpv+bgibzabc3FxXleEyGRkZ8vf3V3p6uvz8/NxdDiykOH51FnAr4avgijd+f7t4BTA1NdWVuweKBGEKAGA1Lg2AVapUceXuAQAAcB1MvRH0sWPH9NVXX+nkyZOy2+1O2wYNGmRmKQAAAJZlWgBMSkrS008/LS8vL5UvX142m82xzWazEQABAABMYloAHD16tMaMGaMRI0bIw8O0u88AAADgL0xLYhcvXlRsbCzhDwAAwM1MS2N9+/bVwoULzRoOAAAAV2DaIeCJEyfqoYce0sqVK9WgQQOVLFnSafu0adPMKgUAAMDSTA2Aq1atUu3atSUp30UgAAAAMIdpAXDq1Kl677331Lt3b7OGBAAAQAFMOwfQ29tbTZs2NWs4AAAAXIFpAXDw4MGaNWuWWcMBAADgCkw7BPzNN99o3bp1WrZsme644458F4EsXrzYrFIAAAAszbQAGBAQoM6dO5s1HAAAAK7AtACYmJho1lAAAAC4Cr6WAwAAwGJMWwGsVq3aVe/3d+jQIbNKAQAAsDTTAuCQIUOcnufk5Gj79u1auXKlXnjhBbPKAAAAsDzTAuDgwYMLbJ89e7a+++47s8oAAACwPLefA9iuXTt9+umn7i4DAADAMtweABctWqTAwEB3lwEAAGAZph0CbtSokdNFIIZhKC0tTb/++qveeusts8oAAACwPNMCYKdOnZyee3h4KCgoSC1btlSdOnXMKgMAAMDyTAuAY8eONWsoAAAAXIXbzwEEAACAuVy+Aujh4XHVG0BLks1m0+XLl11dCgAAAGRCAFyyZMkVtyUnJ2vmzJmy2+2uLgMAAAB/cHkA7NixY762n376ScOHD9fnn3+u7t27a/z48a4uAwAAAH8w9RzAY8eOqV+/fmrQoIEuX76sHTt26P3331eVKlXMLAMAAMDSTAmA6enpGjZsmGrUqKHdu3dr7dq1+vzzz1W/fn0zhgcAAMCfuPwQ8OTJk/Xaa68pJCREn3zySYGHhAEAAGAem2EYhisH8PDwkK+vr9q0aSNPT88r9lu8eLEry3CJjIwM+fv7Kz09XX5+fu4uB9ep6vDl7i4BQDFzeFJ7d5eAG8DvbxNWAHv27Pm3t4EBAACAeVweAJOSklw9BAAAAAqBbwIBAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWc8sGwHHjxslmszk96tSp49h+6dIlxcXFqXz58ipTpoy6dOmiEydOuLFiAAAAc9yyAVCS7rjjDh0/ftzx+Oqrrxzbhg4dqs8//1wLFy7Uxo0bdezYMXXu3NmN1QIAAJijhLsLcKUSJUooJCQkX3t6errmzp2refPm6f7775ckJSYmqm7dutqyZYuaNGlidqkAAACmuaVXAPfv36/Q0FBVr15d3bt315EjRyRJKSkpysnJUZs2bRx969Spo9tvv13JyclX3F9WVpYyMjKcHgAAAMXNLRsAGzdurKSkJK1cuVJvv/22UlNTdd999+n8+fNKS0uTl5eXAgICnF4THBystLS0K+5z4sSJ8vf3dzzCwsJcPAsAAICid8seAm7Xrp3jz3feeacaN26sKlWq6N///rd8fX2va58jRoxQfHy843lGRgYhEAAAFDu37ArgXwUEBKhWrVo6cOCAQkJClJ2drXPnzjn1OXHiRIHnDObx9vaWn5+f0wMAAKC4sUwAzMzM1MGDB1WpUiVFRkaqZMmSWrt2rWP7Tz/9pCNHjigqKsqNVQIAALjeLXsI+Pnnn1eHDh1UpUoVHTt2TGPHjpWnp6cee+wx+fv7q2/fvoqPj1dgYKD8/Pw0cOBARUVFcQUwAAC45d2yAfB///ufHnvsMZ0+fVpBQUFq1qyZtmzZoqCgIEnS9OnT5eHhoS5duigrK0vR0dF666233Fw1AACA69kMwzDcXURxlZGRIX9/f6Wnp3M+YDFWdfhyd5cAoJg5PKm9u0vADeD3t4XOAQQAAMDvCIAAAAAWc8ueAwgAgKsUx1NHOGyNP2MFEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAspoS7C8Ctperw5e4uAQAA/A1WAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsJgS7i4AV1Z1+HJ3lwAAAG5BrAACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsJgS7i4AAAC4XtXhy91dQqEdntTe3SXcslgBBAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFmP5ADh79mxVrVpVPj4+aty4sb755ht3lwQAAOBSlg6ACxYsUHx8vMaOHatt27YpIiJC0dHROnnypLtLAwAAcBlLB8Bp06apX79+6tOnj+rVq6c5c+aoVKlSeu+999xdGgAAgMtY9ruAs7OzlZKSohEjRjjaPDw81KZNGyUnJxf4mqysLGVlZTmep6enS5IyMjJcUqM966JL9gsAQHHgqt+vefs1DMMl+y8OLBsAT506pdzcXAUHBzu1BwcH68cffyzwNRMnTlRCQkK+9rCwMJfUCACAlfnPcO3+z58/L39/f9cOcpOybAC8HiNGjFB8fLzjud1u15kzZ1S+fHnZbDY3VlY4GRkZCgsL09GjR+Xn5+fuckzDvJm3FTBv5m0VNzJ3wzB0/vx5hYaGuqi6m59lA2CFChXk6empEydOOLWfOHFCISEhBb7G29tb3t7eTm0BAQGuKtHl/Pz8LPcPhsS8rYZ5Wwvztp7rnbtVV/7yWPYiEC8vL0VGRmrt2rWONrvdrrVr1yoqKsqNlQEAALiWZVcAJSk+Pl69evXS3XffrXvuuUczZszQhQsX1KdPH3eXBgAA4DKWDoDdunXTr7/+qjFjxigtLU0NGzbUypUr810Ycqvx9vbW2LFj8x3OvtUxb+ZtBcybeVuFledeFGyGla+BBgAAsCDLngMIAABgVQRAAAAAiyEAAgAAWAwBEAAAwGIIgLeo2bNnq2rVqvLx8VHjxo31zTffXLFvUlKSbDab08PHx8fEaotOYeYtSefOnVNcXJwqVaokb29v1apVS1988YVJ1Radwsy7ZcuW+T5vm82m9u3bm1hx0Sjs5z1jxgzVrl1bvr6+CgsL09ChQ3Xp0iWTqi06hZl3Tk6Oxo8fr/DwcPn4+CgiIkIrV640sdqisWnTJnXo0EGhoaGy2WxaunTp375mw4YNuuuuu+Tt7a0aNWooKSnJ5XUWtcLO+/jx43r88cdVq1YteXh4aMiQIabUWdQKO+/FixfrgQceUFBQkPz8/BQVFaVVq1aZU2wxRQC8BS1YsEDx8fEaO3astm3bpoiICEVHR+vkyZNXfI2fn5+OHz/uePz8888mVlw0Cjvv7OxsPfDAAzp8+LAWLVqkn376Sf/v//0/Va5c2eTKb0xh57148WKnz/qHH36Qp6enHn30UZMrvzGFnfe8efM0fPhwjR07Vnv37tXcuXO1YMECvfTSSyZXfmMKO+9Ro0bpnXfe0axZs7Rnzx7985//1COPPKLt27ebXPmNuXDhgiIiIjR79uxr6p+amqr27durVatW2rFjh4YMGaKnnnqq2IWCws47KytLQUFBGjVqlCIiIlxcnesUdt6bNm3SAw88oC+++EIpKSlq1aqVOnToUOx+zk1l4JZzzz33GHFxcY7nubm5RmhoqDFx4sQC+ycmJhr+/v4mVec6hZ3322+/bVSvXt3Izs42q0SXKOy8/2r69OlG2bJljczMTFeV6BKFnXdcXJxx//33O7XFx8cbTZs2dWmdRa2w865UqZLx5ptvOrV17tzZ6N69u0vrdCVJxpIlS67a58UXXzTuuOMOp7Zu3boZ0dHRLqzMta5l3n/WokULY/DgwS6rxyyFnXeeevXqGQkJCUVf0C2CFcBbTHZ2tlJSUtSmTRtHm4eHh9q0aaPk5OQrvi4zM1NVqlRRWFiYOnbsqN27d5tRbpG5nnn/5z//UVRUlOLi4hQcHKz69evr1VdfVW5urlll37Dr/bz/bO7cuYqNjVXp0qVdVWaRu55533vvvUpJSXEcLj106JC++OILxcTEmFJzUbieeWdlZeU7pcPX11dfffWVS2t1t+TkZKf3SZKio6Ov+e8Fije73a7z588rMDDQ3aXctAiAt5hTp04pNzc337eZBAcHKy0trcDX1K5dW++9954+++wzffTRR7Lb7br33nv1v//9z4ySi8T1zPvQoUNatGiRcnNz9cUXX2j06NGaOnWqJkyYYEbJReJ65v1n33zzjX744Qc99dRTrirRJa5n3o8//rjGjx+vZs2aqWTJkgoPD1fLli2L1SHg65l3dHS0pk2bpv3798tut2vNmjWO0wBuZWlpaQW+TxkZGfrtt9/cVBXMMmXKFGVmZqpr167uLuWmRQCEoqKi1LNnTzVs2FAtWrTQ4sWLFRQUpHfeecfdpbmU3W5XxYoV9e677yoyMlLdunXTyJEjNWfOHHeXZpq5c+eqQYMGuueee9xdistt2LBBr776qt566y1t27ZNixcv1vLly/Xyyy+7uzSXeuONN1SzZk3VqVNHXl5eGjBggPr06SMPD/75x61p3rx5SkhI0L///W9VrFjR3eXctCz9XcC3ogoVKsjT01MnTpxwaj9x4oRCQkKuaR8lS5ZUo0aNdODAAVeU6BLXM+9KlSqpZMmS8vT0dLTVrVtXaWlpys7OlpeXl0trLgo38nlfuHBB8+fP1/jx411Zoktcz7xHjx6tHj16OFY7GzRooAsXLqh///4aOXJksQhE1zPvoKAgLV26VJcuXdLp06cVGhqq4cOHq3r16maU7DYhISEFvk9+fn7y9fV1U1Vwtfnz5+upp57SwoUL850CAGc3/794KBQvLy9FRkZq7dq1jja73a61a9cqKirqmvaRm5urXbt2qVKlSq4qs8hdz7ybNm2qAwcOyG63O9r27dunSpUqFYvwJ93Y571w4UJlZWXpiSeecHWZRe565n3x4sV8IS8v/BvF5CvRb+Tz9vHxUeXKlXX58mV9+umn6tixo6vLdauoqCin90mS1qxZc83/DqL4+eSTT9SnTx998sknxfK2VqZz91UoKHrz5883vL29jaSkJGPPnj1G//79jYCAACMtLc0wDMPo0aOHMXz4cEf/hIQEY9WqVcbBgweNlJQUIzY21vDx8TF2797trilcl8LO+8iRI0bZsmWNAQMGGD/99JOxbNkyo2LFisaECRPcNYXrUth552nWrJnRrVs3s8stMoWd99ixY42yZcsan3zyiXHo0CFj9erVRnh4uNG1a1d3TeG6FHbeW7ZsMT799FPj4MGDxqZNm4z777/fqFatmnH27Fk3zeD6nD9/3ti+fbuxfft2Q5Ixbdo0Y/v27cbPP/9sGIZhDB8+3OjRo4ej/6FDh4xSpUoZL7zwgrF3715j9uzZhqenp7Fy5Up3TeG6FHbehmE4+kdGRhqPP/64sX379mL373lh5/3xxx8bJUqUMGbPnm0cP37c8Th37py7pnDTIwDeombNmmXcfvvthpeXl3HPPfcYW7ZscWxr0aKF0atXL8fzIUOGOPoGBwcbMTExxrZt29xQ9Y0rzLwNwzA2b95sNG7c2PD29jaqV69uvPLKK8bly5dNrvrGFXbeP/74oyHJWL16tcmVFq3CzDsnJ8cYN26cER4ebvj4+BhhYWHGs88+W+yCkGEUbt4bNmww6tata3h7exvly5c3evToYfzyyy9uqPrGrF+/3pCU75E31169ehktWrTI95qGDRsaXl5eRvXq1Y3ExETT675R1zPvgvpXqVLF9NpvRGHn3aJFi6v2R342wygmxz4AAABQJDgHEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAi/n/o2MFSZdomUAAAAAASUVORK5CYII=",
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+       "\n",
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+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1e090e37cc3a4837b5dcce88290514ca",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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z6o7OxsvfbaawoJCdGhQ4eKvb+aNWsqKChI8+bNU/ny5VW2bFm1aNGiyPMTr0RAQIDmzp2r/v376+abb1afPn1UuXJlHThwQCtWrFDr1q0L/CMKsAUPXoEMlGj5t4H53//+V+jydu3aXfA2MFOmTDHNmzc3QUFBxt/f39SpU8f885//NKdPn3auc+bMGfPII4+YypUrG4fD4XJLmOPHj5uRI0easLAwU6pUKVO7dm3z3HPPmby8PJd+T5w4YWJjY01wcLApV66c6dWrl9m1a5eR5HJblvxbuBw+fLjAeH755Rdz1113maCgIBMYGGj+/ve/m5SUlCJvJXPuNoq6PUthv6fC5ObmmkmTJpnq1aubUqVKmfDwcDNu3Djn7T4u1E9R3nvvPXPTTTcZPz8/ExwcbPr162d++eWXAuv95z//MTVq1DC+vr6mcePG5tNPPy1wyxJjjPnqq69MkyZNjK+v7yXfEiYtLc0MGjTIVKpUyfj6+poGDRoUequUK7kNTFGv++ijj0zDhg1N6dKlTWRkpJk+fbp58803jSSTnJzsXK84bgNjjDHLli0zUVFRxsfHx+X1Rd0G5rnnnnN5fUJCgpFkFi9e7NJe1P+XCQkJJjo62gQGBprSpUubmjVrmpiYGLNly5ZLqhu4VjiMucizrwFcU5KSknTTTTfpP//5j/r16+fpcgAAFuIcQMAGCvu+1/j4eHl5eV3wGzgAANcezgEEbGDGjBnaunWrbrvtNvn4+GjlypVauXKlhg4dWuA+aihep0+fLvS7af8qMDCw0NuzXKzDhw+f95Y0vr6+Cg4OvuztXywrxgqgeHAIGLCB1atXa9KkSdqxY4eys7N1/fXXq3///nrqqae4D5qbrVu37oIXqcyfP18xMTGX3UdkZOR5bxTdrl07rVu37rK3f7GsGCuA4kEABAA3OnbsmLZu3XrederVq6eqVatedh8bN24s9DB/vgoVKjivJncnK8YKoHgQAAEAAGyGi0AAAABshpN/rkBeXp5SUlJUvnx5j31HKQAAuDTGGB0/flxhYWEuX71oJwTAK5CSksIVlAAAlFAHDx5UtWrVPF2GRxAAr0D+VzMdPHhQAQEBHq4GAABcjKysLIWHh7v1KxavdgTAK5B/2DcgIIAACABACWPn07fseeAbAADAxgiAAAAANkMABAAAsJkSGQDj4uLUrFkzlS9fXiEhIerVq5d27drlsk779u3lcDhcHv/4xz9c1jlw4IC6d++uMmXKKCQkRKNHj9aZM2esHAoAAIDlSuRFIOvXr1dsbKyaNWumM2fO6Mknn1Tnzp21Y8cOlS1b1rnekCFDNHnyZOfzMmXKOH8+e/asunfvrtDQUH311Vc6dOiQBgwYoFKlSmnq1KmWjgcAAMBK18RXwR0+fFghISFav3692rZtK+mPGcDGjRsrPj6+0NesXLlSd9xxh1JSUlSlShVJ0rx58zRmzBgdPnxYvr6+F+w3KytLgYGByszM5CpgAABKCD6/S+gh4HNlZmZKkoKDg13a3377bVWqVEn169fXuHHjdPLkSeeyxMRENWjQwBn+JCk6OlpZWVnavn17of3k5OQoKyvL5QEAAFDSlMhDwH+Vl5enESNGqHXr1qpfv76z/f/+7/8UERGhsLAwbdu2TWPGjNGuXbu0ZMkSSVJqaqpL+JPkfJ6amlpoX3FxcZo0aZKbRgIAAGCNEh8AY2Nj9cMPP+jLL790aR86dKjz5wYNGqhq1arq2LGj9u3bp5o1a15WX+PGjdOoUaOcz/PvJA4AAFCSlOhDwMOGDdPy5cuVkJBwwe/ya9GihSRp7969kqTQ0FClpaW5rJP/PDQ0tNBt+Pn5Ob/1g2//AAAAJVWJDIDGGA0bNkwffvih1q5dq+rVq1/wNUlJSZKkqlWrSpJatWql77//Xunp6c51Vq9erYCAAEVFRbmlbgAAgKtBiTwEHBsbq3feeUfLli1T+fLlnefsBQYGyt/fX/v27dM777yjbt26qWLFitq2bZtGjhyptm3bqmHDhpKkzp07KyoqSv3799eMGTOUmpqqp59+WrGxsfLz8/Pk8AAAANyqRN4Gpqgvb54/f75iYmJ08OBB3Xffffrhhx904sQJhYeH66677tLTTz/tctj2559/1kMPPaR169apbNmyGjhwoKZNmyYfn4vLxVxGDgBAycPndwkNgFcL/oAAACh5+PwuoYeAAbuLHLvC0yVcsv3Tunu6BADAn0rkRSAAAAC4fARAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZH08XAHha5NgVni4BAABLMQMIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGZKZACMi4tTs2bNVL58eYWEhKhXr17atWuXyzq///67YmNjVbFiRZUrV069e/dWWlqayzoHDhxQ9+7dVaZMGYWEhGj06NE6c+aMlUMBAACwXIkMgOvXr1dsbKw2bdqk1atXKzc3V507d9aJEyec64wcOVIff/yxFi9erPXr1yslJUV33323c/nZs2fVvXt3nT59Wl999ZXeeustLViwQOPHj/fEkAAAACzjMMYYTxdxpQ4fPqyQkBCtX79ebdu2VWZmpipXrqx33nlHf/vb3yRJP/74o+rWravExES1bNlSK1eu1B133KGUlBRVqVJFkjRv3jyNGTNGhw8flq+v7wX7zcrKUmBgoDIzMxUQEODWMcJ9Iseu8HQJtrB/WndPlwAAkvj8lkroDOC5MjMzJUnBwcGSpK1btyo3N1edOnVyrlOnTh1df/31SkxMlCQlJiaqQYMGzvAnSdHR0crKytL27dstrB4AAMBaPp4u4Erl5eVpxIgRat26terXry9JSk1Nla+vr4KCglzWrVKlilJTU53r/DX85S/PX1aYnJwc5eTkOJ9nZWUV1zAAAAAsU+JnAGNjY/XDDz9o0aJFbu8rLi5OgYGBzkd4eLjb+wQAAChuJToADhs2TMuXL1dCQoKqVavmbA8NDdXp06eVkZHhsn5aWppCQ0Od65x7VXD+8/x1zjVu3DhlZmY6HwcPHizG0QAAAFijRAZAY4yGDRumDz/8UGvXrlX16tVdljdp0kSlSpXSmjVrnG27du3SgQMH1KpVK0lSq1at9P333ys9Pd25zurVqxUQEKCoqKhC+/Xz81NAQIDLAwAAoKQpkecAxsbG6p133tGyZctUvnx55zl7gYGB8vf3V2BgoAYPHqxRo0YpODhYAQEBeuSRR9SqVSu1bNlSktS5c2dFRUWpf//+mjFjhlJTU/X0008rNjZWfn5+nhweAACAW5XIADh37lxJUvv27V3a58+fr5iYGEnSzJkz5eXlpd69eysnJ0fR0dF6+eWXnet6e3tr+fLleuihh9SqVSuVLVtWAwcO1OTJk60aBgAAgEdcE/cB9BTuI3Rt4D6A1uA+gACuFnx+l9BzAAEAAHD5CIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbMbH0wUAsIfIsSs8XcIl2z+tu6dLAAC3YAYQAADAZgiAAAAANmNZAPzmm2/0/fffO58vW7ZMvXr10pNPPqnTp09bVQYAAIDtWRYAH3zwQe3evVuS9NNPP6lPnz4qU6aMFi9erCeeeMKqMgAAAGzPsgC4e/duNW7cWJK0ePFitW3bVu+8844WLFigDz74wKoyAAAAbM+yAGiMUV5eniTp888/V7du3SRJ4eHhOnLkiFVlAAAA2J5lAbBp06aaMmWKFi5cqPXr16t79z9ur5CcnKwqVapYVQYAAIDtWRYA4+Pj9c0332jYsGF66qmnVKtWLUnS+++/r1tuucWqMgAAAGzPshtBN2zY0OUq4HzPPfecvL29rSoDAADA9iy9D2BGRoZef/11jRs3TkePHpUk7dixQ+np6VaWAQAAYGuWzQBu27ZNHTt2VFBQkPbv368hQ4YoODhYS5Ys0YEDB/Tvf//bqlIAAABszbIZwFGjRmnQoEHas2ePSpcu7Wzv1q2bNmzYYFUZAAAAtmdZAPzf//6nBx98sED7ddddp9TUVKvKAAAAsD3LAqCfn5+ysrIKtO/evVuVK1e2qgwAAADbsywA9ujRQ5MnT1Zubq4kyeFw6MCBAxozZox69+5tVRkAAAC2Z1kAfOGFF5Sdna2QkBCdOnVK7dq1U61atVS+fHn985//tKoMAAAA27PsKuDAwECtXr1aGzdu1Hfffafs7GzdfPPN6tSpk1UlAAAAQBYGwHytW7dW69atre4WAAAAf7LsEPDw4cM1a9asAu0vvfSSRowYYVUZAAAAtmdZAPzggw8Knfm75ZZb9P7771tVBgAAgO1ZFgB/++03BQYGFmgPCAjQkSNHrCoDAADA9iwLgLVq1dKqVasKtK9cuVI1atSwqgwAAADbs+wikFGjRmnYsGE6fPiwOnToIElas2aNXnjhBcXHx1tVBgAAgO1ZFgDvv/9+5eTk6J///KeeffZZSVJkZKTmzp2rAQMGWFUGAACA7Vl6G5iHHnpIDz30kA4fPix/f3+VK1fOyu4BAAAgD9wHUBLf/QsAAOBBll0EkpaWpv79+yssLEw+Pj7y9vZ2eQAAAMAals0AxsTE6MCBA3rmmWdUtWpVORwOq7oGAADAX1gWAL/88kt98cUXaty4sVVdAgAAoBCWHQIODw+XMcaq7gAAAFAEywJgfHy8xo4dq/3791vVJQAAAAph2SHge++9VydPnlTNmjVVpkwZlSpVymX50aNHrSoFAADA1iwLgHzbBwAAwNXBsgA4cOBAq7oCAADAeVh2DqAk7du3T08//bT69u2r9PR0SdLKlSu1fft2K8sAAACwNcsC4Pr169WgQQNt3rxZS5YsUXZ2tiTpu+++04QJE6wqAwAAwPYsC4Bjx47VlClTtHr1avn6+jrbO3TooE2bNllVBgAAgO1ZFgC///573XXXXQXaQ0JCdOTIEavKAAAAsD3LAmBQUJAOHTpUoP3bb7/VddddZ1UZAAAAtmdZAOzTp4/GjBmj1NRUORwO5eXlaePGjXr88cc1YMAAq8oAAACwPcsC4NSpU1WnTh2Fh4crOztbUVFRatu2rW655RY9/fTTVpUBAABge5bcB9AYo9TUVM2aNUvjx4/X999/r+zsbN10002qXbu2FSUAAADgT5YFwFq1amn79u2qXbu2wsPDregWAAAAhbDkELCXl5dq166t3377zYruAAAAcB6WnQM4bdo0jR49Wj/88INVXQIAAKAQln0X8IABA3Ty5Ek1atRIvr6+8vf3d1l+9OhRq0oBAACwNcsCYHx8vFVdAQAA4DwsOQScm5ur9evXq23btho4cGChj0uxYcMG3XnnnQoLC5PD4dDSpUtdlsfExMjhcLg8unTp4rLO0aNH1a9fPwUEBCgoKEiDBw92fj8xAADAtcySAFiqVCl98MEHxba9EydOqFGjRpozZ06R63Tp0kWHDh1yPt59912X5f369dP27du1evVqLV++XBs2bNDQoUOLrUYAAICrlWWHgHv16qWlS5dq5MiRV7ytrl27qmvXruddx8/PT6GhoYUu27lzp1atWqX//e9/atq0qSRp9uzZ6tatm55//nmFhYVdcY0AAABXK8sCYO3atTV58mRt3LhRTZo0UdmyZV2WDx8+vFj7W7dunUJCQlShQgV16NBBU6ZMUcWKFSVJiYmJCgoKcoY/SerUqZO8vLy0efNm3XXXXcVaCwAAwNXEsgD4xhtvKCgoSFu3btXWrVtdljkcjmINgF26dNHdd9+t6tWra9++fXryySfVtWtXJSYmytvbW6mpqQoJCXF5jY+Pj4KDg5WamlrkdnNycpSTk+N8npWVVWw1AwAAWMWyAJicnGxVV+rTp4/z5wYNGqhhw4aqWbOm1q1bp44dO172duPi4jRp0qTiKBEAAMBjLLsRtCfVqFFDlSpV0t69eyVJoaGhSk9Pd1nnzJkzOnr0aJHnDUrSuHHjlJmZ6XwcPHjQrXUDAAC4g2UzgPfff/95l7/55ptu6/uXX37Rb7/9pqpVq0qSWrVqpYyMDG3dulVNmjSRJK1du1Z5eXlq0aJFkdvx8/OTn5+f2+oEAACwgmUB8NixYy7Pc3Nz9cMPPygjI0MdOnS4pG1lZ2c7Z/OkPw4vJyUlKTg4WMHBwZo0aZJ69+6t0NBQ7du3T0888YRq1aql6OhoSVLdunXVpUsXDRkyRPPmzVNubq6GDRumPn36cAUwAAC45lkWAD/88MMCbXl5eXrooYdUs2bNS9rWli1bdNtttzmfjxo1SpI0cOBAzZ07V9u2bdNbb72ljIwMhYWFqXPnznr22WddZu/efvttDRs2TB07dpSXl5d69+6tWbNmXeboAAAASg6HMcZ4soBdu3apffv2OnTokCfLuCxZWVkKDAxUZmamAgICPF0OLlPk2BWeLgFXqf3Tunu6BABuwOf3VXARyL59+3TmzBlPlwEAAGAblh0Czj9Mm88Yo0OHDmnFihWX/F3AAAAAuHyWBcBvv/3W5bmXl5cqV66sF1544YJXCAMAAKD4WBYAExISrOoKAAAA52HZOYDJycnas2dPgfY9e/Zo//79VpUBAABge5YFwJiYGH311VcF2jdv3qyYmBirygAAALA9ywLgt99+q9atWxdob9mypZKSkqwqAwAAwPYsC4AOh0PHjx8v0J6ZmamzZ89aVQYAAIDtWRYA27Ztq7i4OJewd/bsWcXFxalNmzZWlQEAAGB7ll0FPH36dLVt21Y33nijbr31VknSF198oaysLK1du9aqMgAAAGzPshnAqKgobdu2Tffcc4/S09N1/PhxDRgwQD/++KPq169vVRkAAAC2Z9kMoCSFhYVp6tSpVnYJAACAc1g2Azh//nwtXry4QPvixYv11ltvWVUGAACA7VkWAOPi4lSpUqUC7SEhIcwKAgAAWMiyAHjgwAFVr169QHtERIQOHDhgVRkAAAC2Z1kADAkJ0bZt2wq0f/fdd6pYsaJVZQAAANieZQGwb9++Gj58uBISEnT27FmdPXtWa9eu1aOPPqo+ffpYVQYAAIDtWXYV8LPPPqv9+/erY8eO8vH5o9u8vDwNGDCAcwABAAAsZFkA9PX11Xvvvadnn31W3333nfz9/dWgQQNFRERYVQIAAABk8X0AJSk4OFi33XZboVcEAwAAwP0sOQcwIyNDsbGxqlSpkqpUqaIqVaqoUqVKGjZsmDIyMqwoAQAAAH9y+wzg0aNH1apVK/3666/q16+f6tatK0nasWOHFixYoDVr1uirr75ShQoV3F0KAAAAZEEAnDx5snx9fbVv3z5VqVKlwLLOnTtr8uTJmjlzprtLAQAAgCw4BLx06VI9//zzBcKfJIWGhmrGjBn68MMP3V0GAAAA/uT2AHjo0CHVq1evyOX169dXamqqu8sAAADAn9weACtVqqT9+/cXuTw5OVnBwcHuLgMAAAB/cnsAjI6O1lNPPaXTp08XWJaTk6NnnnlGXbp0cXcZAAAA+JMlF4E0bdpUtWvXVmxsrOrUqSNjjHbu3KmXX35ZOTk5WrhwobvLAAAAwJ/cHgCrVaumxMREPfzwwxo3bpyMMZIkh8Oh22+/XS+99JLCw8PdXQYsEjl2hadLAAAAF2DJN4FUr15dK1eu1LFjx7Rnzx5JUq1atTj3DwAAwAMs/Sq4ChUqqHnz5lZ2CQAAgHNY8lVwAAAAuHoQAAEAAGyGAAgAAGAzbg2AN998s44dOybpj9vBnDx50p3dAQAA4CK4NQDu3LlTJ06ckCRNmjRJ2dnZ7uwOAAAAF8GtVwE3btxYgwYNUps2bWSM0fPPP69y5coVuu748ePdWQoAAAD+5NYAuGDBAk2YMEHLly+Xw+HQypUr5eNTsEuHw0EABAAAsIhbA+CNN96oRYsWSZK8vLy0Zs0ahYSEuLNLAAAAXIBlN4LOy8uzqisAAACch6XfBLJv3z7Fx8dr586dkqSoqCg9+uijqlmzppVlAAAA2Jpl9wH89NNPFRUVpa+//loNGzZUw4YNtXnzZtWrV0+rV6+2qgwAAADbs2wGcOzYsRo5cqSmTZtWoH3MmDG6/fbbrSoFAADA1iybAdy5c6cGDx5coP3+++/Xjh07rCoDAADA9iwLgJUrV1ZSUlKB9qSkJK4MBgAAsJBlh4CHDBmioUOH6qefftItt9wiSdq4caOmT5+uUaNGWVUGAACA7VkWAJ955hmVL19eL7zwgsaNGydJCgsL08SJEzV8+HCrygAAALA9ywKgw+HQyJEjNXLkSB0/flySVL58eau6BwAAwJ8svQ9gPoIfAACA51h2EQgAAACuDgRAAAAAmyEAAgAA2IwlATA3N1cdO3bUnj17rOgOAAAA52FJACxVqpS2bdtmRVcAAAC4AMsOAd9333164403rOoOAAAARbDsNjBnzpzRm2++qc8//1xNmjRR2bJlXZa/+OKLVpUCAABga5YFwB9++EE333yzJGn37t0uyxwOh1VlAAAA2J5lATAhIcGqrgAAAHAelt8GZu/evfr000916tQpSZIxxuoSAAAAbM2yAPjbb7+pY8eOuuGGG9StWzcdOnRIkjR48GA99thjVpUBAABge5YFwJEjR6pUqVI6cOCAypQp42y/9957tWrVKqvKAAAAsD3LAuBnn32m6dOnq1q1ai7ttWvX1s8//3xJ29qwYYPuvPNOhYWFyeFwaOnSpS7LjTEaP368qlatKn9/f3Xq1KnATaiPHj2qfv36KSAgQEFBQRo8eLCys7Mva2wAAAAliWUB8MSJEy4zf/mOHj0qPz+/S95Wo0aNNGfOnEKXz5gxQ7NmzdK8efO0efNmlS1bVtHR0fr999+d6/Tr10/bt2/X6tWrtXz5cm3YsEFDhw69tEEBAACUQJYFwFtvvVX//ve/nc8dDofy8vI0Y8YM3XbbbZe0ra5du2rKlCm66667Ciwzxig+Pl5PP/20evbsqYYNG+rf//63UlJSnDOFO3fu1KpVq/T666+rRYsWatOmjWbPnq1FixYpJSXlisYJAABwtbMsAM6YMUOvvvqqunbtqtOnT+uJJ55Q/fr1tWHDBk2fPr3Y+klOTlZqaqo6derkbAsMDFSLFi2UmJgoSUpMTFRQUJCaNm3qXKdTp07y8vLS5s2bi60WAACAq5Fl9wGsX7++du/erZdeeknly5dXdna27r77bsXGxqpq1arF1k9qaqokqUqVKi7tVapUcS5LTU1VSEiIy3IfHx8FBwc71ylMTk6OcnJynM+zsrKKq2wAAADLWBYApT9m4p566ikruyxWcXFxmjRpkqfLAAAAuCKWBsBjx47pjTfe0M6dOyVJUVFRGjRokIKDg4utj9DQUElSWlqay8xiWlqaGjdu7FwnPT3d5XVnzpzR0aNHna8vzLhx4zRq1Cjn86ysLIWHhxdb7QAAAFaw7BzADRs2KDIyUrNmzdKxY8d07NgxzZo1S9WrV9eGDRuKrZ/q1asrNDRUa9ascbZlZWVp8+bNatWqlSSpVatWysjI0NatW53rrF27Vnl5eWrRokWR2/bz81NAQIDLAwAAoKSxbAYwNjZW9957r+bOnStvb29J0tmzZ/Xwww8rNjZW33///UVvKzs7W3v37nU+T05OVlJSkoKDg3X99ddrxIgRmjJlimrXrq3q1avrmWeeUVhYmHr16iVJqlu3rrp06aIhQ4Zo3rx5ys3N1bBhw9SnTx+FhYUV67gBAACuNpYFwL179+r99993hj9J8vb21qhRo1xuD3MxtmzZ4nLrmPzDsgMHDtSCBQv0xBNP6MSJExo6dKgyMjLUpk0brVq1SqVLl3a+5u2339awYcPUsWNHeXl5qXfv3po1a9YVjhIAAODq5zDGGCs6at26tUaPHu2chcu3dOlSTZs2TZs2bbKijGKVlZWlwMBAZWZmcjj4T5FjV3i6BMDW9k/r7ukSgKsen99ungHctm2b8+fhw4fr0Ucf1d69e9WyZUtJ0qZNmzRnzhxNmzbNnWUAAADgL9w6A+jl5SWHw6ELdeFwOHT27Fl3leE2/AuiIGYAAc9iBhC4MD6/3TwDmJyc7M7NAwAA4DK4NQBGRES4c/MAAAC4DJbeCDolJUVffvml0tPTlZeX57Js+PDhVpYCAABgW5YFwAULFujBBx+Ur6+vKlasKIfD4VzmcDgIgAAAABaxLAA+88wzGj9+vMaNGycvL8u+gAQAAADnsCyJnTx5Un369CH8AQAAeJhlaWzw4MFavHixVd0BAACgCJYdAo6Li9Mdd9yhVatWqUGDBipVqpTL8hdffNGqUgAAAGzN0gD46aef6sYbb5SkAheBAAAAwBqWBcAXXnhBb775pmJiYqzqEgAAAIWw7BxAPz8/tW7d2qruAAAAUATLAuCjjz6q2bNnW9UdAAAAimDZIeCvv/5aa9eu1fLly1WvXr0CF4EsWbLEqlIAAABszbIAGBQUpLvvvtuq7gAAAFAEywLg/PnzreoKAAAA58HXcgAAANiMZTOA1atXP+/9/n766SerSgEAALA1ywLgiBEjXJ7n5ubq22+/1apVqzR69GirygAAALA9ywLgo48+Wmj7nDlztGXLFqvKAAAAsD2PnwPYtWtXffDBB54uAwAAwDY8HgDff/99BQcHe7oMAAAA27DsEPBNN93kchGIMUapqak6fPiwXn75ZavKAAAAsD3LAmCvXr1cnnt5ealy5cpq37696tSpY1UZAAAAtmdZAJwwYYJVXQEAAOA8PH4OIAAAAKzl9hlALy+v894AWpIcDofOnDnj7lIAAAAgCwLghx9+WOSyxMREzZo1S3l5ee4uAwAAAH9yewDs2bNngbZdu3Zp7Nix+vjjj9WvXz9NnjzZ3WUAAADgT5aeA5iSkqIhQ4aoQYMGOnPmjJKSkvTWW28pIiLCyjIAAABszZIAmJmZqTFjxqhWrVravn271qxZo48//lj169e3onsAAAD8hdsPAc+YMUPTp09XaGio3n333UIPCQMAAMA6DmOMcWcHXl5e8vf3V6dOneTt7V3kekuWLHFnGW6RlZWlwMBAZWZmKiAgwNPlXBUix67wdAmAre2f1t3TJQBXPT6/LZgBHDBgwAVvAwMAAADruD0ALliwwN1dAAAA4BLwTSAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2c80GwIkTJ8rhcLg86tSp41z++++/KzY2VhUrVlS5cuXUu3dvpaWlebBiAAAAa1yzAVCS6tWrp0OHDjkfX375pXPZyJEj9fHHH2vx4sVav369UlJSdPfdd3uwWgAAAGv4eLoAd/Lx8VFoaGiB9szMTL3xxht655131KFDB0nS/PnzVbduXW3atEktW7a0ulQAAADLXNMzgHv27FFYWJhq1Kihfv366cCBA5KkrVu3Kjc3V506dXKuW6dOHV1//fVKTEwscns5OTnKyspyeQAAAJQ012wAbNGihRYsWKBVq1Zp7ty5Sk5O1q233qrjx48rNTVVvr6+CgoKcnlNlSpVlJqaWuQ24+LiFBgY6HyEh4e7eRQAAADF75o9BNy1a1fnzw0bNlSLFi0UERGh//73v/L397+sbY4bN06jRo1yPs/KyiIEAgCAEueanQE8V1BQkG644Qbt3btXoaGhOn36tDIyMlzWSUtLK/ScwXx+fn4KCAhweQAAAJQ0tgmA2dnZ2rdvn6pWraomTZqoVKlSWrNmjXP5rl27dODAAbVq1cqDVQIAALjfNXsI+PHHH9edd96piIgIpaSkaMKECfL29lbfvn0VGBiowYMHa9SoUQoODlZAQIAeeeQRtWrViiuAAQDANe+aDYC//PKL+vbtq99++02VK1dWmzZttGnTJlWuXFmSNHPmTHl5eal3797KyclRdHS0Xn75ZQ9XDQAA4H4OY4zxdBElVVZWlgIDA5WZmcn5gH+KHLvC0yUAtrZ/WndPlwBc9fj8ttE5gAAAAPgDARAAAMBmrtlzAAHAjkriaRgctgasxwwgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDM+ni4ARYscu8LTJQAAgGsQM4AAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmuBE0AMCjSuJN7/dP6+7pEoArwgwgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANiMj6cLAACgpIkcu8LTJVyy/dO6e7oEXEWYAQQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMz6eLgAAALhf5NgVni7hku2f1t3TJVyzmAEEAACwGQIgAACAzdg+AM6ZM0eRkZEqXbq0WrRooa+//trTJQEAALiVrQPge++9p1GjRmnChAn65ptv1KhRI0VHRys9Pd3TpQEAALiNrQPgiy++qCFDhmjQoEGKiorSvHnzVKZMGb355pueLg0AAMBtbHsV8OnTp7V161aNGzfO2ebl5aVOnTopMTGx0Nfk5OQoJyfH+TwzM1OSlJWV5ZYa83JOumW7AACUBO76fM3frjHGLdsvCWwbAI8cOaKzZ8+qSpUqLu1VqlTRjz/+WOhr4uLiNGnSpALt4eHhbqkRAAA7C4x37/aPHz+uwMBA93ZylbJtALwc48aN06hRo5zP8/LydPToUVWsWFEOh+OCr8/KylJ4eLgOHjyogIAAd5bqMXYYo2SPcdphjJI9xskYrx12GKcVYzTG6Pjx4woLC3PL9ksC2wbASpUqydvbW2lpaS7taWlpCg0NLfQ1fn5+8vPzc2kLCgq65L4DAgKu2f9x89lhjJI9xmmHMUr2GCdjvHbYYZzuHqNdZ/7y2fYiEF9fXzVp0kRr1qxxtuXl5WnNmjVq1aqVBysDAABwL9vOAErSqFGjNHDgQDVt2lTNmzdXfHy8Tpw4oUGDBnm6NAAAALexdQC89957dfjwYY0fP16pqalq3LixVq1aVeDCkOLi5+enCRMmFDiMfC2xwxgle4zTDmOU7DFOxnjtsMM47TDGq4HD2PkaaAAAABuy7TmAAAAAdkUABAAAsBkCIAAAgM0QAAEAAGyGAHiF5syZo8jISJUuXVotWrTQ119/XeS6S5YsUdOmTRUUFKSyZcuqcePGWrhwocs6xhiNHz9eVatWlb+/vzp16qQ9e/a4exjnVZxjzM3N1ZgxY9SgQQOVLVtWYWFhGjBggFJSUqwYSpGK+338q3/84x9yOByKj493Q+WXxh3j3Llzp3r06KHAwECVLVtWzZo104EDB9w5jPMq7jFmZ2dr2LBhqlatmvz9/RUVFaV58+a5exgXdCnj/KtFixbJ4XCoV69eLu0lfd/zV4WN8VrY9/xVUe/jX5XUfc9fnW+cV9u+p8QxuGyLFi0yvr6+5s033zTbt283Q4YMMUFBQSYtLa3Q9RMSEsySJUvMjh07zN69e018fLzx9vY2q1atcq4zbdo0ExgYaJYuXWq+++4706NHD1O9enVz6tQpq4blorjHmJGRYTp16mTee+898+OPP5rExETTvHlz06RJEyuH5cId72O+JUuWmEaNGpmwsDAzc+ZMN4/k/Nwxzr1795rg4GAzevRo880335i9e/eaZcuWFblNd3PHGIcMGWJq1qxpEhISTHJysnnllVeMt7e3WbZsmVXDKuBSx5kvOTnZXHfddebWW281PXv2dFlW0vc9+Yoa47Ww78l3vvcxX0ne9+Q73zivtn1PSUQAvALNmzc3sbGxzudnz541YWFhJi4u7qK3cdNNN5mnn37aGGNMXl6eCQ0NNc8995xzeUZGhvHz8zPvvvtu8RV+CYp7jIX5+uuvjSTz888/X1Gtl8tdY/zll1/MddddZ3744QcTERHh8Z2wO8Z57733mvvuu69Y67wS7hhjvXr1zOTJk13Wufnmm81TTz115QVfpssZ55kzZ8wtt9xiXn/9dTNw4ECXD9RrZd9zvjEWpiTuey5mjNfCvudC47za9j0lEYeAL9Pp06e1detWderUydnm5eWlTp06KTEx8YKvN8ZozZo12rVrl9q2bStJSk5OVmpqqss2AwMD1aJFi4vaZnFzxxgLk5mZKYfDcVnfq3yl3DXGvLw89e/fX6NHj1a9evXcUvulcMc48/LytGLFCt1www2Kjo5WSEiIWrRooaVLl7prGOflrvfylltu0UcffaRff/1VxhglJCRo9+7d6ty5s1vGcSGXO87JkycrJCREgwcPLrDsWtn3nG+MhSmJ+54LjfFa2fecb5xX276npLL1N4FciSNHjujs2bMFvjWkSpUq+vHHH4t8XWZmpq677jrl5OTI29tbL7/8sm6//XZJUmpqqnMb524zf5mV3DHGc/3+++8aM2aM+vbt65EvNnfXGKdPny4fHx8NHz7cbbVfCneMMz09XdnZ2Zo2bZqmTJmi6dOna9WqVbr77ruVkJCgdu3auXVM53LXezl79mwNHTpU1apVk4+Pj7y8vPTaa6+d9x817nQ54/zyyy/1xhtvKCkpqdDl18K+50JjPFdJ3PdczBivhX3PhcZ5te17SioCoMXKly+vpKQkZWdna82aNRo1apRq1Kih9u3be7q0YnOxY8zNzdU999wjY4zmzp3rmWIv0/nGuHXrVv3rX//SN998I4fD4elSr8j5xpmXlydJ6tmzp0aOHClJaty4sb766ivNmzevxOyEL/T3Onv2bG3atEkfffSRIiIitGHDBsXGxiosLMxlVuNqdfz4cfXv31+vvfaaKlWq5Oly3OJSx1gS9z0XM8ZrYd9zMeO8VvY9nkYAvEyVKlWSt7e30tLSXNrT0tIUGhpa5Ou8vLxUq1YtSX/8we7cuVNxcXFq376983VpaWmqWrWqyzYbN25c/IO4AHeMMV/+Dvjnn3/W2rVrPfIvcMk9Y/ziiy+Unp6u66+/3rn+2bNn9dhjjyk+Pl779+93y1jOxx3jrFSpknx8fBQVFeXymrp16+rLL78s/kFcgDvGeOrUKT355JP68MMP1b17d0lSw4YNlZSUpOeff94jAfBSx7lv3z7t379fd955p7Mt/wPUx8dHu3btKvH7nosZY82aNSWV3H3PxYzxWtj3XMw4w8PDr6p9T0nFOYCXydfXV02aNNGaNWucbXl5eVqzZo1atWp10dvJy8tTTk6OJKl69eoKDQ112WZWVpY2b958SdssLu4Yo/T/d8B79uzR559/rooVKxZr3ZfCHWPs37+/tm3bpqSkJOcjLCxMo0eP1qefflrsY7gY7hinr6+vmjVrpl27drmss3v3bkVERBRP4ZfAHWPMzc1Vbm6uvLxcd5Xe3t7ODyWrXeo469Spo++//97l77FHjx667bbblJSUpPDw8BK/77mYMUole99zMWO8FvY9FzPOq23fU2J57vqTkm/RokXGz8/PLFiwwOzYscMMHTrUBAUFmdTUVGOMMf379zdjx451rj916lTz2WefmX379pkdO3aY559/3vj4+JjXXnvNuc60adNMUFCQWbZsmdm2bZvp2bOnx2/FUJxjPH36tOnRo4epVq2aSUpKMocOHXI+cnJyrokxFuZquBLPHeNcsmSJKVWqlHn11VfNnj17zOzZs423t7f54osvLB+fMe4ZY7t27Uy9evVMQkKC+emnn8z8+fNN6dKlzcsvv2z5+PJd6jjPVdhVlSV933Ouc8d4Lex7znUxVzqXxH3PuQob59W27ymJCIBXaPbs2eb66683vr6+pnnz5mbTpk3OZe3atTMDBw50Pn/qqadMrVq1TOnSpU2FChVMq1atzKJFi1y2l5eXZ5555hlTpUoV4+fnZzp27Gh27dpl1XAKVZxjTE5ONpIKfSQkJFg4KlfF/T6e62rYCRvjnnG+8cYbzvUaNWpkli5dasVQilTcYzx06JCJiYkxYWFhpnTp0ubGG280L7zwgsnLy7NqSIW6lHGeq7AP1JK+7znXuWO8FvY95yopAdAY94zzatv3lDQOY4zxzNwjAAAAPIFzAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsJn/BycRXyBAewXjAAAAAElFTkSuQmCC' 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+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3dff7b1c54a54759968be8570e103f04",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "20af2b4fe4cd48419458f7edb24d7a8f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
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+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "848ef50677a44953885e686448caf873",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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bcSVMXNvf66+/Lkk3vKPZTMWKFbtuULpaduOZlpaW5TPKi+TkZIdr1KS/w6Cbm1uW/Sq7Wt3d3bN8zm+++eZ1H0/z3nvvOdzxPmPGDGVkZNj3v1txo/EsVaqU2rZtq48//lhz587VAw88kOXyAmfL7nNMSkrSrFmzcryONm3a6K+//tLXX39tb7t06VKuHxgP5HccAQSuUr16dTVr1kx169aVv7+/Nm/erPnz5ysqKsq+TN26dSVJAwcOVJs2beTu7q6IiAg99NBDat68uV566SUdOnRItWvX1sqVK/XVV19p8ODB9sd61K1bV507d9a0adN0+vRp+2Ng9uzZIylnR618fHzUtGlTTZ48Wenp6SpbtqxWrlx5W49Y3Ujt2rXVvXt3vffee/bTpz/++KNmz56tjh07OhyBcqW6detq1apVev311xUcHKywsDA1aNAgy3KNGjVSiRIl1L17dw0cOFA2m01z5sy5Lafs1qxZo6ioKD322GO68847lZGRoTlz5sjd3V2dO3e+aa0PPvig5syZI19fX1WvXl3x8fFatWqVSpYsmW1/aWlpatmypR5//HHt3r1b77zzjpo0aeJwU0Ne3Ww8u3XrpkcffVSSNH78+FvuL7dat26twoUL66GHHlK/fv2UkpKi999/XwEBATp27FiO1tGvXz+99dZb6tKliwYNGqQyZcpo7ty5KlKkiCTzLnsAnI0ACFxl4MCB+vrrr7Vy5UqlpqYqNDRUEyZM0LBhw+zLdOrUSQMGDNCnn36qjz/+WIZhKCIiQm5ubvr66681atQoffbZZ5o1a5bKly+v1157zX537BUfffSRgoKC9Mknn2jhwoVq1aqVPvvsM1WpUsX+RXMz8+bN04ABA/T222/LMAy1bt1ay5YtU3Bw8G0dk+v54IMPVKFCBcXGxmrhwoUKCgrSiBEjNHr0aFP6z4nXX39dffv2tf+sWffu3bMNgCVLltSSJUs0dOhQjRw5UiVKlNCTTz6pli1bZrlLNLdq166tNm3aaPHixfrrr79UtGhR1a5dW8uWLbPftX2jWv/73//K3d1dc+fO1aVLl9S4cWOtWrXqunW99dZbmjt3rkaNGqX09HR16dJF06dPvy3B5Wbj+dBDD6lEiRLKzMy8LYEzt6pUqaL58+dr5MiReu655xQUFKT+/furdOnSWe4gvp4rz4AcMGCA/vvf/6p48eLq1q2bGjVqpM6dO+f47yeQ39kMrkoF8oVt27bp7rvv1scff6yuXbu6uhwg1zIyMhQcHKyHHnpIM2fOdHU5t9W0adM0ZMgQ/fnnnypbtqyrywFuGdcAAi5w8eLFLG3Tpk2Tm5vbTX+BA8ivFi1apJMnT6pbt26uLuWWXPv389KlS/rf//6nypUrE/7wr8EpYMAFJk+erC1btqh58+by8PDQsmXLtGzZMvXt2zfLs86Qf505c0ZpaWnXne/u7q7SpUubWJFrbNq0Sdu3b9f48eN1991367777nOYn5aWpjNnztxwHb6+vk57LEtuderUSXfccYfq1KmjpKQkffzxx/r9998dnnMIFHScAgZcIC4uTmPHjtXOnTuVkpKiO+64Q0899ZReeukleXjw/2UFRbNmzbR+/frrzg8NDXXqA5jzix49eujjjz9WnTp1FBsbq5o1azrMX7du3U1vDJo1a5Z69OjhxCpzbtq0afrggw906NAhXb58WdWrV9fzzz9v+mNtAGciAAJAHm3ZsuWGv+7g5eWlxo0bm1hR/nT27Flt2bLlhsvUqFFDZcqUMakiAARAAAAAi+EmEAAAAIvhYqNbkJmZqaNHj8rb25uHgwIAUEAYhqFz584pODhYbm7WPBZGALwFR48e5Y5NAAAKqCNHjqhcuXKuLsMlCIC3wNvbW9LfO5CPj4+LqwEAADmRnJyskJAQ+/e4FREAb8GV074+Pj4EQAAAChgrX75lzRPfAAAAFkYABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACL8XB1AQCQX5Uf/o2rS8i1Q5Pau7oEAAUARwABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWEyBDIAxMTGqX7++vL29FRAQoI4dO2r37t0OyzRr1kw2m83h9cwzzzgsc/jwYbVv315FixZVQECAhg0bpoyMDDM3BQAAwHQeri4gL9avX6/IyEjVr19fGRkZevHFF9W6dWvt3LlTxYoVsy/Xp08fjRs3zj5dtGhR+58vX76s9u3bKygoSBs2bNCxY8fUrVs3FSpUSBMnTjR1ewAAAMxUIAPg8uXLHaZjY2MVEBCgLVu2qGnTpvb2okWLKigoKNt1rFy5Ujt37tSqVasUGBioOnXqaPz48XrhhRc0ZswYFS5c2KnbAAAA4CoF8hTwtZKSkiRJ/v7+Du1z585VqVKlVLNmTY0YMUIXLlywz4uPj1etWrUUGBhob2vTpo2Sk5O1Y8eObPtJTU1VcnKywwsAAKCgKZBHAK+WmZmpwYMHq3HjxqpZs6a9/f/+7/8UGhqq4OBgbd++XS+88IJ2796tBQsWSJISEhIcwp8k+3RCQkK2fcXExGjs2LFO2hIAAABzFPgAGBkZqd9++03ff/+9Q3vfvn3tf65Vq5bKlCmjli1bav/+/apYsWKe+hoxYoSio6Pt08nJyQoJCclb4QAAAC5SoE8BR0VFacmSJVq7dq3KlSt3w2UbNGggSdq3b58kKSgoSMePH3dY5sr09a4b9PT0lI+Pj8MLAACgoCmQAdAwDEVFRWnhwoVas2aNwsLCbvqebdu2SZLKlCkjSQoPD9evv/6qEydO2JeJi4uTj4+Pqlev7pS6AQAA8oMCeQo4MjJS8+bN01dffSVvb2/7NXu+vr7y8vLS/v37NW/ePLVr104lS5bU9u3bNWTIEDVt2lR33XWXJKl169aqXr26nnrqKU2ePFkJCQkaOXKkIiMj5enp6crNAwAAcKoCeQRwxowZSkpKUrNmzVSmTBn767PPPpMkFS5cWKtWrVLr1q1VtWpVDR06VJ07d9bixYvt63B3d9eSJUvk7u6u8PBwPfnkk+rWrZvDcwMBAAD+jQrkEUDDMG44PyQkROvXr7/pekJDQ7V06dLbVRYAAECBUCCPAAIAACDvCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGA9XFwAAuH3KD//G1SXk2qFJ7V1dAmA5HAEEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALMbD1QUAsIbyw79xdQkAgH9wBBAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEFMgDGxMSofv368vb2VkBAgDp27Kjdu3c7LHPp0iVFRkaqZMmSKl68uDp37qzjx487LHP48GG1b99eRYsWVUBAgIYNG6aMjAwzNwUAAMB0pgXAn3/+Wb/++qt9+quvvlLHjh314osvKi0tLVfrWr9+vSIjI7Vx40bFxcUpPT1drVu31vnz5+3LDBkyRIsXL9YXX3yh9evX6+jRo+rUqZN9/uXLl9W+fXulpaVpw4YNmj17tmJjYzVq1Khb31gAAIB8zGYYhmFGR/Xr19fw4cPVuXNnHThwQDVq1NAjjzyin376Se3bt9e0adPyvO6TJ08qICBA69evV9OmTZWUlKTSpUtr3rx5evTRRyVJv//+u6pVq6b4+Hg1bNhQy5Yt04MPPqijR48qMDBQkvTuu+/qhRde0MmTJ1W4cOGb9pucnCxfX18lJSXJx8cnz/UDVsCDoHE9hya1d3UJsBi+v008Arhnzx7VqVNHkvTFF1+oadOmmjdvnmJjY/Xll1/e0rqTkpIkSf7+/pKkLVu2KD09Xa1atbIvU7VqVd1xxx2Kj4+XJMXHx6tWrVr28CdJbdq0UXJysnbs2JFtP6mpqUpOTnZ4AQAAFDSmBUDDMJSZmSlJWrVqldq1aydJCgkJ0alTp/K83szMTA0ePFiNGzdWzZo1JUkJCQkqXLiw/Pz8HJYNDAxUQkKCfZmrw9+V+VfmZScmJka+vr72V0hISJ7rBgAAcBXTAmC9evU0YcIEzZkzR+vXr1f79n8f8j948GCWIJYbkZGR+u233/Tpp5/erlKva8SIEUpKSrK/jhw54vQ+AQAAbjfTAuC0adP0888/KyoqSi+99JIqVaokSZo/f74aNWqUp3VGRUVpyZIlWrt2rcqVK2dvDwoKUlpamhITEx2WP378uIKCguzLXHtX8JXpK8tcy9PTUz4+Pg4vAACAgsbDrI7uuusuh7uAr3jttdfk7u6eq3UZhqEBAwZo4cKFWrduncLCwhzm161bV4UKFdLq1avVuXNnSdLu3bt1+PBhhYeHS5LCw8P1yiuv6MSJEwoICJAkxcXFycfHR9WrV8/LJgIAABQIpgVASUpMTNT8+fO1f/9+DRs2TP7+/tq5c6cCAwNVtmzZHK8nMjJS8+bN01dffSVvb2/7NXu+vr7y8vKSr6+vevfurejoaPn7+8vHx0cDBgxQeHi4GjZsKElq3bq1qlevrqeeekqTJ09WQkKCRo4cqcjISHl6ejpl+wEAAPID0wLg9u3b1bJlS/n5+enQoUPq06eP/P39tWDBAh0+fFgfffRRjtc1Y8YMSVKzZs0c2mfNmqUePXpIkt544w25ubmpc+fOSk1NVZs2bfTOO+/Yl3V3d9eSJUvUv39/hYeHq1ixYurevbvGjRt3y9sKAACQn5n2HMBWrVrpnnvu0eTJk+Xt7a1ffvlFFSpU0IYNG/R///d/OnTokBll3FY8RwjIOZ4DiOvhOYAwG9/fJt4E8tNPP6lfv35Z2suWLXvdx64AAADg9jMtAHp6emb74OQ9e/aodOnSZpUBAABgeaYFwA4dOmjcuHFKT0+XJNlsNh0+fFgvvPCC/U5dAAAAOJ9pAXDq1KlKSUlRQECALl68qPvuu0+VKlWSt7e3XnnlFbPKAAAAsDzT7gL29fVVXFycfvjhB/3yyy9KSUnRPffc4/B7vQAAAHA+U58DKEmNGzdW48aNze4WAAAA/zDtFPDAgQM1ffr0LO1vvfWWBg8ebFYZAAAAlmdaAPzyyy+zPfLXqFEjzZ8/36wyAAAALM+0AHj69Gn5+vpmaffx8dGpU6fMKgMAAMDyTAuAlSpV0vLly7O0L1u2TBUqVDCrDAAAAMsz7SaQ6OhoRUVF6eTJk2rRooUkafXq1Zo6daqmTZtmVhkAAACWZ1oA7NWrl1JTU/XKK69o/PjxkqTy5ctrxowZ6tatm1llAAAAWJ6pj4Hp37+/+vfvr5MnT8rLy0vFixc3s3sAAADIBc8BlMRv/wIAALiQaTeBHD9+XE899ZSCg4Pl4eEhd3d3hxcAAADMYdoRwB49eujw4cN6+eWXVaZMGdlsNrO6BgAAwFVMC4Dff/+9vvvuO9WpU8esLgEAAJAN004Bh4SEyDAMs7oDAADAdZgWAKdNm6bhw4fr0KFDZnUJAACAbJh2CviJJ57QhQsXVLFiRRUtWlSFChVymH/mzBmzSgEAALA00wIgv/YBAACQP5gWALt3725WVwAAALgB064BlKT9+/dr5MiR6tKli06cOCFJWrZsmXbs2GFmGQAAAJZmWgBcv369atWqpU2bNmnBggVKSUmRJP3yyy8aPXq0WWUAAABYnmkBcPjw4ZowYYLi4uJUuHBhe3uLFi20ceNGs8oAAACwPNMC4K+//qpHHnkkS3tAQIBOnTplVhkAAACWZ1oA9PPz07Fjx7K0b926VWXLljWrDAAAAMszLQBGRETohRdeUEJCgmw2mzIzM/XDDz/oueeeU7du3cwqAwAAwPJMC4ATJ05U1apVFRISopSUFFWvXl1NmzZVo0aNNHLkSLPKAAAAsDxTngNoGIYSEhI0ffp0jRo1Sr/++qtSUlJ09913q3LlymaUAAAAgH+YFgArVaqkHTt2qHLlygoJCTGjWwAAAGTDlFPAbm5uqly5sk6fPm1GdwAAALgB064BnDRpkoYNG6bffvvNrC4BAACQDdN+C7hbt266cOGCateurcKFC8vLy8th/pkzZ8wqBQAAwNJMC4DTpk0zqysAAADcgCkBMD09XevXr9fLL7+ssLAwM7oEAADAdZhyDWChQoX05ZdfmtEVAAAAbsK0m0A6duyoRYsWmdUdAAAArsO0awArV66scePG6YcfflDdunVVrFgxh/kDBw40qxQAAABLMy0Azpw5U35+ftqyZYu2bNniMM9msxEAAQAATGJaADx48KBZXQEAAOAGTLsGEAAAAPmDaUcAe/XqdcP5H374oUmVAAAAWJtpAfDs2bMO0+np6frtt9+UmJioFi1amFUGAACA5ZkWABcuXJilLTMzU/3791fFihXNKgMAAMDyXHoNoJubm6Kjo/XGG2+4sgwAAABLcflNIPv371dGRoarywAAALAM004BR0dHO0wbhqFjx47pm2++Uffu3c0qAwAAwPJMC4Bbt251mHZzc1Pp0qU1derUm94hDAAAgNvHtAC4du1as7oCAADADZh2DeDBgwe1d+/eLO179+7VoUOHzCoDAADA8kwLgD169NCGDRuytG/atEk9evQwqwwAAADLMy0Abt26VY0bN87S3rBhQ23bts2sMgAAACzPtABos9l07ty5LO1JSUm6fPmyWWUAAABYnmkBsGnTpoqJiXEIe5cvX1ZMTIyaNGmSq3V9++23euihhxQcHCybzaZFixY5zO/Ro4dsNpvD64EHHnBY5syZM+ratat8fHzk5+en3r17KyUlJc/bBwAAUFCYdhfwq6++qqZNm6pKlSq69957JUnfffedkpOTtWbNmlyt6/z586pdu7Z69eqlTp06ZbvMAw88oFmzZtmnPT09HeZ37dpVx44dU1xcnNLT09WzZ0/17dtX8+bNy+WWAQAAFCymBcDq1atr+/bteuutt/TLL7/Iy8tL3bp1U1RUlPz9/XO1rrZt26pt27Y3XMbT01NBQUHZztu1a5eWL1+un376SfXq1ZMkvfnmm2rXrp2mTJmi4ODgXNUDAABQkJgWACUpODhYEydONKWvdevWKSAgQCVKlFCLFi00YcIElSxZUpIUHx8vPz8/e/iTpFatWsnNzU2bNm3SI488YkqNAAAArmBaAJw1a5aKFy+uxx57zKH9iy++0IULF27rz8E98MAD6tSpk8LCwrR//369+OKLatu2reLj4+Xu7q6EhAQFBAQ4vMfDw0P+/v5KSEi47npTU1OVmppqn05OTr5tNQMAAJjFtJtAYmJiVKpUqSztAQEBt/2oYEREhDp06KBatWqpY8eOWrJkiX766SetW7fultYbExMjX19f+yskJOT2FAwAAGAi0wLg4cOHFRYWlqU9NDRUhw8fdmrfFSpUUKlSpbRv3z5JUlBQkE6cOOGwTEZGhs6cOXPd6wYlacSIEUpKSrK/jhw54tS6AQAAnMG0ABgQEKDt27dnaf/ll1/s1+Y5y59//qnTp0+rTJkykqTw8HAlJiZqy5Yt9mXWrFmjzMxMNWjQ4Lrr8fT0lI+Pj8MLAACgoDHtGsAuXbpo4MCB8vb2VtOmTSVJ69ev16BBgxQREZGrdaWkpNiP5kl//87wtm3b5O/vL39/f40dO1adO3dWUFCQ9u/fr+eff16VKlVSmzZtJEnVqlXTAw88oD59+ujdd99Venq6oqKiFBERwR3AAADgX8+0ADh+/HgdOnRILVu2lIfH391mZmaqW7duub4GcPPmzWrevLl9Ojo6WpLUvXt3zZgxQ9u3b9fs2bOVmJio4OBgtW7dWuPHj3d4FuDcuXMVFRWlli1bys3NTZ07d9b06dNvw5YCAADkbzbDMAwzO9yzZ4/9OYC1atVSaGiomd3fVsnJyfL19VVSUhKng4GbKD/8G1eXgHzq0KT2ri4BFsP3t8nPAZQkf39/NW/ePNs7ggEAAOB8ptwEkpiYqMjISJUqVUqBgYEKDAxUqVKlFBUVpcTERDNKAAAAwD+cfgTwzJkzCg8P119//aWuXbuqWrVqkqSdO3cqNjZWq1ev1oYNG1SiRAlnlwIAAACZEADHjRunwoULa//+/QoMDMwyr3Xr1ho3bpzeeOMNZ5cCAAAAmXAKeNGiRZoyZUqW8Cf9/UDmyZMna+HChc4uAwAAAP9wegA8duyYatSocd35NWvWvOHv7wIAAOD2cnoALFWqlA4dOnTd+QcPHpS/v7+zywAAAMA/nB4A27Rpo5deeklpaWlZ5qWmpurll1/WAw884OwyAAAA8A9TbgKpV6+eKleurMjISFWtWlWGYWjXrl165513lJqaqjlz5ji7DAAAAPzD6QGwXLlyio+P17PPPqsRI0boyg+P2Gw23X///XrrrbcUEhLi7DIAAADwD1N+CSQsLEzLli3T2bNntXfvXklSpUqVuPYPAADABUz9KbgSJUroP//5j5ldAgAA4Bqm/BQcAAAA8g8CIAAAgMUQAAEAACzGqQHwnnvu0dmzZyX9/TiYCxcuOLM7AAAA5IBTA+CuXbt0/vx5SdLYsWOVkpLizO4AAACQA069C7hOnTrq2bOnmjRpIsMwNGXKFBUvXjzbZUeNGuXMUgAAAPAPpwbA2NhYjR49WkuWLJHNZtOyZcvk4ZG1S5vNRgAEAAAwiVMDYJUqVfTpp59Kktzc3LR69WoFBAQ4s0sAAADchGkPgs7MzDSrKwAAANyAqb8Esn//fk2bNk27du2SJFWvXl2DBg1SxYoVzSwDAADA0kx7DuCKFStUvXp1/fjjj7rrrrt01113adOmTapRo4bi4uLMKgMAAMDyTDsCOHz4cA0ZMkSTJk3K0v7CCy/o/vvvN6sUAAAASzPtCOCuXbvUu3fvLO29evXSzp07zSoDAADA8kwLgKVLl9a2bduytG/bto07gwEAAExk2ingPn36qG/fvjpw4IAaNWokSfrhhx/06quvKjo62qwyAAAALM+0APjyyy/L29tbU6dO1YgRIyRJwcHBGjNmjAYOHGhWGQAAAJZnWgC02WwaMmSIhgwZonPnzkmSvL29zeoeAAAA/zD1OYBXEPwAAABcx7SbQAAAAJA/EAABAAAshgAIAABgMaYEwPT0dLVs2VJ79+41ozsAAADcgCkBsFChQtq+fbsZXQEAAOAmTDsF/OSTT2rmzJlmdQcAAIDrMO0xMBkZGfrwww+1atUq1a1bV8WKFXOY//rrr5tVCgAAgKWZFgB/++033XPPPZKkPXv2OMyz2WxmlQEAAGB5pgXAtWvXmtUVAAAAbsD0x8Ds27dPK1as0MWLFyVJhmGYXQIAAIClmRYAT58+rZYtW+rOO+9Uu3btdOzYMUlS7969NXToULPKAAAAsDzTTgEPGTJEhQoV0uHDh1WtWjV7+xNPPKHo6GhNnTrVrFKAAq/88G9cXQIAoAAzLQCuXLlSK1asULly5RzaK1eurD/++MOsMgAAACzPtFPA58+fV9GiRbO0nzlzRp6enmaVAQAAYHmmBcB7771XH330kX3aZrMpMzNTkydPVvPmzc0qAwAAwPJMOwU8efJktWzZUps3b1ZaWpqef/557dixQ2fOnNEPP/xgVhkAAACWZ9oRwJo1a2rPnj1q0qSJHn74YZ0/f16dOnXS1q1bVbFiRbPKAAAAsDzTjgBKkq+vr1566SUzuwQAAMA1TA2AZ8+e1cyZM7Vr1y5JUvXq1dWzZ0/5+/ubWQYAAIClmXYK+Ntvv1X58uU1ffp0nT17VmfPntX06dMVFhamb7/91qwyAAAALM9mmPRbbLVq1VJ4eLhmzJghd3d3SdLly5f17LPPasOGDfr111/NKOO2Sk5Olq+vr5KSkuTj4+PqcmAhPAgacK1Dk9q7ugTcAr6/TTwCuG/fPg0dOtQe/iTJ3d1d0dHR2rdvn1llAAAAWJ5pAfCee+6xX/t3tV27dql27dpmlQEAAGB5Tr0JZPv27fY/Dxw4UIMGDdK+ffvUsGFDSdLGjRv19ttva9KkSc4sAwAAAFdx6jWAbm5ustlsulkXNptNly9fdlYZTsM1BHAVrgEEXItrAAs2vr+dfAr44MGDOnDggA4ePHjD14EDB3K13m+//VYPPfSQgoODZbPZtGjRIof5hmFo1KhRKlOmjLy8vNSqVSvt3bvXYZkzZ86oa9eu8vHxkZ+fn3r37q2UlJRb3WQAAIB8z6mngENDQ52y3vPnz6t27drq1auXOnXqlGX+5MmTNX36dM2ePVthYWF6+eWX1aZNG+3cuVNFihSRJHXt2lXHjh1TXFyc0tPT1bNnT/Xt21fz5s1zSs0AAAD5hakPgj569Ki+//57nThxQpmZmQ7zBg4cmOP1tG3bVm3bts12nmEYmjZtmkaOHKmHH35YkvTRRx8pMDBQixYtUkREhHbt2qXly5frp59+Ur169SRJb775ptq1a6cpU6YoODg4j1sIAACQ/5kWAGNjY9WvXz8VLlxYJUuWlM1ms8+z2Wy5CoA3cvDgQSUkJKhVq1b2Nl9fXzVo0EDx8fGKiIhQfHy8/Pz87OFPklq1aiU3Nzdt2rRJjzzySLbrTk1NVWpqqn06OTn5ttQMAABgJtMC4Msvv6xRo0ZpxIgRcnNz3qWHCQkJkqTAwECH9sDAQPu8hIQEBQQEOMz38PCQv7+/fZnsxMTEaOzYsbe5YgAAAHOZ9hzACxcuKCIiwqnhz9lGjBihpKQk++vIkSOuLgkAACDXTEtjvXv31hdffOH0foKCgiRJx48fd2g/fvy4fV5QUJBOnDjhMD8jI0NnzpyxL5MdT09P+fj4OLwAAAAKGtNOAcfExOjBBx/U8uXLVatWLRUqVMhh/uuvv35b+gkLC1NQUJBWr16tOnXqSPr7Wr1Nmzapf//+kqTw8HAlJiZqy5Ytqlu3riRpzZo1yszMVIMGDW5LHQAAAPmVqQFwxYoVqlKliiRluQkkN1JSUhx+P/jgwYPatm2b/P39dccdd2jw4MGaMGGCKleubH8MTHBwsDp27ChJqlatmh544AH16dNH7777rtLT0xUVFaWIiAjuAAYAAP96pgXAqVOn6sMPP1SPHj1ueV2bN29W8+bN7dPR0dGSpO7duys2NlbPP/+8zp8/r759+yoxMVFNmjTR8uXL7c8AlKS5c+cqKipKLVu2lJubmzp37qzp06ffcm0AAAD5nVN/Cu5qQUFB+u6771S5cmUzujMFPyUDV+Gn4ADX4qfgCja+v028CWTQoEF68803zeoOAAAA12HaKeAff/xRa9as0ZIlS1SjRo0sN4EsWLDArFIAAAAszbQA6Ofnl+3v9gIAAMBcpgXAWbNmmdUVAAAAbqDg/iwHAAAA8sS0I4BhYWE3fN7fgQMHzCoFAADA0kwLgIMHD3aYTk9P19atW7V8+XINGzbMrDIAAAAsz7QAOGjQoGzb3377bW3evNmsMgAAACzP5dcAtm3bVl9++aWrywAAALAMlwfA+fPny9/f39VlAAAAWIZpp4Dvvvtuh5tADMNQQkKCTp48qXfeecesMgAAACzPtADYsWNHh2k3NzeVLl1azZo1U9WqVc0qAwAAwPJMC4CjR482qysAAADcgMuvAQQAAIC5nH4E0M3N7YYPgJYkm82mjIwMZ5cCAAAAmRAAFy5ceN158fHxmj59ujIzM51dBgAAAP7h9AD48MMPZ2nbvXu3hg8frsWLF6tr164aN26cs8sAAADAP0y9BvDo0aPq06ePatWqpYyMDG3btk2zZ89WaGiomWUAAABYmikBMCkpSS+88IIqVaqkHTt2aPXq1Vq8eLFq1qxpRvcAAAC4itNPAU+ePFmvvvqqgoKC9Mknn2R7ShgAAADmsRmGYTizAzc3N3l5ealVq1Zyd3e/7nILFixwZhlOkZycLF9fXyUlJcnHx8fV5cBCyg//xtUlAJZ2aFJ7V5eAW8D3twlHALt163bTx8AAAADAPE4PgLGxsc7uAgAAALnAL4EAAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAx/9oAOGbMGNlsNodX1apV7fMvXbqkyMhIlSxZUsWLF1fnzp11/PhxF1YMAABgjn9tAJSkGjVq6NixY/bX999/b583ZMgQLV68WF988YXWr1+vo0ePqlOnTi6sFgAAwBweri7AmTw8PBQUFJSlPSkpSTNnztS8efPUokULSdKsWbNUrVo1bdy4UQ0bNjS7VAAAANP8q48A7t27V8HBwapQoYK6du2qw4cPS5K2bNmi9PR0tWrVyr5s1apVdccddyg+Pt5V5QIAAJjiX3sEsEGDBoqNjVWVKlV07NgxjR07Vvfee69+++03JSQkqHDhwvLz83N4T2BgoBISEq67ztTUVKWmptqnk5OTnVU+AACA0/xrA2Dbtm3tf77rrrvUoEEDhYaG6vPPP5eXl1ee1hkTE6OxY8ferhIBAABc4l99Cvhqfn5+uvPOO7Vv3z4FBQUpLS1NiYmJDsscP34822sGrxgxYoSSkpLsryNHjji5agAAgNvPMgEwJSVF+/fvV5kyZVS3bl0VKlRIq1evts/fvXu3Dh8+rPDw8Ouuw9PTUz4+Pg4vAACAguZfewr4ueee00MPPaTQ0FAdPXpUo0ePlru7u7p06SJfX1/17t1b0dHR8vf3l4+PjwYMGKDw8HDuAAYAAP96/9oA+Oeff6pLly46ffq0SpcurSZNmmjjxo0qXbq0JOmNN96Qm5ubOnfurNTUVLVp00bvvPOOi6sGAABwPpthGIariyiokpOT5evrq6SkJE4Hw1Tlh3/j6hIASzs0qb2rS8At4PvbQtcAAgAA4G8EQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFiMh6sLAACgoCmIv8fN7xfjahwBBAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACL4S5gWF5BvJsPAIBbwRFAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABbj4eoCAACA85Uf/o2rS8i1Q5Pau7qEfy3LHwF8++23Vb58eRUpUkQNGjTQjz/+6OqSAAAAnMrSAfCzzz5TdHS0Ro8erZ9//lm1a9dWmzZtdOLECVeXBgAA4DQ2wzAMVxfhKg0aNFD9+vX11ltvSZIyMzMVEhKiAQMGaPjw4Td9f3Jysnx9fZWUlCQfH5/bXl9BPFwPAMDt4qxTwM7+/i4ILHsNYFpamrZs2aIRI0bY29zc3NSqVSvFx8dn+57U1FSlpqbap5OSkiT9vSM5Q2bqBaesFwCAgsBZ369X1mvhY2DWDYCnTp3S5cuXFRgY6NAeGBio33//Pdv3xMTEaOzYsVnaQ0JCnFIjAABW5jvNues/d+6cfH19ndtJPmXZAJgXI0aMUHR0tH06MzNTZ86cUcmSJWWz2Zzad3JyskJCQnTkyBHLHq6+VYzh7cE43jrG8PZgHG+dVcfQMAydO3dOwcHBri7FZSwbAEuVKiV3d3cdP37cof348eMKCgrK9j2enp7y9PR0aPPz83NWidny8fGx1F9SZ2AMbw/G8dYxhrcH43jrrDiGVj3yd4Vl7wIuXLiw6tatq9WrV9vbMjMztXr1aoWHh7uwMgAAAOey7BFASYqOjlb37t1Vr149/ec//9G0adN0/vx59ezZ09WlAQAAOI2lA+ATTzyhkydPatSoUUpISFCdOnW0fPnyLDeG5Aeenp4aPXp0llPQyDnG8PZgHG8dY3h7MI63jjG0Lks/BxAAAMCKLHsNIAAAgFURAAEAACyGAAgAAGAxBEAAAACLIQDmAzExMapfv768vb0VEBCgjh07avfu3Td8z4IFC1SvXj35+fmpWLFiqlOnjubMmWNSxflPXsbwap9++qlsNps6duzovCILgLyMY2xsrGw2m8OrSJEiJlWc/+R1X0xMTFRkZKTKlCkjT09P3XnnnVq6dKkJFedPeRnHZs2aZdkXbTab2rdvb1LV+Ute98Vp06apSpUq8vLyUkhIiIYMGaJLly6ZUDHMRADMB9avX6/IyEht3LhRcXFxSk9PV+vWrXX+/Pnrvsff318vvfSS4uPjtX37dvXs2VM9e/bUihUrTKw8/8jLGF5x6NAhPffcc7r33ntNqDR/y+s4+vj46NixY/bXH3/8YVLF+U9exjAtLU3333+/Dh06pPnz52v37t16//33VbZsWRMrz1/yMo4LFixw2A9/++03ubu767HHHjOx8vwjL2M4b948DR8+XKNHj9auXbs0c+ZMffbZZ3rxxRdNrBymMJDvnDhxwpBkrF+/Plfvu/vuu42RI0c6qaqCJadjmJGRYTRq1Mj44IMPjO7duxsPP/ywOQUWEDkZx1mzZhm+vr7mFVXA5GQMZ8yYYVSoUMFIS0szsbKCJS//Lr7xxhuGt7e3kZKS4sTKCo6cjGFkZKTRokULh7bo6GijcePGzi4PJuMIYD6UlJQk6e+jfDlhGIZWr16t3bt3q2nTps4srcDI6RiOGzdOAQEB6t27txllFTg5HceUlBSFhoYqJCREDz/8sHbs2GFGeQVCTsbw66+/Vnh4uCIjIxUYGKiaNWtq4sSJunz5slll5nu5/XdRkmbOnKmIiAgVK1bMWWUVKDkZw0aNGmnLli368ccfJUkHDhzQ0qVL1a5dO1NqhIlcnUDh6PLly0b79u1z9H9biYmJRrFixQwPDw/D09PTmDlzpgkV5n85HcPvvvvOKFu2rHHy5EnDMAyOAF4jp+O4YcMGY/bs2cbWrVuNdevWGQ8++KDh4+NjHDlyxKRK86+cjmGVKlUMT09Po1evXsbmzZuNTz/91PD39zfGjBljUqX5W27+Xbxi06ZNhiRj06ZNTqys4MjNGP73v/81ChUqZHh4eBiSjGeeecaECmE2AmA+88wzzxihoaE5+vK8fPmysXfvXmPr1q3GlClTDF9fX2Pt2rXOLzKfy8kYJicnG+XLlzeWLl1qbyMAOsrNvni1tLQ0o2LFilyOYOR8DCtXrmyEhIQYGRkZ9rapU6caQUFBzi6xQMjLvti3b1+jVq1aTqyqYMnpGK5du9YIDAw03n//fWP79u3GggULjJCQEGPcuHEmVQqzEADzkcjISKNcuXLGgQMH8vT+3r17G61bt77NVRUsOR3DrVu3GpIMd3d3+8tmsxk2m81wd3c39u3bZ1LF+dOt7ouPPvqoERERcZurKlhyM4ZNmzY1WrZs6dC2dOlSQ5KRmprqrBILhLzsiykpKYaPj48xbdo0J1ZWcORmDJs0aWI899xzDm1z5swxvLy8jMuXLzurRLgA1wDmA4ZhKCoqSgsXLtSaNWsUFhaWp/VkZmYqNTX1NldXMOR2DKtWrapff/1V27Zts786dOig5s2ba9u2bQoJCTGp8vzlduyLly9f1q+//qoyZco4ocL8Ly9j2LhxY+3bt0+ZmZn2tj179qhMmTIqXLiwM8vNt25lX/ziiy+UmpqqJ5980okV5n95GcMLFy7Izc0xGri7u9vXh38RF4ZP/KN///6Gr6+vsW7dOuPYsWP214ULF+zLPPXUU8bw4cPt0xMnTjRWrlxp7N+/39i5c6cxZcoUw8PDw3j//fddsQkul5cxvBangPM2jmPHjjVWrFhh7N+/39iyZYsRERFhFClSxNixY4crNsHl8jKGhw8fNry9vY2oqChj9+7dxpIlS4yAgABjwoQJrtiEfOFW/k43adLEeOKJJ8wsN1/KyxiOHj3a8Pb2Nj755BPjwIEDxsqVK42KFSsajz/+uCs2AU5EAMwHJGX7mjVrln2Z++67z+jevbt9+qWXXjIqVapkFClSxChRooQRHh5ufPrpp+YXn0/kZQyvRQDM2zgOHjzYuOOOO4zChQsbgYGBRrt27Yyff/7Z/OLzibzuixs2bDAaNGhgeHp6GhUqVDBeeeUVh2sCrSav4/j7778bkoyVK1eaW3A+lJcxTE9PN8aMGWNUrFjRKFKkiBESEmI8++yzxtmzZ02vH85lMwyO6QIAAFgJ1wACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAx/w86ykizJIFCdgAAAABJRU5ErkJggg==",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' 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+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d92cc040949f498db4ea629de588b897",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a04cb0098fd54e1d84ebfe36bd951d48",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5ae4bb20613f4ee3b22f37c6fb4b6e31",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "56b3aacc3ca54947a64e51b6bf72d403",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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HixNens5P3339e2bdv08ssvKykpyfXAzVl5eXm/OwNXrVq1Cy7rAgAXiwAIoNS1adNGqampmj59uvLy8lSjRg099thjtv+e1wceeECHDx9Wz549lZycXGz7008/XWL7ufbt2+dakgUA/ijuAQSAy8TevXt/92vq2rVrp4CAAIsqAnClIgACAADYDA+BAAAA2Az3AP4JTqdTBw8eVOXKlfk6IwAAygljjE6ePKmoqCh5edlzLowA+CccPHjQ1k80AgBQnh04cEBXX321p8vwCALgn1C5cmVJv/wDCgoK8nA1AADgYuTm5io6Otr1d9yOCIB/wtnLvkFBQQRAAADKGTvfvlUuL3ynpKTohhtuUOXKlRUeHq5evXppx44dbvt07NhRDofD7XXfffe57ZOZman4+HhVqFBB4eHhGjdunAoLC608FQAAAMuVyxnA9PR0JSYm6oYbblBhYaEeeeQRde3aVdu2bXNbWX/YsGGaNm2a632FChVcPxcVFSk+Pl6RkZH68ssvdejQIQ0cOFC+vr564oknLD0fAAAAK10R6wAePXpU4eHhSk9Pd33PaMeOHdWsWTPNnj27xM+sWLFCt9xyiw4ePKiIiAhJ0ksvvaTx48fr6NGj8vPz+91+c3NzFRwcrJycHC4BAwBQTvD3u5xeAj5fTk6OJCk0NNStfeHChQoLC1OjRo00ceJEnT592rVtzZo1aty4sSv8SVK3bt2Um5urrVu3lthPfn6+cnNz3V4AAADlTbm8BHwup9Op0aNHq23btmrUqJGr/e6771bNmjUVFRWlTZs2afz48dqxY4eWLl0qScrKynILf5Jc77OyskrsKyUl5Xe/pxMAAOByV+4DYGJiorZs2aLPP//crX348OGunxs3bqzq1aurS5cu2rNnj2rXrv2H+po4caLGjh3ren/2MXIAAIDypFxfAk5KStLy5cv18ccf/+5Cjq1atZIk7d69W5IUGRmpw4cPu+1z9n1kZGSJx/D393ct+cLSLwAAoLwqlwHQGKOkpCS9++67Wr16tWJiYn73MxkZGZKk6tWrS5JiY2O1efNmHTlyxLVPamqqgoKC1KBBgzKpGwAA4HJQLi8BJyYmatGiRXrvvfdUuXJl1z17wcHBCgwM1J49e7Ro0SL17NlTVatW1aZNmzRmzBi1b99eTZo0kSR17dpVDRo00IABAzRr1ixlZWXp0UcfVWJiovz9/T15egAAAGWqXC4Dc6GVu+fPn69BgwbpwIEDuueee7RlyxadOnVK0dHRuuOOO/Too4+6Xbb9/vvvNWLECH3yySeqWLGiEhISNHPmTPn4XFwu5jFyAADKH/5+l9MAeLngHxAAAOUPf7/L6T2AAAAA+OMIgAAAADZDAAQAALCZcvkUMIDyp9aEDzxdwiXbPzPe0yUAQJlgBhAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDM+ni4AwKWrNeEDT5cAACjHmAEEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzZTLAJiSkqIbbrhBlStXVnh4uHr16qUdO3a47fPzzz8rMTFRVatWVaVKldSnTx8dPnzYbZ/MzEzFx8erQoUKCg8P17hx41RYWGjlqQAAAFiuXAbA9PR0JSYm6quvvlJqaqoKCgrUtWtXnTp1yrXPmDFj9P7772vx4sVKT0/XwYMH1bt3b9f2oqIixcfH68yZM/ryyy/1+uuva8GCBZoyZYonTgkAAMAyDmOM8XQRf9bRo0cVHh6u9PR0tW/fXjk5OapWrZoWLVqkv/zlL5Kk7777Ttddd53WrFmj1q1ba8WKFbrlllt08OBBRURESJJeeukljR8/XkePHpWfn9/v9pubm6vg4GDl5OQoKCioTM8ROFetCR94ugRb2D8z3tMlACgD/P0upzOA58vJyZEkhYaGSpI2btyogoICxcXFufapX7++atSooTVr1kiS1qxZo8aNG7vCnyR169ZNubm52rp1a4n95OfnKzc31+0FAABQ3pT7AOh0OjV69Gi1bdtWjRo1kiRlZWXJz89PISEhbvtGREQoKyvLtc+54e/s9rPbSpKSkqLg4GDXKzo6upTPBgAAoOyV+wCYmJioLVu26O233y7zviZOnKicnBzX68CBA2XeJwAAQGnz8XQBf0ZSUpKWL1+uTz/9VFdffbWrPTIyUmfOnFF2drbbLODhw4cVGRnp2mfdunVuxzv7lPDZfc7n7+8vf3//Uj4LAAAAa5XLGUBjjJKSkvTuu+9q9erViomJcdveokUL+fr6Ki0tzdW2Y8cOZWZmKjY2VpIUGxurzZs368iRI659UlNTFRQUpAYNGlhzIgAAAB5QLmcAExMTtWjRIr333nuqXLmy65694OBgBQYGKjg4WEOHDtXYsWMVGhqqoKAgPfDAA4qNjVXr1q0lSV27dlWDBg00YMAAzZo1S1lZWXr00UeVmJjILB8AALiilcsAOG/ePElSx44d3drnz5+vQYMGSZKee+45eXl5qU+fPsrPz1e3bt304osvuvb19vbW8uXLNWLECMXGxqpixYpKSEjQtGnTrDoNAAAAj7gi1gH0FNYRgqewDqA1WAcQuDLx97uc3gMIAACAP44ACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDOWBcCvv/5amzdvdr1/77331KtXLz3yyCM6c+aMVWUAAADYnmUB8N5779XOnTslSXv37lXfvn1VoUIFLV68WA8//LBVZQAAANieZQFw586datasmSRp8eLFat++vRYtWqQFCxbonXfesaoMAAAA27MsABpj5HQ6JUn//e9/1bNnT0lSdHS0fvzxR6vKAAAAsD3LAmDLli01Y8YMvfnmm0pPT1d8fLwkad++fYqIiLCqDAAAANuzLADOnj1bX3/9tZKSkjRp0iTVqVNHkrRkyRK1adPGqjIAAABsz8eqjpo0aeL2FPBZTz31lLy9va0qAwAAwPYsXQcwOztbr7zyiiZOnKjjx49LkrZt26YjR45YWQYAAICtWTYDuGnTJnXp0kUhISHav3+/hg0bptDQUC1dulSZmZl64403rCoFAADA1iwLgGPHjtXgwYM1a9YsVa5c2dXes2dP3X333VaVARRTa8IHni4BAABLWXYJeP369br33nuLtV911VXKysqyqgwAAADbsywA+vv7Kzc3t1j7zp07Va1aNavKAAAAsD3LAuBtt92madOmqaCgQJLkcDiUmZmp8ePHq0+fPlaVAQAAYHuWBcBnnnlGeXl5Cg8P108//aQOHTqoTp06qly5sh5//HGrygAAALA9yx4CCQ4OVmpqqr744gt9++23ysvL0/XXX6+4uDirSgAAAIAsDIBntW3bVm3btrW6WwAAAPzKskvAI0eO1Jw5c4q1v/DCCxo9erRVZQAAANieZQHwnXfeKXHmr02bNlqyZIlVZQAAANieZQHw2LFjCg4OLtYeFBSkH3/80aoyAAAAbM+yAFinTh2tXLmyWPuKFSt0zTXXWFUGAACA7Vn6VXBJSUk6evSoOnfuLElKS0vTM888o9mzZ1tVBgAAgO1ZFgCHDBmi/Px8Pf7445o+fbokqVatWpo3b54GDhxoVRkAAAC2Z+kyMCNGjNCIESN09OhRBQYGqlKlSlZ2DwAAAHlgHUBJfPcvAACAB1n2EMjhw4c1YMAARUVFycfHR97e3m4vAAAAWMOyGcBBgwYpMzNTkydPVvXq1eVwOKzqGgAAAOewLAB+/vnn+uyzz9SsWTOrugQAAEAJLLsEHB0dLWOMVd0BAADgAiwLgLNnz9aECRO0f/9+q7oEAABACSy7BHzXXXfp9OnTql27tipUqCBfX1+37cePH7eqFAAAAFuzLADybR8AAACXB8sCYEJCglVdAQAA4DdYdg+gJO3Zs0ePPvqo+vXrpyNHjkiSVqxYoa1bt1pZBgAAgK1ZFgDT09PVuHFjrV27VkuXLlVeXp4k6dtvv9XUqVOtKgMAAMD2LAuAEyZM0IwZM5Samio/Pz9Xe+fOnfXVV19ZVQYAAIDtWRYAN2/erDvuuKNYe3h4uH788UerygAAALA9ywJgSEiIDh06VKz9m2++0VVXXWVVGQAAALZnWQDs27evxo8fr6ysLDkcDjmdTn3xxRd66KGHNHDgQKvKAAAAsD3LAuATTzyh+vXrKzo6Wnl5eWrQoIHat2+vNm3a6NFHH7WqDAAAANuzZB1AY4yysrI0Z84cTZkyRZs3b1ZeXp6aN2+uunXrWlECAAAAfmVZAKxTp462bt2qunXrKjo62opuAQAAUAJLLgF7eXmpbt26OnbsmBXdAQAA4DdYdg/gzJkzNW7cOG3ZssWqLgEAAFACywLgwIEDtW7dOjVt2lSBgYEKDQ11e12KTz/9VLfeequioqLkcDi0bNkyt+2DBg2Sw+Fwe3Xv3t1tn+PHj6t///4KCgpSSEiIhg4d6vp2EgAAgCuZJfcAStLs2bNL7VinTp1S06ZNNWTIEPXu3bvEfbp376758+e73vv7+7tt79+/vw4dOqTU1FQVFBRo8ODBGj58uBYtWlRqdQIAAFyOLAmABQUFSk9P1+TJkxUTE/Onj9ejRw/16NHjN/fx9/dXZGRkidu2b9+ulStXav369WrZsqUk6fnnn1fPnj319NNPKyoq6k/XCAAAcLmy5BKwr6+v3nnnHSu6cvnkk08UHh6uevXqacSIEW4PoKxZs0YhISGu8CdJcXFx8vLy0tq1ay2tEwAAwGqW3QPYq1evYvfqlZXu3bvrjTfeUFpamp588kmlp6erR48eKioqkiRlZWUpPDzc7TM+Pj4KDQ1VVlbWBY+bn5+v3NxctxcAAEB5Y9k9gHXr1tW0adP0xRdfqEWLFqpYsaLb9pEjR5ZaX3379nX93LhxYzVp0kS1a9fWJ598oi5duvzh46akpCg5Obk0SgQAAPAYywLgq6++qpCQEG3cuFEbN2502+ZwOEo1AJ7vmmuuUVhYmHbv3q0uXbooMjJSR44ccdunsLBQx48fv+B9g5I0ceJEjR071vU+NzeXRa0BAEC5Y1kA3Ldvn1VdFfO///1Px44dU/Xq1SVJsbGxys7O1saNG9WiRQtJ0urVq+V0OtWqVasLHsff37/Y08QAAADljWUBsDTl5eVp9+7drvf79u1TRkaGa03B5ORk9enTR5GRkdqzZ48efvhh1alTR926dZMkXXfdderevbuGDRuml156SQUFBUpKSlLfvn15AhgAAFzxLAuAQ4YM+c3tr7322kUfa8OGDerUqZPr/dnLsgkJCZo3b542bdqk119/XdnZ2YqKilLXrl01ffp0t9m7hQsXKikpSV26dJGXl5f69OmjOXPmXOJZAQAAlD+WBcATJ064vS8oKNCWLVuUnZ2tzp07X9KxOnbsKGPMBbevWrXqd48RGhrKos8AAMCWLAuA7777brE2p9OpESNGqHbt2laVAQAAYHuWrQNYYudeXho7dqyee+45T5YBAABgKx4NgJK0Z88eFRYWeroMAAAA27DsEvC56+dJkjFGhw4d0gcffKCEhASrygAAALA9ywLgN9984/bey8tL1apV0zPPPPO7TwgDAACg9FgWAD/++GOrugIAAMBvsOwewH379mnXrl3F2nft2qX9+/dbVQYAAIDtWTYDOGjQIA0ZMkR169Z1a1+7dq1eeeUVffLJJ1aVAgAXpdaEDzxdwiXbPzPe0yUAKAcsmwH85ptv1LZt22LtrVu3VkZGhlVlAAAA2J5lAdDhcOjkyZPF2nNyclRUVGRVGQAAALZnWQBs3769UlJS3MJeUVGRUlJS1K5dO6vKAAAAsD3L7gF88skn1b59e9WrV0833XSTJOmzzz5Tbm6uVq9ebVUZAAAAtmfZDGCDBg20adMm/fWvf9WRI0d08uRJDRw4UN99950aNWpkVRkAAAC2Z9kMoCRFRUXpiSeesLJLAAAAnMeyGcD58+dr8eLFxdoXL16s119/3aoyAAAAbM+yAJiSkqKwsLBi7eHh4cwKAgAAWMiyAJiZmamYmJhi7TVr1lRmZqZVZQAAANieZQEwPDxcmzZtKtb+7bffqmrVqlaVAQAAYHuWBcB+/fpp5MiR+vjjj1VUVKSioiKtXr1ao0aNUt++fa0qAwAAwPYsewp4+vTp2r9/v7p06SIfn1+6dTqdGjhwIPcAAgAAWMiyAOjn56d//etfmj59ur799lsFBgaqcePGqlmzplUlAAAAQBavAyhJoaGh6tSpU4lPBAMAAKDsWXIPYHZ2thITExUWFqaIiAhFREQoLCxMSUlJys7OtqIEAAAA/KrMZwCPHz+u2NhY/fDDD+rfv7+uu+46SdK2bdu0YMECpaWl6csvv1SVKlXKuhQAAADIggA4bdo0+fn5ac+ePYqIiCi2rWvXrpo2bZqee+65si4FAAAAsuAS8LJly/T0008XC3+SFBkZqVmzZundd98t6zIAAADwqzIPgIcOHVLDhg0vuL1Ro0bKysoq6zIAAADwqzIPgGFhYdq/f/8Ft+/bt0+hoaFlXQYAAAB+VeYBsFu3bpo0aZLOnDlTbFt+fr4mT56s7t27l3UZAAAA+JUlD4G0bNlSdevWVWJiourXry9jjLZv364XX3xR+fn5evPNN8u6DAAAAPyqzAPg1VdfrTVr1uj+++/XxIkTZYyRJDkcDt1888164YUXFB0dXdZlAAAA4FeWfBNITEyMVqxYoRMnTmjXrl2SpDp16nDvHwAAgAdY+lVwVapU0Y033mhllwAAADiPJV8FBwAAgMsHARAAAMBmCIAAAAA2U6YB8Prrr9eJEyck/bIczOnTp8uyOwAAAFyEMg2A27dv16lTpyRJycnJysvLK8vuAAAAcBHK9CngZs2aafDgwWrXrp2MMXr66adVqVKlEvedMmVKWZYCAACAX5VpAFywYIGmTp2q5cuXy+FwaMWKFfLxKd6lw+EgAAIAAFikTANgvXr19Pbbb0uSvLy8lJaWpvDw8LLsEgAAAL/DsoWgnU6nVV0BAADgN1j6TSB79uzR7NmztX37dklSgwYNNGrUKNWuXdvKMgAAAGzNsnUAV61apQYNGmjdunVq0qSJmjRporVr16phw4ZKTU21qgwAAADbs2wGcMKECRozZoxmzpxZrH38+PG6+eabrSoFAADA1iybAdy+fbuGDh1arH3IkCHatm2bVWUAAADYnmUBsFq1asrIyCjWnpGRwZPBAAAAFrLsEvCwYcM0fPhw7d27V23atJEkffHFF3ryySc1duxYq8oAAACwPcsC4OTJk1W5cmU988wzmjhxoiQpKipKjz32mEaOHGlVGQAAALZnWQB0OBwaM2aMxowZo5MnT0qSKleubFX3AAAA+JWl6wCeRfADAADwHMseAgEAAMDlgQAIAABgMwRAAAAAm7EkABYUFKhLly7atWuXFd0BAADgN1gSAH19fbVp0yYrugIAAMDvsOwS8D333KNXX33Vqu4AAABwAZYtA1NYWKjXXntN//3vf9WiRQtVrFjRbfuzzz5rVSkAAAC2ZlkA3LJli66//npJ0s6dO922ORwOq8oAAACwPcsC4Mcff2xVVwAAAPgNli8Ds3v3bq1atUo//fSTJMkYY3UJAAAAtmZZADx27Ji6dOmia6+9Vj179tShQ4ckSUOHDtWDDz5oVRkAAAC2Z1kAHDNmjHx9fZWZmakKFSq42u+66y6tXLnyko716aef6tZbb1VUVJQcDoeWLVvmtt0YoylTpqh69eoKDAxUXFxcsTUIjx8/rv79+ysoKEghISEaOnSo8vLy/vD5AQAAlBeW3QP40UcfadWqVbr66qvd2uvWravvv//+ko516tQpNW3aVEOGDFHv3r2LbZ81a5bmzJmj119/XTExMZo8ebK6deumbdu2KSAgQJLUv39/HTp0SKmpqSooKNDgwYM1fPhwLVq06I+fJAB4WK0JH3i6hEu2f2a8p0sAbMeyAHjq1Cm3mb+zjh8/Ln9//0s6Vo8ePdSjR48StxljNHv2bD366KO6/fbbJUlvvPGGIiIitGzZMvXt21fbt2/XypUrtX79erVs2VKS9Pzzz6tnz556+umnFRUVdYlnBwAAUH5Ydgn4pptu0htvvOF673A45HQ6NWvWLHXq1KnU+tm3b5+ysrIUFxfnagsODlarVq20Zs0aSdKaNWsUEhLiCn+SFBcXJy8vL61du/aCx87Pz1dubq7bCwAAoLyxbAZw1qxZ6tKlizZs2KAzZ87o4Ycf1tatW3X8+HF98cUXpdZPVlaWJCkiIsKtPSIiwrUtKytL4eHhbtt9fHwUGhrq2qckKSkpSk5OLrVaAQAAPMGyGcBGjRpp586dateunW6//XadOnVKvXv31jfffKPatWtbVcafMnHiROXk5LheBw4c8HRJAAAAl8yyGUDpl0uxkyZNKtM+IiMjJUmHDx9W9erVXe2HDx9Ws2bNXPscOXLE7XOFhYU6fvy46/Ml8ff3v+T7FQEAAC43lgbAEydO6NVXX9X27dslSQ0aNNDgwYMVGhpaan3ExMQoMjJSaWlprsCXm5urtWvXasSIEZKk2NhYZWdna+PGjWrRooUkafXq1XI6nWrVqlWp1QIAAHA5suwS8KeffqpatWppzpw5OnHihE6cOKE5c+YoJiZGn3766SUdKy8vTxkZGcrIyJD0y4MfGRkZyszMlMPh0OjRozVjxgz95z//0ebNmzVw4EBFRUWpV69ekqTrrrtO3bt317Bhw7Ru3Tp98cUXSkpKUt++fXkCGAAAXPEsmwFMTEzUXXfdpXnz5snb21uSVFRUpPvvv1+JiYnavHnzRR9rw4YNbk8Ojx07VpKUkJCgBQsW6OGHH9apU6c0fPhwZWdnq127dlq5cqVrDUBJWrhwoZKSktSlSxd5eXmpT58+mjNnTimdLQAAwOXLYSz6Mt7AwEBlZGSoXr16bu07duxQs2bNXN8NXJ7k5uYqODhYOTk5CgoK8nQ5+IPK48K5wJWEhaBhNf5+W3gJ+Prrr3fd+3eu7du3q2nTplaVAQAAYHtlegl406ZNrp9HjhypUaNGaffu3WrdurUk6auvvtLcuXM1c+bMsiwDAAAA5yjTS8BeXl5yOBz6vS4cDoeKiorKqowywxTylYFLwIBncQkYVuPvdxnPAO7bt68sDw8AAIA/oEwDYM2aNcvy8AAAAPgDLF0I+uDBg/r888915MgROZ1Ot20jR460shQAAADbsiwALliwQPfee6/8/PxUtWpVORwO1zaHw0EABAAAsIhlAXDy5MmaMmWKJk6cKC8vy1afAQAAwHksS2KnT59W3759CX8AAAAeZlkaGzp0qBYvXmxVdwAAALgAyy4Bp6Sk6JZbbtHKlSvVuHFj+fr6um1/9tlnrSoFAADA1iwNgKtWrXJ9F/D5D4EAAADAGpYFwGeeeUavvfaaBg0aZFWXAAAAKIFl9wD6+/urbdu2VnUHAACAC7AsAI4aNUrPP/+8Vd0BAADgAiy7BLxu3TqtXr1ay5cvV8OGDYs9BLJ06VKrSgEAALA1ywJgSEiIevfubVV3AAAAuADLAuD8+fOt6goAAAC/ga/lAAAAsBnLZgBjYmJ+c72/vXv3WlUKAACArVkWAEePHu32vqCgQN98841WrlypcePGWVUGAACA7VkWAEeNGlVi+9y5c7VhwwarygAAALA9j98D2KNHD73zzjueLgMAAMA2PB4AlyxZotDQUE+XAQAAYBuWXQJu3ry520MgxhhlZWXp6NGjevHFF60qAwAAwPYsC4C9evVye+/l5aVq1aqpY8eOql+/vlVlAAAA2J5lAXDq1KlWdQUAAIDf4PF7AAEAAGCtMp8B9PLy+s0FoCXJ4XCosLCwrEsBAACALAiA77777gW3rVmzRnPmzJHT6SzrMgAAAPCrMg+At99+e7G2HTt2aMKECXr//ffVv39/TZs2razLAAAAwK8svQfw4MGDGjZsmBo3bqzCwkJlZGTo9ddfV82aNa0sAwAAwNYsCYA5OTkaP3686tSpo61btyotLU3vv/++GjVqZEX3AAAAOEeZXwKeNWuWnnzySUVGRuqtt94q8ZIwAAAArOMwxpiy7MDLy0uBgYGKi4uTt7f3BfdbunRpWZZRJnJzcxUcHKycnBwFBQV5uhz8QbUmfODpEgBb2z8z3tMlwGb4+23BDODAgQN/dxkYAAAAWKfMA+CCBQvKugsAAABcAr4JBAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2MwVGwAfe+wxORwOt1f9+vVd23/++WclJiaqatWqqlSpkvr06aPDhw97sGIAAABrXLEBUJIaNmyoQ4cOuV6ff/65a9uYMWP0/vvva/HixUpPT9fBgwfVu3dvD1YLAABgDR9PF1CWfHx8FBkZWaw9JydHr776qhYtWqTOnTtLkubPn6/rrrtOX331lVq3bm11qQAAAJa5omcAd+3apaioKF1zzTXq37+/MjMzJUkbN25UQUGB4uLiXPvWr19fNWrU0Jo1azxVLgAAgCWu2BnAVq1aacGCBapXr54OHTqk5ORk3XTTTdqyZYuysrLk5+enkJAQt89EREQoKyvrgsfMz89Xfn6+631ubm5ZlQ8AAFBmrtgA2KNHD9fPTZo0UatWrVSzZk39+9//VmBg4B86ZkpKipKTk0urxCtSrQkfeLoEAADwO67oS8DnCgkJ0bXXXqvdu3crMjJSZ86cUXZ2tts+hw8fLvGewbMmTpyonJwc1+vAgQNlXDUAAEDps00AzMvL0549e1S9enW1aNFCvr6+SktLc23fsWOHMjMzFRsbe8Fj+Pv7KygoyO0FAABQ3lyxl4Afeugh3XrrrapZs6YOHjyoqVOnytvbW/369VNwcLCGDh2qsWPHKjQ0VEFBQXrggQcUGxvLE8AAAOCKd8UGwP/973/q16+fjh07pmrVqqldu3b66quvVK1aNUnSc889Jy8vL/Xp00f5+fnq1q2bXnzxRQ9XDQAAUPYcxhjj6SLKq9zcXAUHBysnJ4fLwb/iIRAAl2r/zHhPlwCb4e+3je4BBAAAwC8IgAAAADZDAAQAALAZAiAAAIDNEAABAABshgAIAABgMwRAAAAAmyEAAgAA2AwBEAAAwGYIgAAAADZDAAQAALAZH08XAACwt/L4HeJ8fzHKO2YAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJshAAIAANgMARAAAMBmCIAAAAA2QwAEAACwGQIgAACAzRAAAQAAbIYACAAAYDMEQAAAAJvx8XQBAACUN7UmfODpEi7Z/pnxni4BlxFmAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkfTxcAAADKXq0JH3i6hEu2f2a8p0u4YjEDCAAAYDMEQAAAAJvhEvBlrDxO1wMAgMsfM4AAAAA2QwAEAACwGQIgAACAzdg+AM6dO1e1atVSQECAWrVqpXXr1nm6JAAAgDJl6wD4r3/9S2PHjtXUqVP19ddfq2nTpurWrZuOHDni6dIAAADKjK0D4LPPPqthw4Zp8ODBatCggV566SVVqFBBr732mqdLAwAAKDO2XQbmzJkz2rhxoyZOnOhq8/LyUlxcnNasWVPiZ/Lz85Wfn+96n5OTI0nKzc0tkxqd+afL5LgAAJQHZfX39exxjTFlcvzywLYB8Mcff1RRUZEiIiLc2iMiIvTdd9+V+JmUlBQlJycXa4+Oji6TGgEAsLPg2WV7/JMnTyo4OLhsO7lM2TYA/hETJ07U2LFjXe+dTqeOHz+uqlWryuFweLCyy0tubq6io6N14MABBQUFebqcKxpjbQ3G2TqMtTXsPs7GGJ08eVJRUVGeLsVjbBsAw8LC5O3trcOHD7u1Hz58WJGRkSV+xt/fX/7+/m5tISEhZVViuRcUFGTL/7B4AmNtDcbZOoy1New8znad+TvLtg+B+Pn5qUWLFkpLS3O1OZ1OpaWlKTY21oOVAQAAlC3bzgBK0tixY5WQkKCWLVvqxhtv1OzZs3Xq1CkNHjzY06UBAACUGVsHwLvuuktHjx7VlClTlJWVpWbNmmnlypXFHgzBpfH399fUqVOLXS5H6WOsrcE4W4extgbjDIex8zPQAAAANmTbewABAADsigAIAABgMwRAAAAAmyEAAgAA2AwBEKVu7ty5qlWrlgICAtSqVSutW7fO0yWVGykpKbrhhhtUuXJlhYeHq1evXtqxY4fbPj///LMSExNVtWpVVapUSX369Cm2oHlmZqbi4+NVoUIFhYeHa9y4cSosLLTyVMqdmTNnyuFwaPTo0a42xrp0/PDDD7rnnntUtWpVBQYGqnHjxtqwYYNruzFGU6ZMUfXq1RUYGKi4uDjt2rXL7RjHjx9X//79FRQUpJCQEA0dOlR5eXlWn8plraioSJMnT1ZMTIwCAwNVu3ZtTZ8+3e37bhlruBigFL399tvGz8/PvPbaa2br1q1m2LBhJiQkxBw+fNjTpZUL3bp1M/PnzzdbtmwxGRkZpmfPnqZGjRomLy/Ptc99991noqOjTVpamtmwYYNp3bq1adOmjWt7YWGhadSokYmLizPffPON+fDDD01YWJiZOHGiJ06pXFi3bp2pVauWadKkiRk1apSrnbH+844fP25q1qxpBg0aZNauXWv27t1rVq1aZXbv3u3aZ+bMmSY4ONgsW7bMfPvtt+a2224zMTEx5qeffnLt0717d9O0aVPz1Vdfmc8++8zUqVPH9OvXzxOndNl6/PHHTdWqVc3y5cvNvn37zOLFi02lSpXM3//+d9c+jDXOIgCiVN14440mMTHR9b6oqMhERUWZlJQUD1ZVfh05csRIMunp6cYYY7Kzs42vr69ZvHixa5/t27cbSWbNmjXGGGM+/PBD4+XlZbKyslz7zJs3zwQFBZn8/HxrT6AcOHnypKlbt65JTU01HTp0cAVAxrp0jB8/3rRr1+6C251Op4mMjDRPPfWUqy07O9v4+/ubt956yxhjzLZt24wks379etc+K1asMA6Hw/zwww9lV3w5Ex8fb4YMGeLW1rt3b9O/f39jDGMNd1wCRqk5c+aMNm7cqLi4OFebl5eX4uLitGbNGg9WVn7l5ORIkkJDQyVJGzduVEFBgdsY169fXzVq1HCN8Zo1a9S4cWO3Bc27deum3Nxcbd261cLqy4fExETFx8e7janEWJeW//znP2rZsqXuvPNOhYeHq3nz5vrHP/7h2r5v3z5lZWW5jXNwcLBatWrlNs4hISFq2bKla5+4uDh5eXlp7dq11p3MZa5NmzZKS0vTzp07JUnffvutPv/8c/Xo0UMSYw13tv4mEJSuH3/8UUVFRcW+SSUiIkLfffedh6oqv5xOp0aPHq22bduqUaNGkqSsrCz5+fkpJCTEbd+IiAhlZWW59inpd3B2G/7P22+/ra+//lrr168vto2xLh179+7VvHnzNHbsWD3yyCNav369Ro4cKT8/PyUkJLjGqaRxPHecw8PD3bb7+PgoNDSUcT7HhAkTlJubq/r168vb21tFRUV6/PHH1b9/f0lirOGGAAhcphITE7VlyxZ9/vnnni7linTgwAGNGjVKqampCggI8HQ5Vyyn06mWLVvqiSeekCQ1b95cW7Zs0UsvvaSEhAQPV3dl+fe//62FCxdq0aJFatiwoTIyMjR69GhFRUUx1iiGS8AoNWFhYfL29i72lOThw4cVGRnpoarKp6SkJC1fvlwff/yxrr76ald7ZGSkzpw5o+zsbLf9zx3jyMjIEn8HZ7fhFxs3btSRI0d0/fXXy8fHRz4+PkpPT9ecOXPk4+OjiIgIxroUVK9eXQ0aNHBru+6665SZmSnp/8bpt/67ERkZqSNHjrhtLyws1PHjxxnnc4wbN04TJkxQ37591bhxYw0YMEBjxoxRSkqKJMYa7giAKDV+fn5q0aKF0tLSXG1Op1NpaWmKjY31YGXlhzFGSUlJevfdd7V69WrFxMS4bW/RooV8fX3dxnjHjh3KzMx0jXFsbKw2b97s9h/x1NRUBQUFFftDbGddunTR5s2blZGR4Xq1bNlS/fv3d/3MWP95bdu2LbaU0c6dO1WzZk1JUkxMjCIjI93GOTc3V2vXrnUb5+zsbG3cuNG1z+rVq+V0OtWqVSsLzqJ8OH36tLy83P+se3t7y+l0SmKscR5PP4WCK8vbb79t/P39zYIFC8y2bdvM8OHDTUhIiNtTkriwESNGmODgYPPJJ5+YQ4cOuV6nT5927XPfffeZGjVqmNWrV5sNGzaY2NhYExsb69p+dmmSrl27moyMDLNy5UpTrVo1lia5COc+BWwMY10a1q1bZ3x8fMzjjz9udu3aZRYuXGgqVKhg/vnPf7r2mTlzpgkJCTHvvfee2bRpk7n99ttLXJqkefPmZu3atebzzz83devWZWmS8yQkJJirrrrKtQzM0qVLTVhYmHn44Ydd+zDWOIsAiFL3/PPPmxo1ahg/Pz9z4403mq+++srTJZUbkkp8zZ8/37XPTz/9ZO6//35TpUoVU6FCBXPHHXeYQ4cOuR1n//79pkePHiYwMNCEhYWZBx980BQUFFh8NuXP+QGQsS4d77//vmnUqJHx9/c39evXNy+//LLbdqfTaSZPnmwiIiKMv7+/6dKli9mxY4fbPseOHTP9+vUzlSpVMkFBQWbw4MHm5MmTVp7GZS83N9eMGjXK1KhRwwQEBJhrrrnGTJo0yW1JIsYaZzmMOWeJcAAAAFzxuAcQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAAAAANkMABAAAsBkCIAAAgM0QAAEAAGyGAAgAAGAzBEAAAACb+f9jtjv6BLc6ZwAAAABJRU5ErkJggg==' width=640.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_dispersion.plots.all()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, one may also export the ellipses to a ``.kml`` file so it can be easily visualized in Google Earth\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_dispersion.export_ellipses_to_kml(\n",
+    "    filename=\"monte_carlo_analysis_outputs/monte_carlo_class_example.kml\",\n",
+    "    origin_lat=env.latitude,\n",
+    "    origin_lon=env.longitude,\n",
+    "    type=\"impact\",\n",
+    ")"
+   ]
+  }
+ ],
+ "metadata": {
+  "hide_input": false,
+  "kernelspec": {
+   "display_name": "Python 3.10.5 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "26de051ba29f2982a8de78e945f0abaf191376122a1563185a90213a26c5da77"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/notebooks/dispersion_analysis/parachute_drop_from_helicopter.ipynb b/docs/notebooks/monte_carlo_analysis/parachute_drop_from_helicopter.ipynb
similarity index 98%
rename from docs/notebooks/dispersion_analysis/parachute_drop_from_helicopter.ipynb
rename to docs/notebooks/monte_carlo_analysis/parachute_drop_from_helicopter.ipynb
index 873cd6301..b0a510b91 100644
--- a/docs/notebooks/dispersion_analysis/parachute_drop_from_helicopter.ipynb
+++ b/docs/notebooks/monte_carlo_analysis/parachute_drop_from_helicopter.ipynb
@@ -14,6 +14,13 @@
     "This is an advanced use of RocketPy. This notebook wraps RocketPy's methods to run a Monte Carlo analysis and predict probability distributions of the rocket's landing point if realeased from a helicopter. This is a common test used to validate the parachute system before a rocket launch."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "TODO: Use the new MonteCarlo class in this notebook"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -391,7 +398,7 @@
    "outputs": [],
    "source": [
     "# Basic analysis info\n",
-    "filename = \"dispersion_analysis_outputs/parachute_drop_from_helicopter\"\n",
+    "filename = \"monte_carlo_analysis_outputs/parachute_drop_from_helicopter\"\n",
     "number_of_simulations = 4000\n",
     "\n",
     "# Create data files for inputs, outputs and error logging\n",
@@ -411,7 +418,7 @@
     "Env.maxExpectedHeight = 1500\n",
     "Env.setAtmosphericModel(\n",
     "    type=\"Ensemble\",\n",
-    "    file=\"dispersion_analysis_inputs/LASC2019_reanalysis.nc\",\n",
+    "    file=\"monte_carlo_analysis_inputs/LASC2019_reanalysis.nc\",\n",
     "    dictionary=\"ECMWF\",\n",
     ")\n",
     "\n",
@@ -435,7 +442,7 @@
     "\n",
     "    # Create motor\n",
     "    Keron = SolidMotor(\n",
-    "        thrustSource=\"dispersion_analysis_inputs/thrustCurve.csv\",\n",
+    "        thrustSource=\"monte_carlo_analysis_inputs/thrustCurve.csv\",\n",
     "        burn_time=5.274,\n",
     "        reshapeThrustCurve=(setting[\"burn_time\"], setting[\"impulse\"]),\n",
     "        nozzle_radius=setting[\"nozzle_radius\"],\n",
@@ -458,8 +465,8 @@
     "        mass=setting[\"rocketMass\"],\n",
     "        inertiaI=setting[\"inertiaI\"],\n",
     "        inertiaZ=setting[\"inertiaZ\"],\n",
-    "        powerOffDrag=\"dispersion_analysis_inputs/Cd_PowerOff.csv\",\n",
-    "        powerOnDrag=\"dispersion_analysis_inputs/Cd_PowerOn.csv\",\n",
+    "        powerOffDrag=\"monte_carlo_analysis_inputs/Cd_PowerOff.csv\",\n",
+    "        powerOnDrag=\"monte_carlo_analysis_inputs/Cd_PowerOn.csv\",\n",
     "        centerOfDryMassPosition=0,\n",
     "        coordinateSystemOrientation=\"tailToNose\",\n",
     "    )\n",
@@ -580,7 +587,7 @@
    },
    "outputs": [],
    "source": [
-    "filename = \"dispersion_analysis_outputs/parachute_drop_from_helicopter\"\n",
+    "filename = \"monte_carlo_analysis_outputs/parachute_drop_from_helicopter\"\n",
     "\n",
     "# Initialize variable to store all results\n",
     "dispersion_general_results = []\n",
@@ -1164,7 +1171,7 @@
     "from matplotlib.patches import Ellipse\n",
     "\n",
     "# Import background map\n",
-    "img = imread(\"dispersion_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
+    "img = imread(\"monte_carlo_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
     "\n",
     "# Retrieve dispersion data por apogee and impact XY position\n",
     "apogeeX = np.array(dispersion_results[\"apogeeX\"])\n",
diff --git a/docs/reference/classes/monte_carlo/index.rst b/docs/reference/classes/monte_carlo/index.rst
new file mode 100644
index 000000000..0f4630696
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/index.rst
@@ -0,0 +1,9 @@
+Monte Carlo Analysis
+====================
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Contents:
+
+   monte_carlo
+   Stochastic models <stochastic_models/index>
diff --git a/docs/reference/classes/monte_carlo/monte_carlo.rst b/docs/reference/classes/monte_carlo/monte_carlo.rst
new file mode 100644
index 000000000..8c127855b
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/monte_carlo.rst
@@ -0,0 +1,5 @@
+Monte Carlo Class
+-----------------
+
+.. autoclass:: rocketpy.simulation.MonteCarlo
+    :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/index.rst b/docs/reference/classes/monte_carlo/stochastic_models/index.rst
new file mode 100644
index 000000000..7bf705347
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/index.rst
@@ -0,0 +1,26 @@
+.. _stochastic_reference:
+
+Stochastic Models
+=================
+
+This section provides detailed API references for the Stochastic models in RocketPy.
+These models extend the standard RocketPy objects by introducing uncertainties to
+input parameters, enabling robust Monte Carlo simulations.
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Contents:
+
+   stochastic_model
+   stochastic_environment
+   stochastic_motor_model
+   stochastic_solid_motor
+   stochastic_generic_motor
+   stochastic_nose_cone
+   stochastic_trapezoidal_fins
+   stochastic_elliptical_fins
+   stochastic_tail
+   stochastic_rail_buttons
+   stochastic_rocket
+   stochastic_parachute
+   stochastic_flight
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_elliptical_fins.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_elliptical_fins.rst
new file mode 100644
index 000000000..f661b6115
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_elliptical_fins.rst
@@ -0,0 +1,5 @@
+Stochastic Elliptical Fins
+--------------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticEllipticalFins
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_environment.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_environment.rst
new file mode 100644
index 000000000..41e12dbd7
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_environment.rst
@@ -0,0 +1,5 @@
+Stochastic Environment
+----------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticEnvironment
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_flight.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_flight.rst
new file mode 100644
index 000000000..c3e7ba85d
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_flight.rst
@@ -0,0 +1,5 @@
+Stochastic Flight
+-----------------
+
+.. autoclass:: rocketpy.stochastic.StochasticFlight
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_generic_motor.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_generic_motor.rst
new file mode 100644
index 000000000..617bfd06e
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_generic_motor.rst
@@ -0,0 +1,5 @@
+Stochastic Generic Motor
+------------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticGenericMotor
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_model.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_model.rst
new file mode 100644
index 000000000..619ca848e
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_model.rst
@@ -0,0 +1,7 @@
+.. _stochastic_model:
+
+Stochastic Model
+-----------------
+
+.. autoclass:: rocketpy.stochastic.StochasticModel
+    :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_motor_model.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_motor_model.rst
new file mode 100644
index 000000000..3f96b4a23
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_motor_model.rst
@@ -0,0 +1,5 @@
+Stochastic Motor Model
+----------------------
+
+.. autoclass:: rocketpy.stochastic.stochastic_motor_model.StochasticMotorModel
+    :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_nose_cone.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_nose_cone.rst
new file mode 100644
index 000000000..cf471219b
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_nose_cone.rst
@@ -0,0 +1,5 @@
+Stochastic Nose Cone
+--------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticNoseCone
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_parachute.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_parachute.rst
new file mode 100644
index 000000000..ffd851dc1
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_parachute.rst
@@ -0,0 +1,5 @@
+Stochastic Parachute
+--------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticParachute
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_rail_buttons.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_rail_buttons.rst
new file mode 100644
index 000000000..7036486aa
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_rail_buttons.rst
@@ -0,0 +1,5 @@
+Stochastic Rail Buttons
+-----------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticRailButtons
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_rocket.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_rocket.rst
new file mode 100644
index 000000000..af262b55b
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_rocket.rst
@@ -0,0 +1,5 @@
+Stochastic Rocket
+-----------------
+
+.. autoclass:: rocketpy.stochastic.StochasticRocket
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_solid_motor.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_solid_motor.rst
new file mode 100644
index 000000000..8135af752
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_solid_motor.rst
@@ -0,0 +1,5 @@
+Stochastic Solid Motor
+----------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticSolidMotor
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_tail.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_tail.rst
new file mode 100644
index 000000000..27c8c321e
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_tail.rst
@@ -0,0 +1,5 @@
+Stochastic Tail
+---------------
+
+.. autoclass:: rocketpy.stochastic.StochasticTail
+   :members:
\ No newline at end of file
diff --git a/docs/reference/classes/monte_carlo/stochastic_models/stochastic_trapezoidal_fins.rst b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_trapezoidal_fins.rst
new file mode 100644
index 000000000..d172a441a
--- /dev/null
+++ b/docs/reference/classes/monte_carlo/stochastic_models/stochastic_trapezoidal_fins.rst
@@ -0,0 +1,5 @@
+Stochastic Trapezoidal Fins
+---------------------------
+
+.. autoclass:: rocketpy.stochastic.StochasticTrapezoidalFins
+    :members:
\ No newline at end of file
diff --git a/docs/reference/index.rst b/docs/reference/index.rst
index 9b7295281..08f99447c 100644
--- a/docs/reference/index.rst
+++ b/docs/reference/index.rst
@@ -17,6 +17,7 @@ This reference manual details functions, modules, methods and attributes include
    classes/Flight
    Utilities <classes/utils/index>
    classes/EnvironmentAnalysis
+   Monte Carlo Analysis <classes/monte_carlo/index> 
 
 .. toctree::
    :maxdepth: 2
diff --git a/docs/requirements.in b/docs/requirements.in
new file mode 100644
index 000000000..b716d0c54
--- /dev/null
+++ b/docs/requirements.in
@@ -0,0 +1,7 @@
+nbsphinx==0.9.4
+pydata-sphinx-theme==0.15.2
+jupyter-sphinx==0.5.3
+sphinx_design==0.5.0
+ipykernel==6.29.4
+pandas==2.2.2
+lxml_html_clean==0.1.1
\ No newline at end of file
diff --git a/docs/requirements.txt b/docs/requirements.txt
index 7d45029bb..bd8cb90ef 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,7 +1,247 @@
-nbsphinx>=0.8.0
-pydata-sphinx-theme==0.13.3
-m2r2>=0.2.1
-jupyter-sphinx==0.4.0
-sphinx_design==0.5.0
-ipykernel>=6.25.0
-pandas>=1.4.4
\ No newline at end of file
+#
+# This file is autogenerated by pip-compile with Python 3.12
+# by the following command:
+#
+#    pip-compile docs/requirements.in
+#
+accessible-pygments==0.0.5
+    # via pydata-sphinx-theme
+alabaster==0.7.16
+    # via sphinx
+asttokens==2.4.1
+    # via stack-data
+attrs==23.2.0
+    # via
+    #   jsonschema
+    #   referencing
+babel==2.15.0
+    # via
+    #   pydata-sphinx-theme
+    #   sphinx
+beautifulsoup4==4.12.3
+    # via
+    #   nbconvert
+    #   pydata-sphinx-theme
+bleach==6.1.0
+    # via nbconvert
+certifi==2024.2.2
+    # via requests
+charset-normalizer==3.3.2
+    # via requests
+comm==0.2.2
+    # via
+    #   ipykernel
+    #   ipywidgets
+debugpy==1.8.1
+    # via ipykernel
+decorator==5.1.1
+    # via ipython
+defusedxml==0.7.1
+    # via nbconvert
+docutils==0.20.1
+    # via
+    #   nbsphinx
+    #   pydata-sphinx-theme
+    #   sphinx
+entrypoints==0.4
+    # via nbconvert
+executing==2.0.1
+    # via stack-data
+fastjsonschema==2.19.1
+    # via nbformat
+idna==3.7
+    # via requests
+imagesize==1.4.1
+    # via sphinx
+ipykernel==6.29.4
+    # via
+    #   -r docs/requirements.in
+    #   jupyter-sphinx
+ipython==8.24.0
+    # via
+    #   ipykernel
+    #   ipywidgets
+    #   jupyter-sphinx
+ipywidgets==8.1.2
+    # via jupyter-sphinx
+jedi==0.19.1
+    # via ipython
+jinja2==3.1.4
+    # via
+    #   nbconvert
+    #   nbsphinx
+    #   sphinx
+jsonschema==4.22.0
+    # via nbformat
+jsonschema-specifications==2023.12.1
+    # via jsonschema
+jupyter-client==8.6.2
+    # via
+    #   ipykernel
+    #   nbclient
+jupyter-core==5.7.2
+    # via
+    #   ipykernel
+    #   jupyter-client
+    #   nbclient
+    #   nbconvert
+    #   nbformat
+jupyter-sphinx==0.5.3
+    # via -r docs/requirements.in
+jupyterlab-pygments==0.3.0
+    # via nbconvert
+jupyterlab-widgets==3.0.10
+    # via ipywidgets
+lxml==5.2.2
+    # via
+    #   lxml-html-clean
+    #   nbconvert
+lxml-html-clean==0.1.1
+    # via -r docs/requirements.in
+markupsafe==2.1.5
+    # via
+    #   jinja2
+    #   nbconvert
+matplotlib-inline==0.1.7
+    # via
+    #   ipykernel
+    #   ipython
+mistune==0.8.4
+    # via nbconvert
+nbclient==0.10.0
+    # via nbconvert
+nbconvert==6.5.4
+    # via
+    #   jupyter-sphinx
+    #   nbsphinx
+nbformat==5.10.4
+    # via
+    #   jupyter-sphinx
+    #   nbclient
+    #   nbconvert
+    #   nbsphinx
+nbsphinx==0.9.4
+    # via -r docs/requirements.in
+nest-asyncio==1.6.0
+    # via ipykernel
+numpy==1.26.4
+    # via pandas
+packaging==24.0
+    # via
+    #   ipykernel
+    #   nbconvert
+    #   pydata-sphinx-theme
+    #   sphinx
+pandas==2.2.2
+    # via -r docs/requirements.in
+pandocfilters==1.5.1
+    # via nbconvert
+parso==0.8.4
+    # via jedi
+pexpect==4.9.0
+    # via ipython
+platformdirs==4.2.2
+    # via jupyter-core
+prompt-toolkit==3.0.43
+    # via ipython
+psutil==5.9.8
+    # via ipykernel
+ptyprocess==0.7.0
+    # via pexpect
+pure-eval==0.2.2
+    # via stack-data
+pydata-sphinx-theme==0.15.2
+    # via -r docs/requirements.in
+pygments==2.18.0
+    # via
+    #   accessible-pygments
+    #   ipython
+    #   nbconvert
+    #   pydata-sphinx-theme
+    #   sphinx
+python-dateutil==2.9.0.post0
+    # via
+    #   jupyter-client
+    #   pandas
+pytz==2024.1
+    # via pandas
+pyzmq==26.0.3
+    # via
+    #   ipykernel
+    #   jupyter-client
+referencing==0.35.1
+    # via
+    #   jsonschema
+    #   jsonschema-specifications
+requests==2.32.2
+    # via sphinx
+rpds-py==0.18.1
+    # via
+    #   jsonschema
+    #   referencing
+six==1.16.0
+    # via
+    #   asttokens
+    #   bleach
+    #   python-dateutil
+snowballstemmer==2.2.0
+    # via sphinx
+soupsieve==2.5
+    # via beautifulsoup4
+sphinx==7.3.7
+    # via
+    #   jupyter-sphinx
+    #   nbsphinx
+    #   pydata-sphinx-theme
+    #   sphinx-design
+sphinx-design==0.5.0
+    # via -r docs/requirements.in
+sphinxcontrib-applehelp==1.0.8
+    # via sphinx
+sphinxcontrib-devhelp==1.0.6
+    # via sphinx
+sphinxcontrib-htmlhelp==2.0.5
+    # via sphinx
+sphinxcontrib-jsmath==1.0.1
+    # via sphinx
+sphinxcontrib-qthelp==1.0.7
+    # via sphinx
+sphinxcontrib-serializinghtml==1.1.10
+    # via sphinx
+stack-data==0.6.3
+    # via ipython
+tinycss2==1.3.0
+    # via nbconvert
+tornado==6.4
+    # via
+    #   ipykernel
+    #   jupyter-client
+traitlets==5.14.3
+    # via
+    #   comm
+    #   ipykernel
+    #   ipython
+    #   ipywidgets
+    #   jupyter-client
+    #   jupyter-core
+    #   matplotlib-inline
+    #   nbclient
+    #   nbconvert
+    #   nbformat
+    #   nbsphinx
+typing-extensions==4.12.0
+    # via
+    #   ipython
+    #   pydata-sphinx-theme
+tzdata==2024.1
+    # via pandas
+urllib3==2.2.1
+    # via requests
+wcwidth==0.2.13
+    # via prompt-toolkit
+webencodings==0.5.1
+    # via
+    #   bleach
+    #   tinycss2
+widgetsnbextension==4.0.10
+    # via ipywidgets
diff --git a/docs/static/landing_images/api.svg b/docs/static/landing_images/api.svg
new file mode 100644
index 000000000..e637525cc
--- /dev/null
+++ b/docs/static/landing_images/api.svg
@@ -0,0 +1,31 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="100" height="100" viewBox="0 0 1170 1063">
+  <metadata><?xpacket begin="" id="W5M0MpCehiHzreSzNTczkc9d"?>
+<x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Adobe XMP Core 5.6-c138 79.159824, 2016/09/14-01:09:01        ">
+   <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
+      <rdf:Description rdf:about=""/>
+   </rdf:RDF>
+</x:xmpmeta>
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
+                                                                                                    
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new file mode 100644
index 000000000..d61b0937d
--- /dev/null
+++ b/docs/static/landing_images/user_guide.svg
@@ -0,0 +1 @@
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diff --git a/docs/static/notebooks.css b/docs/static/notebooks.css
deleted file mode 100644
index 2a7f23067..000000000
--- a/docs/static/notebooks.css
+++ /dev/null
@@ -1,5 +0,0 @@
-.nbinput .prompt,
-.nboutput.container .output_area.stderr,
-.nboutput .prompt {
-    display: none;
-}
diff --git a/docs/static/rocketpy.css b/docs/static/rocketpy.css
new file mode 100644
index 000000000..f2a0fc9cc
--- /dev/null
+++ b/docs/static/rocketpy.css
@@ -0,0 +1,80 @@
+.nbinput .prompt,
+.nboutput.container .output_area.stderr,
+.nboutput .prompt {
+    display: none;
+}
+
+/* Main page overview cards */
+
+.sd-card {
+    background: #fff;
+    border-radius: 0;
+    padding: 30px 10px 20px 10px;
+    margin: 10px 0px;
+}
+  
+.sd-card .sd-card-header {
+    text-align: center;
+}
+
+.sd-card .sd-card-header .sd-card-text {
+    margin: 0px;
+}
+
+.sd-card .sd-card-img-top {
+    height: 52px;
+    width: 52px;
+    margin-left: auto;
+    margin-right: auto;
+}
+
+.sd-card .sd-card-header {
+    border: none;
+    background-color: white;
+    color: #150458 !important;
+    font-size: var(--pst-font-size-h5);
+    font-weight: bold;
+    padding: 2.5rem 0rem 0.5rem 0rem;
+}
+
+.sd-card .sd-card-footer {
+    border: none;
+    background-color: white;
+}
+
+.sd-card .sd-card-footer .sd-card-text {
+    max-width: 220px;
+    margin-left: auto;
+    margin-right: auto;
+}
+
+/* Dark theme tweaking */
+html[data-theme=dark] .sd-card img[src*='.svg'] {
+    filter: invert(0.82) brightness(0.8) contrast(1.2);
+}
+
+/* Main index page overview cards */
+html[data-theme=dark] .sd-card {
+    background-color:var(--pst-color-background);
+}
+
+html[data-theme=dark] .sd-shadow-sm {
+    box-shadow: 0 .1rem 1rem rgba(250, 250, 250, .6) !important
+}
+
+html[data-theme=dark] .sd-card .sd-card-header {
+    background-color:var(--pst-color-background);
+    color: #150458 !important;
+}
+
+html[data-theme=dark] .sd-card .sd-card-footer {
+    background-color:var(--pst-color-background);
+}
+
+html[data-theme=dark] h1 {
+    color: var(--pst-color-primary);
+}
+
+html[data-theme=dark] h3 {
+    color: #0a6774;
+}
\ No newline at end of file
diff --git a/docs/user/first_simulation.rst b/docs/user/first_simulation.rst
index 6fab61238..93f328922 100644
--- a/docs/user/first_simulation.rst
+++ b/docs/user/first_simulation.rst
@@ -663,7 +663,7 @@ analysis. Here we will show some examples, but much more can be done!
 .. seealso::
     *RocketPy* can be used to perform a Monte Carlo Dispersion Analysis.
     See 
-    `Monte Carlo Simulations <https://colab.research.google.com/github/RocketPy-Team/rocketpy/blob/master/docs/notebooks/dispersion_analysis/dispersion_analysis.html>`_ 
+    `Monte Carlo Simulations <https://colab.research.google.com/github/RocketPy-Team/rocketpy/blob/master/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis.html>`_ 
     for more information.
 
 Apogee as a Function of Mass
diff --git a/docs/user/function.rst b/docs/user/function.rst
index b95496991..bd8e82d3c 100644
--- a/docs/user/function.rst
+++ b/docs/user/function.rst
@@ -346,6 +346,7 @@ d. Differentiation and Integration
 One of the most useful ``Function`` features for data analysis is easily differentiating and integrating the data source. These methods are divided as follow:
 
 - :meth:`rocketpy.Function.differentiate`: differentiate the ``Function`` at a given point, returning the derivative value as the result;
+- :meth:`rocketpy.Function.differentiate_complex_step`: differentiate the ``Function`` at a given point using the complex step method, returning the derivative value as the result;
 - :meth:`rocketpy.Function.integral`: performs a definite integral over specified limits, returns the integral value (area under ``Function``);
 - :meth:`rocketpy.Function.derivative_function`: computes the derivative of the given `Function`, returning another `Function` that is the derivative of the original at each point;
 - :meth:`rocketpy.Function.integral_function`: calculates the definite integral of the function from a given point up to a variable, returns a ``Function``.
@@ -363,6 +364,19 @@ Let's make a familiar example of differentiation: the derivative of the function
     # Differentiate it at x = 3
     print(f.differentiate(3))
 
+RocketPy also supports the complex step method for differentiation, which is a very accurate method for numerical differentiation. Let's compare the results of the complex step method with the standard method:
+
+.. jupyter-execute::
+
+    # Define the function x^2
+    f = Function(lambda x: x**2)
+
+    # Differentiate it at x = 3 using the complex step method
+    print(f.differentiate_complex_step(3))
+
+The complex step method can be as twice as faster as the standard method,  but
+it requires the function to be differentiable in the complex plane.
+
 Also one may compute the derivative function:
 
 .. jupyter-execute::
diff --git a/docs/user/index.rst b/docs/user/index.rst
index 6896f9d4e..7d8c12241 100644
--- a/docs/user/index.rst
+++ b/docs/user/index.rst
@@ -28,10 +28,12 @@ RocketPy's User Guide
 
 .. toctree::
    :maxdepth: 2
-   :caption: Dispersion Analysis
+   :caption: Monte Carlo Simulations
 
-   ../notebooks/dispersion_analysis/dispersion_analysis.ipynb  
-   ../notebooks/dispersion_analysis/parachute_drop_from_helicopter.ipynb
+   Stochastic Classes <stochastic.rst>
+   ../notebooks/monte_carlo_analysis/monte_carlo_class_usage.ipynb
+   ../notebooks/monte_carlo_analysis/monte_carlo_analysis.ipynb
+   ../notebooks/monte_carlo_analysis/parachute_drop_from_helicopter.ipynb
 
 .. toctree::
    :maxdepth: 2
diff --git a/docs/user/installation.rst b/docs/user/installation.rst
index 328a251a4..f73310dfe 100644
--- a/docs/user/installation.rst
+++ b/docs/user/installation.rst
@@ -19,7 +19,7 @@ If you want to choose a specific version to guarantee compatibility, you may ins
 
 .. code-block:: shell
 
-    pip install rocketpy==1.2.2
+    pip install rocketpy==1.3.0.post1
 
 
 Optional Installation Method: ``conda``
@@ -49,7 +49,7 @@ Once you are done downloading/cloning RocketPy's repository, you can install it
 
 .. code-block:: shell
 
-    python setup.py install 
+    python -m pip install .
 
 
 Development version
@@ -76,7 +76,7 @@ Alternatively, you can clone RocketPy's repository, check out the branch named `
 
 .. code-block:: shell
 
-    python setup.py install 
+    python -m pip install -e .
 
 
 Requirements
diff --git a/docs/user/rocket.rst b/docs/user/rocket.rst
index 28e091e8d..fa09f058e 100644
--- a/docs/user/rocket.rst
+++ b/docs/user/rocket.rst
@@ -12,6 +12,7 @@ Defining a Rocket in RocketPy is simple and requires a few steps:
 4. Add, if desired, parachutes;
 5. Set, if desired, rail guides;
 6. See results.
+7. Inertia Tensors.
 
 Lets go through each of these steps in detail.
 
@@ -428,3 +429,54 @@ The lets check all the information available about the rocket:
 .. jupyter-execute::
 
     calisto.all_info()
+
+7. Inertia Tensors
+------------------
+
+The inertia tensor of the rocket at a given time can be obtained using the
+``get_inertia_tensor_at_time`` method. This method evaluates each component of
+the inertia tensor at the specified time and returns a
+:class:`rocketpy.mathutils.Matrix` object.
+
+The inertia tensor is a matrix that looks like this:
+
+.. math::
+    :label: inertia_tensor
+
+    \mathbf{I} = \begin{bmatrix}
+    I_{11} & I_{12} & I_{13} \\
+    I_{21} & I_{22} & I_{23} \\
+    I_{31} & I_{32} & I_{33}
+    \end{bmatrix}
+
+For example, to get the inertia tensor of the rocket at time 0.5 seconds, you
+can use the following code:
+
+.. jupyter-execute::
+
+    calisto.get_inertia_tensor_at_time(0.5)
+
+Derivative of the Inertia Tensor
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+You can also get the derivative of the inertia tensor at a given time using the
+``get_inertia_tensor_derivative_at_time`` method. Here's an example:
+
+.. jupyter-execute::
+
+    calisto.get_inertia_tensor_derivative_at_time(0.5)
+
+Implications from these results
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The inertia tensor reveals important information about the rocket's symmetry 
+and ease of rotation:
+
+1. **Axis Symmetry**: If I\ :sub:`11` and I\ :sub:`22` are equal, the rocket is symmetric around the axes perpendicular to the rocket's center axis. In our defined rocket, I\ :sub:`11` and I\ :sub:`22` are indeed equal, indicating that our rocket is axisymmetric.
+
+2. **Zero Products of Inertia**: The off-diagonal elements of the inertia tensor are zero, which means the products of inertia are zero. This indicates that the rocket is symmetric around its center axis.
+
+3. **Ease of Rotation**: The I\ :sub:`33` value is significantly lower than the other two. This suggests that the rocket is easier to rotate around its center axis than around the axes perpendicular to the rocket. This is an important factor when considering the rocket's stability and control.
+
+However, these conclusions are based on the assumption that the inertia tensor is calculated with respect to the rocket's center of mass and aligned with the principal axes of the rocket. If the inertia tensor is calculated with respect to a different point or not aligned with the principal axes, the conclusions may not hold.
+
diff --git a/docs/user/stochastic.rst b/docs/user/stochastic.rst
new file mode 100644
index 000000000..1d325b21e
--- /dev/null
+++ b/docs/user/stochastic.rst
@@ -0,0 +1,249 @@
+.. _stochastic_usage:
+
+Working with Stochastic objects
+===============================
+
+For each RocketPy object (e.g. Environment, SolidMotor, Rocket, etc.), we can
+create a ``Stochastic`` counterpart that extends the initial model, allowing us
+to define the uncertainties of each input parameter.
+
+The idea of the ``Stochastic`` classes is to take the deterministic classes and
+assign uncertainties to their input parameters. This will reflect the inherent
+uncertainties in the real-world data and provide a more realistic simulation.
+
+.. seealso::
+    For ``Stochastic`` class API details, see :ref:`stochastic_reference`.
+
+.. note::
+    In this tutorial, classes without the ``Stochastic`` prefix are considered \
+    deterministic. For instance, ``SolidMotor`` is a deterministic class, while \
+    its stochastic counterpart is named ``StochasticSolidMotor``.
+
+Initialization Parameters
+-------------------------
+
+In terms of initialization parameters, the ``Stochastic`` classes are very
+similar to the deterministic classes.
+We will separate the parameters into three categories: the "deterministic object",
+the "optional parameters", and the "additional parameters".
+Let's take a look at their nuances:
+
+.. note::
+    In Python, we use the terms "argument", "parameter", and "initialization parameter" 
+    interchangeably to refer to the values passed to a function or class during initialization.
+
+    For the sake of clarity, we will use the term "argument" from now on.
+
+Arguments
+^^^^^^^^^
+
+1. **Deterministic Object**: \
+    All ``Stochastic`` classes **must** receive a \
+    deterministic object as an argument. This is the only mandatory argument.
+
+2. **Optional Arguments**: \
+    The remaining parameters are the same as in the \
+    deterministic classes, and they are optional. They only need to be passed \
+    if you want to define the uncertainty for that argument. If you don't pass an \
+    argument, it will not be varied during the simulation, and the nominal value \
+    will be taken from the deterministic object.
+
+3. **Additional Arguments**: \
+    Some ``Stochastic`` classes may present additional \
+    arguments that are not present in the deterministic classes. These are used \
+    for specific purposes, such as a multiplication factor for the drag curves.
+
+
+Specifying Uncertainties
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+Furthermore, the optional arguments - which define the uncertainties - can be
+passed in a few different ways:
+
+1. **As a single value**: \
+    This will be the standard deviation for that parameter. \
+    The default distribution used will be a normal distribution, and the nominal \
+    value will be the value of that same argument from the deterministic object.
+
+2. **As a tuple of two numbers**: \
+    The first number will be the nominal value of \
+    the distribution, and the second number will be the standard deviation. The \
+    default distribution used will be a normal distribution.
+
+3. **As a tuple of two numbers and a string**: \
+    The first number will be the \
+    nominal value of the distribution, the second number will be the standard \
+    deviation, and the string will be the distribution type. The distribution \
+    type can be one of the following: *"normal"*, *"binomial"*, *"chisquare"*, \
+    *"exponential"*, *"gamma"*, *"gumbel"*, *"laplace"*, *"logistic"*, \
+    *"poisson"*, *"uniform"*, and *"wald"*.
+
+3. **As a tuple of a number and a string**: \
+    The number will be the standard \
+    deviation, and the string will be the distribution type. The nominal value \
+    will be taken from the standard object.
+
+4. **As a list of values**: \
+    The values will be randomly chosen from this list and \
+    used as the parameter value during the simulation. You cannot assign standard \
+    deviations when using lists, nor can you assign different distribution types. 
+
+.. note::
+    In statistics, the terms "Normal" and "Gaussian" refer to the same type of \
+    distribution. This distribution is commonly used and is the default for the \
+    ``Stochastic`` classes in RocketPy.
+
+    In this context, a "distribution" refers to a function that describes the \
+    probability of a parameter assuming a certain value. The type of distribution \
+    determines the shape of this function. We use the term "distribution" to \
+    simplify the explanation of the stochastic classes.
+
+Examples
+--------
+
+Here is a better explanation of the arguments with examples:
+
+Example 1: Stochastic Solid Motor
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Consider the ``StochasticSolidMotor`` object:
+
+.. jupyter-execute::
+
+    from rocketpy import SolidMotor, StochasticSolidMotor
+
+    motor = SolidMotor(
+        thrust_source="../data/motors/Cesaroni_M1670.eng",
+        dry_mass=1.815,
+        dry_inertia=(0.125, 0.125, 0.002),
+        nozzle_radius=33 / 1000,
+        grain_number=5,
+        grain_density=1815,
+        grain_outer_radius=33 / 1000,
+        grain_initial_inner_radius=15 / 1000,
+        grain_initial_height=120 / 1000,
+        grain_separation=5 / 1000,
+        grains_center_of_mass_position=0.397,
+        center_of_dry_mass_position=0.317,
+        nozzle_position=0,
+        burn_time=3.9,
+        throat_radius=11 / 1000,
+        coordinate_system_orientation="nozzle_to_combustion_chamber",
+    )
+
+    stochastic_motor = StochasticSolidMotor(
+        solid_motor=motor,
+        burn_start_time=(0, 0.1, "binomial"),
+        grains_center_of_mass_position=0.001,
+        grain_density=10,
+        grain_separation=1 / 1000,
+        grain_initial_height=1 / 1000,
+        grain_initial_inner_radius=0.375 / 1000,
+        grain_outer_radius=0.375 / 1000,
+        total_impulse=(6500, 100),
+        throat_radius=0.5 / 1000,
+        nozzle_radius=0.5 / 1000,
+        nozzle_position=0.001,
+    )
+
+    stochastic_motor.visualize_attributes()
+
+Interpreting the Output
+"""""""""""""""""""""""
+
+To illustrate the example above, you can notice that: 
+
+- The ``burn_start_time`` argument was specified as a tuple of 3 items (0, 0.1, "binomial"), meaning the nominal value is 0, the standard deviation is 0.1, and the distribution type is binomial. You can check that it was correctly set being reading the ``burn_start_time: 0.00000 ± 0.10000 (numpy.random.binomial)`` line in the output. 
+- ``total_impulse`` was given as a tuple of 2 numbers (6500, 100), indicating a nominal value of 6500 and a standard deviation of 1000, with the default distribution being normal, which is the default distribution type.
+
+.. note::
+    Always remember to run ``stochastic_object.visualize_attributes()`` to check \
+    if the uncertainties were correctly set.
+
+Sampling a Stochastic Object
+""""""""""""""""""""""""""""
+
+Continuing with the example, you can use the ``stochastic_motor`` object to generate 
+a random `SolidMotor` object considering the uncertainties defined in the initialization.
+
+.. jupyter-execute::
+
+    sampled_motor = stochastic_motor.create_object()
+    print(sampled_motor)
+
+This will create a new ``SolidMotor`` object in memory and assign it to the
+variable ``sampled_motor``. This behaves exactly like a ``SolidMotor`` object, but
+considering that each parameter was randomly sampled from the defined distributions. 
+We can compare the nominal values of the ``motor`` object with the sampled values
+of the ``sampled_motor`` object:
+
+.. jupyter-execute::
+
+    print("Deterministic Motor with nominal values:\n")
+    motor.prints.all()
+    print("\n\nSampled Motor considering uncertainties:\n")
+    sampled_motor.prints.all()
+
+As you can notice, the values from the ``sampled_motor`` object are slightly different
+from the nominal values of the ``motor`` object.
+
+.. important::
+    If you run the ``create_object()`` method multiple times, you will get different
+    results each time, as the values are always randomly sampled from the defined
+    distributions.
+
+
+Determining Uncertainties
+-------------------------
+
+Determining the uncertainties for each parameter is crucial for accurate simulations.
+Here are some practical methods:
+
+1. **Empirical Measurements**: \
+    For geometric properties and other parameters that \
+    can be measured, you can take multiple measurements and calculate the standard \
+    deviation. This method provides a direct and reliable estimate of uncertainty. \
+    Some examples include: rocket mass, dimensions or positions and material density.
+
+2. **Historical Data**: \
+    Use historical data from previous experiments or similar \
+    projects to base your standard deviations. For example, if you are designing a \
+    rocket with similar characteristics to a previous project, you can use the \
+    uncertainties from that project as a starting point.
+
+3. **Literature Review**: \
+    Review literature and technical documents to find \
+    estimation values for uncertainties. For example, for aerodynamic coefficients, \
+    you can find typical values in textbooks or research papers, these usually \
+    come from wind tunnel tests. A good resource to base your uncertainties is the \
+    `RocketPy article <https://doi.org/10.1061/(ASCE)AS.1943-5525.0001331>`_.  
+
+5. **Rule of Thumb**: \
+    In the absence of specific data, you can use general rules \
+    of thumb. For example, assigning a standard deviation of 10% of the nominal \
+    value is a common practice.
+
+As your rocket project evolves, you will likely gather more data and refine your
+models. Consequently, the uncertainties should decrease, resulting in stochastic
+models with less variance. This iterative process will enhance the accuracy and
+reliability of your simulations over time.
+
+.. Determining Which Arguments to Vary
+.. -----------------------------------
+
+.. Choosing which arguments to vary is crucial for effective Monte Carlo simulations.
+.. RocketPy offers a ``Sensitivity Analysis toolkit``, which can help you to identify
+.. which parameters most significantly impact your simulation results.
+
+
+Conclusion
+----------
+
+The ``Stochastic`` classes in RocketPy provide a powerful way to introduce and
+manage uncertainties in your simulations. By defining distributions for each
+input parameter, you can perform more realistic and robust Monte Carlo simulations,
+better reflecting the inherent uncertainties in rocketry. 
+
+.. note:: 
+    See the ``MonteCarlo`` class documentation for more information on how to run \
+    Monte Carlo simulations with stochastic objects.
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 000000000..623be535d
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,77 @@
+[project]
+name = "rocketpy"
+version = "1.3.0.post1"
+description="Advanced 6-DOF trajectory simulation for High-Power Rocketry."
+dynamic = ["dependencies"]
+readme = "README.md"
+requires-python = ">=3.8"
+authors = [
+  {name = "Giovani Hidalgo Ceotto", email = "ghceotto@gmail.com"}
+]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent",
+]
+
+[project.urls]
+homepage = "https://rocketpy.org/"
+documentation = "https://docs.rocketpy.org/"
+repository = "https://github.com/RocketPy-Team/RocketPy"
+
+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+packages = { find = { where = ["."], include = ["rocketpy*"] } }
+
+[tool.setuptools.dynamic]
+dependencies = { file = ["requirements.txt"] }
+
+[project.optional-dependencies]
+tests = [ 
+    "pytest", 
+    "pytest-coverage",
+    "black[jupyter]",
+    "flake8-black",
+    "flake8-pyproject",
+    "pandas",
+    "numericalunits==1.25",
+    "pylint",
+    "isort"
+]
+
+env-analysis = [ 
+    "windrose>=1.6.8", 
+    "timezonefinder", 
+    "jsonpickle", 
+    "ipython", 
+    "ipywidgets>=7.6.3" 
+]
+
+monte-carlo = [
+    "imageio",
+]
+
+all = ["rocketpy[env-analysis]", "rocketpy[monte-carlo]"]
+
+[tool.black]
+line-length = 88 
+include = '\.py$|\.ipynb$'
+skip-string-normalization = true
+
+[tool.coverage.report]
+# Regexes for lines to exclude from consideration
+exclude_also = [
+    #Don't complain about exceptions or warnings not being covered by tests
+    "warnings.warn*"
+]
+
+[tool.flake8]
+max-line-length = 88
+max-module-lines = 3000
+ignore = ['E203', 'W503']
+exclude = [
+    '.git,__pycache__',
+]
diff --git a/requirements-optional.txt b/requirements-optional.txt
index 699bbde14..0cf42683d 100644
--- a/requirements-optional.txt
+++ b/requirements-optional.txt
@@ -2,4 +2,5 @@ windrose>=1.6.8
 ipython
 ipywidgets>=7.6.3
 jsonpickle
-timezonefinder
\ No newline at end of file
+timezonefinder
+imageio
\ No newline at end of file
diff --git a/requirements-tests.txt b/requirements-tests.txt
index 42f5a8292..4fc2bc811 100644
--- a/requirements-tests.txt
+++ b/requirements-tests.txt
@@ -2,7 +2,8 @@ pytest
 pytest-coverage
 black[jupyter]
 flake8-black
+flake8-pyproject
 pandas
 numericalunits==1.25
 pylint
-isort
\ No newline at end of file
+isort
diff --git a/rocketpy/__init__.py b/rocketpy/__init__.py
index 43a6ebc67..d7d600802 100644
--- a/rocketpy/__init__.py
+++ b/rocketpy/__init__.py
@@ -38,4 +38,15 @@
     TrapezoidalFins,
 )
 from .sensors import Accelerometer, Barometer, Gyroscope
-from .simulation import Flight
+from .simulation import Flight, MonteCarlo
+from .stochastic import (
+    StochasticEllipticalFins,
+    StochasticEnvironment,
+    StochasticFlight,
+    StochasticNoseCone,
+    StochasticParachute,
+    StochasticRocket,
+    StochasticSolidMotor,
+    StochasticTail,
+    StochasticTrapezoidalFins,
+)
diff --git a/rocketpy/_encoders.py b/rocketpy/_encoders.py
new file mode 100644
index 000000000..3fb5202a3
--- /dev/null
+++ b/rocketpy/_encoders.py
@@ -0,0 +1,43 @@
+"""Defines a custom JSON encoder for RocketPy objects."""
+
+import json
+import types
+
+import numpy as np
+
+from rocketpy.mathutils.function import Function
+
+
+class RocketPyEncoder(json.JSONEncoder):
+    """NOTE: This is still under construction, please don't use it yet."""
+
+    def default(self, o):
+        if isinstance(
+            o,
+            (
+                np.int_,
+                np.intc,
+                np.intp,
+                np.int8,
+                np.int16,
+                np.int32,
+                np.int64,
+                np.uint8,
+                np.uint16,
+                np.uint32,
+                np.uint64,
+            ),
+        ):
+            return int(o)
+        elif isinstance(o, (np.float_, np.float16, np.float32, np.float64)):
+            return float(o)
+        elif isinstance(o, np.ndarray):
+            return o.tolist()
+        elif hasattr(o, "to_dict"):
+            return o.to_dict()
+        # elif isinstance(o, Function):
+        #     return o.__dict__()
+        elif isinstance(o, (Function, types.FunctionType)):
+            return repr(o)
+        else:
+            return json.JSONEncoder.default(self, o)
diff --git a/rocketpy/environment/environment.py b/rocketpy/environment/environment.py
index 5a845a173..b01a4ecbc 100644
--- a/rocketpy/environment/environment.py
+++ b/rocketpy/environment/environment.py
@@ -269,9 +269,9 @@ def __init__(
         self,
         gravity=None,
         date=None,
-        latitude=0,
-        longitude=0,
-        elevation=0,
+        latitude=0.0,
+        longitude=0.0,
+        elevation=0.0,
         datum="SIRGAS2000",
         timezone="UTC",
         max_expected_height=80000.0,
@@ -1551,24 +1551,26 @@ def process_custom_atmosphere(
         # Check maximum height of custom wind input
         if not callable(self.wind_velocity_x.source):
             max_expected_height = max(self.wind_velocity_x[-1, 0], max_expected_height)
-        if not callable(self.wind_velocity_y.source):
-            max_expected_height = max(self.wind_velocity_y[-1, 0], max_expected_height)
 
-        # Compute wind profile direction and heading
-        wind_heading = (
-            lambda h: np.arctan2(self.wind_velocity_x(h), self.wind_velocity_y(h))
-            * (180 / np.pi)
-            % 360
-        )
+        def wind_heading_func(h):
+            return (
+                np.arctan2(
+                    self.wind_velocity_x.get_value_opt(h),
+                    self.wind_velocity_y.get_value_opt(h),
+                )
+                * (180 / np.pi)
+                % 360
+            )
+
         self.wind_heading = Function(
-            wind_heading,
+            wind_heading_func,
             inputs="Height Above Sea Level (m)",
             outputs="Wind Heading (Deg True)",
             interpolation="linear",
         )
 
         def wind_direction(h):
-            return (wind_heading(h) - 180) % 360
+            return (wind_heading_func(h) - 180) % 360
 
         self.wind_direction = Function(
             wind_direction,
@@ -1578,7 +1580,10 @@ def wind_direction(h):
         )
 
         def wind_speed(h):
-            return np.sqrt(self.wind_velocity_x(h) ** 2 + self.wind_velocity_y(h) ** 2)
+            return np.sqrt(
+                self.wind_velocity_x.get_value_opt(h) ** 2
+                + self.wind_velocity_y.get_value_opt(h) ** 2
+            )
 
         self.wind_speed = Function(
             wind_speed,
@@ -3077,6 +3082,24 @@ def calculate_density_profile(self):
         Returns
         -------
         None
+
+        Examples
+        --------
+        Creating an Environment object and calculating the density
+        at Sea Level:
+
+        >>> env = Environment()
+        >>> env.calculate_density_profile()
+        >>> env.density(0)
+        1.225000018124288
+
+        Creating an Environment object and calculating the density
+        at 1000m above Sea Level:
+
+        >>> env = Environment()
+        >>> env.calculate_density_profile()
+        >>> env.density(1000)
+        1.1116193933422585
         """
         # Retrieve pressure P, gas constant R and temperature T
         P = self.pressure
@@ -3179,22 +3202,26 @@ def add_wind_gust(self, wind_gust_x, wind_gust_y):
         # Reset wind heading and velocity magnitude
         self.wind_heading = Function(
             lambda h: (180 / np.pi)
-            * np.arctan2(self.wind_velocity_x(h), self.wind_velocity_y(h))
+            * np.arctan2(
+                self.wind_velocity_x.get_value_opt(h),
+                self.wind_velocity_y.get_value_opt(h),
+            )
             % 360,
             "Height (m)",
             "Wind Heading (degrees)",
             extrapolation="constant",
         )
         self.wind_speed = Function(
-            lambda h: (self.wind_velocity_x(h) ** 2 + self.wind_velocity_y(h) ** 2)
+            lambda h: (
+                self.wind_velocity_x.get_value_opt(h) ** 2
+                + self.wind_velocity_y.get_value_opt(h) ** 2
+            )
             ** 0.5,
             "Height (m)",
             "Wind Speed (m/s)",
             extrapolation="constant",
         )
 
-        return None
-
     def info(self):
         """Prints most important data and graphs available about the
         Environment.
diff --git a/rocketpy/mathutils/function.py b/rocketpy/mathutils/function.py
index eda903bcc..2439dafce 100644
--- a/rocketpy/mathutils/function.py
+++ b/rocketpy/mathutils/function.py
@@ -5,6 +5,7 @@
 """
 
 import warnings
+from bisect import bisect_left
 from collections.abc import Iterable
 from copy import deepcopy
 from functools import cached_property
@@ -16,6 +17,14 @@
 from scipy import integrate, linalg, optimize
 
 NUMERICAL_TYPES = (float, int, complex, np.ndarray, np.integer, np.floating)
+INTERPOLATION_TYPES = {
+    "linear": 0,
+    "polynomial": 1,
+    "akima": 2,
+    "spline": 3,
+    "shepard": 4,
+}
+EXTRAPOLATION_TYPES = {"zero": 0, "natural": 1, "constant": 2}
 
 
 class Function:
@@ -106,28 +115,20 @@ def __init__(
         (II) Fields in CSV files may be enclosed in double quotes. If fields
         are not quoted, double quotes should not appear inside them.
         """
-        if inputs is None:
-            inputs = ["Scalar"]
-        if outputs is None:
-            outputs = ["Scalar"]
-
-        inputs, outputs, interpolation, extrapolation = self._check_user_input(
-            source, inputs, outputs, interpolation, extrapolation
-        )
-
-        # initialize variables to avoid errors when being called by other methods
-        self.get_value_opt = None
-        self.__polynomial_coefficients__ = None
-        self.__akima_coefficients__ = None
-        self.__spline_coefficients__ = None
-
-        # store variables
-        self.set_inputs(inputs)
-        self.set_outputs(outputs)
+        # initialize parameters
+        self.source = source
+        self.__inputs__ = inputs
+        self.__outputs__ = outputs
         self.__interpolation__ = interpolation
         self.__extrapolation__ = extrapolation
-        self.set_source(source)
-        self.set_title(title)
+        self.title = title
+        self.__img_dim__ = 1  # always 1, here for backwards compatibility
+
+        # args must be passed from self.
+        self.set_source(self.source)
+        self.set_inputs(self.__inputs__)
+        self.set_outputs(self.__outputs__)
+        self.set_title(self.title)
 
     # Define all set methods
     def set_inputs(self, inputs):
@@ -142,8 +143,7 @@ def set_inputs(self, inputs):
         -------
         self : Function
         """
-        self.__inputs__ = [inputs] if isinstance(inputs, str) else list(inputs)
-        self.__dom_dim__ = len(self.__inputs__)
+        self.__inputs__ = self.__validate_inputs(inputs)
         return self
 
     def set_outputs(self, outputs):
@@ -158,8 +158,7 @@ def set_outputs(self, outputs):
         -------
         self : Function
         """
-        self.__outputs__ = [outputs] if isinstance(outputs, str) else list(outputs)
-        self.__img_dim__ = len(self.__outputs__)
+        self.__outputs__ = self.__validate_outputs(outputs)
         return self
 
     def set_source(self, source):
@@ -208,101 +207,45 @@ def set_source(self, source):
         self : Function
             Returns the Function instance.
         """
-        *_, interpolation, extrapolation = self._check_user_input(
-            source,
-            self.__inputs__,
-            self.__outputs__,
-            self.__interpolation__,
-            self.__extrapolation__,
-        )
-        # If the source is a Function
-        if isinstance(source, Function):
-            source = source.get_source()
-        # Import CSV if source is a string or Path and convert values to ndarray
-        if isinstance(source, (str, Path)):
-            with open(source, "r") as file:
-                try:
-                    source = np.loadtxt(file, delimiter=",", dtype=float)
-                except ValueError:
-                    # If an error occurs, headers are present
-                    source = np.loadtxt(source, delimiter=",", dtype=float, skiprows=1)
-                except Exception as e:
-                    raise ValueError(
-                        "The source file is not a valid csv or txt file."
-                    ) from e
-
-        # Convert to ndarray if source is a list
-        if isinstance(source, (list, tuple)):
-            source = np.array(source, dtype=np.float64)
-        # Convert number source into vectorized lambda function
-        if isinstance(source, (int, float)):
-            temp = 1 * source
-
-            def source_function(_):
-                return temp
-
-            source = source_function
+        source = self.__validate_source(source)
 
         # Handle callable source or number source
         if callable(source):
-            # Set source
-            self.source = source
-            # Set get_value_opt
             self.get_value_opt = source
+            self.__interpolation__ = None
+            self.__extrapolation__ = None
+
             # Set arguments name and domain dimensions
             parameters = signature(source).parameters
             self.__dom_dim__ = len(parameters)
-            if self.__inputs__ == ["Scalar"]:
+            if self.__inputs__ is None:
                 self.__inputs__ = list(parameters)
-            # Set interpolation and extrapolation
-            self.__interpolation__ = None
-            self.__extrapolation__ = None
+
         # Handle ndarray source
         else:
-            # Check to see if dimensions match incoming data set
-            new_total_dim = len(source[0, :])
-            old_total_dim = self.__dom_dim__ + self.__img_dim__
+            # Evaluate dimension
+            self.__dom_dim__ = source.shape[1] - 1
 
-            # If they don't, update default values or throw error
-            if new_total_dim != old_total_dim:
-                # Update dimensions and inputs
-                self.__dom_dim__ = new_total_dim - 1
-                self.__inputs__ = self.__dom_dim__ * self.__inputs__
-
-            # Do things if domDim is 1
+            # set x and y. If Function is 2D, also set z
             if self.__dom_dim__ == 1:
                 source = source[source[:, 0].argsort()]
-
                 self.x_array = source[:, 0]
                 self.x_initial, self.x_final = self.x_array[0], self.x_array[-1]
-
                 self.y_array = source[:, 1]
                 self.y_initial, self.y_final = self.y_array[0], self.y_array[-1]
-
-                # Finally set data source as source
-                self.source = source
-            # Do things if function is multivariate
-            else:
+                self.get_value_opt = self.__get_value_opt_1d
+            elif self.__dom_dim__ > 1:
                 self.x_array = source[:, 0]
                 self.x_initial, self.x_final = self.x_array[0], self.x_array[-1]
-
                 self.y_array = source[:, 1]
                 self.y_initial, self.y_final = self.y_array[0], self.y_array[-1]
-
                 self.z_array = source[:, 2]
                 self.z_initial, self.z_final = self.z_array[0], self.z_array[-1]
+                self.get_value_opt = self.__get_value_opt_nd
 
-                # Finally set data source as source
-                self.source = source
-            # Update extrapolation method
-            if self.__extrapolation__ is None:
-                self.set_extrapolation(extrapolation)
-            # Set default interpolation for point source if it hasn't
-            if self.__interpolation__ is None:
-                self.set_interpolation(interpolation)
-            else:
-                # Updates interpolation coefficients
-                self.set_interpolation(self.__interpolation__)
+        self.source = source
+        self.set_interpolation(self.__interpolation__)
+        self.set_extrapolation(self.__extrapolation__)
         return self
 
     @cached_property
@@ -342,21 +285,27 @@ def set_interpolation(self, method="spline"):
         -------
         self : Function
         """
-        # Set interpolation method
-        self.__interpolation__ = method
+        if not callable(self.source):
+            self.__interpolation__ = self.__validate_interpolation(method)
+            self.__update_interpolation_coefficients(self.__interpolation__)
+            self.__set_interpolation_func()
+        return self
+
+    def __update_interpolation_coefficients(self, method):
+        """Update interpolation coefficients for the given method."""
         # Spline, akima and polynomial need data processing
         # Shepard, and linear do not
-        if method == "spline":
-            self.__interpolate_spline__()
-        elif method == "polynomial":
+        if method == "polynomial":
             self.__interpolate_polynomial__()
+            self._coeffs = self.__polynomial_coefficients__
         elif method == "akima":
             self.__interpolate_akima__()
-
-        # Set get_value_opt
-        self.set_get_value_opt()
-
-        return self
+            self._coeffs = self.__akima_coefficients__
+        elif method == "spline" or method is None:
+            self.__interpolate_spline__()
+            self._coeffs = self.__spline_coefficients__
+        else:
+            self._coeffs = []
 
     def set_extrapolation(self, method="constant"):
         """Set extrapolation behavior of data set.
@@ -375,137 +324,163 @@ def set_extrapolation(self, method="constant"):
         self : Function
             The Function object.
         """
-        self.__extrapolation__ = method
+        if not callable(self.source):
+            self.__extrapolation__ = self.__validate_extrapolation(method)
+            self.__set_extrapolation_func()
         return self
 
+    def __set_interpolation_func(self):
+        """Defines interpolation function used by the Function. Each
+        interpolation method has its own function with exception of shepard,
+        which has its interpolation/extrapolation function defined in
+        ``Function.__interpolate_shepard__``. The function is stored in
+        the attribute _interpolation_func."""
+        interpolation = INTERPOLATION_TYPES[self.__interpolation__]
+        if interpolation == 0:  # linear
+
+            def linear_interpolation(x, x_min, x_max, x_data, y_data, coeffs):
+                x_interval = bisect_left(x_data, x)
+                x_left = x_data[x_interval - 1]
+                y_left = y_data[x_interval - 1]
+                dx = float(x_data[x_interval] - x_left)
+                dy = float(y_data[x_interval] - y_left)
+                return (x - x_left) * (dy / dx) + y_left
+
+            self._interpolation_func = linear_interpolation
+
+        elif interpolation == 1:  # polynomial
+
+            def polynomial_interpolation(x, x_min, x_max, x_data, y_data, coeffs):
+                return np.sum(coeffs * x ** np.arange(len(coeffs)))
+
+            self._interpolation_func = polynomial_interpolation
+
+        elif interpolation == 2:  # akima
+
+            def akima_interpolation(x, x_min, x_max, x_data, y_data, coeffs):
+                x_interval = bisect_left(x_data, x)
+                x_interval = x_interval if x_interval != 0 else 1
+                a = coeffs[4 * x_interval - 4 : 4 * x_interval]
+                return a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
+
+            self._interpolation_func = akima_interpolation
+
+        elif interpolation == 3:  # spline
+
+            def spline_interpolation(x, x_min, x_max, x_data, y_data, coeffs):
+                x_interval = bisect_left(x_data, x)
+                x_interval = max(x_interval, 1)
+                a = coeffs[:, x_interval - 1]
+                x = x - x_data[x_interval - 1]
+                return a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
+
+            self._interpolation_func = spline_interpolation
+
+        elif interpolation == 4:  # shepard does not use interpolation function
+            self._interpolation_func = None
+
+    def __set_extrapolation_func(self):
+        """Defines extrapolation function used by the Function. Each
+        extrapolation method has its own function. The function is stored in
+        the attribute _extrapolation_func."""
+        interpolation = INTERPOLATION_TYPES[self.__interpolation__]
+        extrapolation = EXTRAPOLATION_TYPES[self.__extrapolation__]
+
+        if interpolation == 4:  # shepard does not use extrapolation function
+            self._extrapolation_func = None
+
+        elif extrapolation == 0:  # zero
+
+            def zero_extrapolation(x, x_min, x_max, x_data, y_data, coeffs):
+                return 0
+
+            self._extrapolation_func = zero_extrapolation
+        elif extrapolation == 1:  # natural
+            if interpolation == 0:  # linear
+
+                def natural_extrapolation(x, x_min, x_max, x_data, y_data, coeffs):
+                    x_interval = 1 if x < x_min else -1
+                    x_left = x_data[x_interval - 1]
+                    y_left = y_data[x_interval - 1]
+                    dx = float(x_data[x_interval] - x_left)
+                    dy = float(y_data[x_interval] - y_left)
+                    return (x - x_left) * (dy / dx) + y_left
+
+            elif interpolation == 1:  # polynomial
+
+                def natural_extrapolation(x, x_min, x_max, x_data, y_data, coeffs):
+                    return np.sum(coeffs * x ** np.arange(len(coeffs)))
+
+            elif interpolation == 2:  # akima
+
+                def natural_extrapolation(x, x_min, x_max, x_data, y_data, coeffs):
+                    a = coeffs[:4] if x < x_min else coeffs[-4:]
+                    return a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
+
+            elif interpolation == 3:  # spline
+
+                def natural_extrapolation(x, x_min, x_max, x_data, y_data, coeffs):
+                    if x < x_min:
+                        a = coeffs[:, 0]
+                        x = x - x_data[0]
+                    else:
+                        a = coeffs[:, -1]
+                        x = x - x_data[-2]
+                    return a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
+
+            self._extrapolation_func = natural_extrapolation
+        elif extrapolation == 2:  # constant
+
+            def constant_extrapolation(x, x_min, x_max, x_data, y_data, coeffs):
+                return y_data[0] if x < x_min else y_data[-1]
+
+            self._extrapolation_func = constant_extrapolation
+
     def set_get_value_opt(self):
-        """Crates a method that evaluates interpolations rather quickly
-        when compared to other options available, such as just calling
-        the object instance or calling ``Function.get_value`` directly. See
-        ``Function.get_value_opt`` for documentation.
+        """Defines a method that evaluates interpolations.
 
         Returns
         -------
         self : Function
         """
+        if callable(self.source):
+            self.get_value_opt = self.source
+        elif self.__dom_dim__ == 1:
+            self.get_value_opt = self.__get_value_opt_1d
+        elif self.__dom_dim__ > 1:
+            self.get_value_opt = self.__get_value_opt_nd
+        return self
+
+    def __get_value_opt_1d(self, x):
+        """Evaluate the Function at a single point x. This method is used
+        when the Function is 1-D.
+
+        Parameters
+        ----------
+        x : scalar
+            Value where the Function is to be evaluated.
+
+        Returns
+        -------
+        y : scalar
+            Value of the Function at the specified point.
+        """
         # Retrieve general info
         x_data = self.x_array
         y_data = self.y_array
         x_min, x_max = self.x_initial, self.x_final
-        if self.__extrapolation__ == "zero":
-            extrapolation = 0  # Extrapolation is zero
-        elif self.__extrapolation__ == "natural":
-            extrapolation = 1  # Extrapolation is natural
-        elif self.__extrapolation__ == "constant":
-            extrapolation = 2  # Extrapolation is constant
+        coeffs = self._coeffs
+        if x_min <= x <= x_max:
+            y = self._interpolation_func(x, x_min, x_max, x_data, y_data, coeffs)
         else:
-            raise ValueError(f"Invalid extrapolation type {self.__extrapolation__}")
+            y = self._extrapolation_func(x, x_min, x_max, x_data, y_data, coeffs)
+        return y
 
-        # Crete method to interpolate this info for each interpolation type
-        if self.__interpolation__ == "spline":
-            coeffs = self.__spline_coefficients__
-
-            def get_value_opt(x):
-                x_interval = np.searchsorted(x_data, x)
-                # Interval found... interpolate... or extrapolate
-                if x_min <= x <= x_max:
-                    # Interpolate
-                    x_interval = x_interval if x_interval != 0 else 1
-                    a = coeffs[:, x_interval - 1]
-                    x = x - x_data[x_interval - 1]
-                    y = a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
-                else:
-                    # Extrapolate
-                    if extrapolation == 0:  # Extrapolation == zero
-                        y = 0
-                    elif extrapolation == 1:  # Extrapolation == natural
-                        a = coeffs[:, 0] if x < x_min else coeffs[:, -1]
-                        x = x - x_data[0] if x < x_min else x - x_data[-2]
-                        y = a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
-                    else:  # Extrapolation is set to constant
-                        y = y_data[0] if x < x_min else y_data[-1]
-                return y
-
-        elif self.__interpolation__ == "linear":
-
-            def get_value_opt(x):
-                x_interval = np.searchsorted(x_data, x)
-                # Interval found... interpolate... or extrapolate
-                if x_min <= x <= x_max:
-                    # Interpolate
-                    dx = float(x_data[x_interval] - x_data[x_interval - 1])
-                    dy = float(y_data[x_interval] - y_data[x_interval - 1])
-                    y = (x - x_data[x_interval - 1]) * (dy / dx) + y_data[
-                        x_interval - 1
-                    ]
-                else:
-                    # Extrapolate
-                    if extrapolation == 0:  # Extrapolation == zero
-                        y = 0
-                    elif extrapolation == 1:  # Extrapolation == natural
-                        x_interval = 1 if x < x_min else -1
-                        dx = float(x_data[x_interval] - x_data[x_interval - 1])
-                        dy = float(y_data[x_interval] - y_data[x_interval - 1])
-                        y = (x - x_data[x_interval - 1]) * (dy / dx) + y_data[
-                            x_interval - 1
-                        ]
-                    else:  # Extrapolation is set to constant
-                        y = y_data[0] if x < x_min else y_data[-1]
-                return y
-
-        elif self.__interpolation__ == "akima":
-            coeffs = np.array(self.__akima_coefficients__)
-
-            def get_value_opt(x):
-                x_interval = np.searchsorted(x_data, x)
-                # Interval found... interpolate... or extrapolate
-                if x_min <= x <= x_max:
-                    # Interpolate
-                    x_interval = x_interval if x_interval != 0 else 1
-                    a = coeffs[4 * x_interval - 4 : 4 * x_interval]
-                    y = a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
-                else:
-                    # Extrapolate
-                    if extrapolation == 0:  # Extrapolation == zero
-                        y = 0
-                    elif extrapolation == 1:  # Extrapolation == natural
-                        a = coeffs[:4] if x < x_min else coeffs[-4:]
-                        y = a[3] * x**3 + a[2] * x**2 + a[1] * x + a[0]
-                    else:  # Extrapolation is set to constant
-                        y = y_data[0] if x < x_min else y_data[-1]
-                return y
-
-        elif self.__interpolation__ == "polynomial":
-            coeffs = self.__polynomial_coefficients__
-
-            def get_value_opt(x):
-                # Interpolate... or extrapolate
-                if x_min <= x <= x_max:
-                    # Interpolate
-                    y = 0
-                    for i, coef in enumerate(coeffs):
-                        y += coef * (x**i)
-                else:
-                    # Extrapolate
-                    if extrapolation == 0:  # Extrapolation == zero
-                        y = 0
-                    elif extrapolation == 1:  # Extrapolation == natural
-                        y = 0
-                        for i, coef in enumerate(coeffs):
-                            y += coef * (x**i)
-                    else:  # Extrapolation is set to constant
-                        y = y_data[0] if x < x_min else y_data[-1]
-                return y
-
-        elif self.__interpolation__ == "shepard":
-            # change the function's name to avoid mypy's error
-            def get_value_opt_multiple(*args):
-                return self.__interpolate_shepard__(args)
-
-            get_value_opt = get_value_opt_multiple
-
-        self.get_value_opt = get_value_opt
-        return self
+    def __get_value_opt_nd(self, *args):
+        """Evaluate the Function at a single point (x, y, z). This method is
+        used when the Function is N-D."""
+        # always use shepard for N-D functions
+        return self.__interpolate_shepard__(args)
 
     def set_discrete(
         self,
@@ -885,7 +860,7 @@ def get_value(self, *args):
             # if the function is 1-D:
             if self.__dom_dim__ == 1:
                 # if the args is a simple number (int or float)
-                if isinstance(args[0], (int, float)):
+                if isinstance(args[0], (int, float, complex)):
                     return self.source(args[0])
                 # if the arguments are iterable, we map and return a list
                 if isinstance(args[0], Iterable):
@@ -894,113 +869,26 @@ def get_value(self, *args):
             # if the function is n-D:
             else:
                 # if each arg is a simple number (int or float)
-                if all(isinstance(arg, (int, float)) for arg in args):
+                if all(isinstance(arg, (int, float, complex)) for arg in args):
                     return self.source(*args)
                 # if each arg is iterable, we map and return a list
                 if all(isinstance(arg, Iterable) for arg in args):
                     return [self.source(*arg) for arg in zip(*args)]
 
-        # Returns value for shepard interpolation
-        elif self.__interpolation__ == "shepard":
-            return self.__interpolate_shepard__(args)
+        elif self.__dom_dim__ > 1:  # deals with nd functions and shepard interp
+            return self.get_value_opt(*args)
 
-        # Returns value for polynomial interpolation function type
-        elif self.__interpolation__ == "polynomial":
-            if isinstance(args[0], (int, float)):
-                args = [list(args)]
-            x = np.array(args[0])
-            x_data = self.x_array
-            y_data = self.y_array
-            x_min, x_max = self.x_initial, self.x_final
-            coeffs = self.__polynomial_coefficients__
-            matrix = np.zeros((len(args[0]), coeffs.shape[0]))
-            for i in range(coeffs.shape[0]):
-                matrix[:, i] = x**i
-            ans = matrix.dot(coeffs).tolist()
-            for i, _ in enumerate(x):
-                if not x_min <= x[i] <= x_max:
-                    if self.__extrapolation__ == "constant":
-                        ans[i] = y_data[0] if x[i] < x_min else y_data[-1]
-                    elif self.__extrapolation__ == "zero":
-                        ans[i] = 0
-            return ans if len(ans) > 1 else ans[0]
-        # Returns value for spline, akima or linear interpolation function type
-        elif self.__interpolation__ in ["spline", "akima", "linear"]:
+        # Returns value for other interpolation type
+        else:  # interpolation is "polynomial", "spline", "akima" or "linear"
             if isinstance(args[0], (int, float, complex, np.integer)):
                 args = [list(args)]
-            x = list(args[0])
-            x_data = self.x_array
-            y_data = self.y_array
-            x_intervals = np.searchsorted(x_data, x)
-            x_min, x_max = self.x_initial, self.x_final
-            if self.__interpolation__ == "spline":
-                coeffs = self.__spline_coefficients__
-                for i, _ in enumerate(x):
-                    if x[i] == x_min or x[i] == x_max:
-                        x[i] = y_data[x_intervals[i]]
-                    elif x_min < x[i] < x_max or (self.__extrapolation__ == "natural"):
-                        if not x_min < x[i] < x_max:
-                            a = coeffs[:, 0] if x[i] < x_min else coeffs[:, -1]
-                            x[i] = (
-                                x[i] - x_data[0] if x[i] < x_min else x[i] - x_data[-2]
-                            )
-                        else:
-                            a = coeffs[:, x_intervals[i] - 1]
-                            x[i] = x[i] - x_data[x_intervals[i] - 1]
-                        x[i] = a[3] * x[i] ** 3 + a[2] * x[i] ** 2 + a[1] * x[i] + a[0]
-                    else:
-                        # Extrapolate
-                        if self.__extrapolation__ == "zero":
-                            x[i] = 0
-                        else:  # Extrapolation is set to constant
-                            x[i] = y_data[0] if x[i] < x_min else y_data[-1]
-            elif self.__interpolation__ == "linear":
-                for i, _ in enumerate(x):
-                    # Interval found... interpolate... or extrapolate
-                    inter = x_intervals[i]
-                    if x_min <= x[i] <= x_max:
-                        # Interpolate
-                        dx = float(x_data[inter] - x_data[inter - 1])
-                        dy = float(y_data[inter] - y_data[inter - 1])
-                        x[i] = (x[i] - x_data[inter - 1]) * (dy / dx) + y_data[
-                            inter - 1
-                        ]
-                    else:
-                        # Extrapolate
-                        if self.__extrapolation__ == "zero":  # Extrapolation == zero
-                            x[i] = 0
-                        elif (
-                            self.__extrapolation__ == "natural"
-                        ):  # Extrapolation == natural
-                            inter = 1 if x[i] < x_min else -1
-                            dx = float(x_data[inter] - x_data[inter - 1])
-                            dy = float(y_data[inter] - y_data[inter - 1])
-                            x[i] = (x[i] - x_data[inter - 1]) * (dy / dx) + y_data[
-                                inter - 1
-                            ]
-                        else:  # Extrapolation is set to constant
-                            x[i] = y_data[0] if x[i] < x_min else y_data[-1]
-            else:
-                coeffs = self.__akima_coefficients__
-                for i, _ in enumerate(x):
-                    if x[i] == x_min or x[i] == x_max:
-                        x[i] = y_data[x_intervals[i]]
-                    elif x_min < x[i] < x_max or (self.__extrapolation__ == "natural"):
-                        if not x_min < x[i] < x_max:
-                            a = coeffs[:4] if x[i] < x_min else coeffs[-4:]
-                        else:
-                            a = coeffs[4 * x_intervals[i] - 4 : 4 * x_intervals[i]]
-                        x[i] = a[3] * x[i] ** 3 + a[2] * x[i] ** 2 + a[1] * x[i] + a[0]
-                    else:
-                        # Extrapolate
-                        if self.__extrapolation__ == "zero":
-                            x[i] = 0
-                        else:  # Extrapolation is set to constant
-                            x[i] = y_data[0] if x[i] < x_min else y_data[-1]
-            if isinstance(args[0], np.ndarray):
-                return np.array(x)
-            else:
-                return x if len(x) > 1 else x[0]
+
+        x = list(args[0])
+        x = list(map(self.get_value_opt, x))
+        if isinstance(args[0], np.ndarray):
+            return np.array(x)
+        else:
+            return x if len(x) > 1 else x[0]
 
     def __getitem__(self, args):
         """Returns item of the Function source. If the source is not an array,
@@ -1984,7 +1872,7 @@ def __add__(self, other):
                 # Create new Function object
                 return Function(source, inputs, outputs, interpolation, extrapolation)
             else:
-                return Function(lambda x: (self.get_value(x) + other(x)))
+                return Function(lambda x: (self.get_value_opt(x) + other(x)))
         # If other is Float except...
         except AttributeError:
             if isinstance(other, NUMERICAL_TYPES):
@@ -2005,10 +1893,10 @@ def __add__(self, other):
                         source, inputs, outputs, interpolation, extrapolation
                     )
                 else:
-                    return Function(lambda x: (self.get_value(x) + other))
+                    return Function(lambda x: (self.get_value_opt(x) + other))
             # Or if it is just a callable
             elif callable(other):
-                return Function(lambda x: (self.get_value(x) + other(x)))
+                return Function(lambda x: (self.get_value_opt(x) + other(x)))
 
     def __radd__(self, other):
         """Sums 'other' and a Function object and returns a new Function
@@ -2051,7 +1939,7 @@ def __sub__(self, other):
         try:
             return self + (-other)
         except TypeError:
-            return Function(lambda x: (self.get_value(x) - other(x)))
+            return Function(lambda x: (self.get_value_opt(x) - other(x)))
 
     def __rsub__(self, other):
         """Subtracts a Function object from 'other' and returns a new Function
@@ -2091,54 +1979,40 @@ def __mul__(self, other):
         result : Function
             A Function object which gives the result of self(x)*other(x).
         """
-        # If other is Function try...
-        try:
-            # Check if Function objects source is array or callable
-            # Check if Function objects have the same domain discretization
-            if (
-                isinstance(other.source, np.ndarray)
-                and isinstance(self.source, np.ndarray)
-                and self.__dom_dim__ == other.__dom_dim__
-                and np.array_equal(self.x_array, other.x_array)
-            ):
-                # Operate on grid values
-                ys = self.y_array * other.y_array
-                xs = self.x_array
-                source = np.concatenate(([xs], [ys])).transpose()
-                # Retrieve inputs, outputs and interpolation
-                inputs = self.__inputs__[:]
-                outputs = self.__outputs__[0] + "*" + other.__outputs__[0]
-                outputs = "(" + outputs + ")"
-                interpolation = self.__interpolation__
-                extrapolation = self.__extrapolation__
-                # Create new Function object
-                return Function(source, inputs, outputs, interpolation, extrapolation)
-            else:
-                return Function(lambda x: (self.get_value(x) * other(x)))
-        # If other is Float except...
-        except AttributeError:
-            if isinstance(other, NUMERICAL_TYPES):
-                # Check if Function object source is array or callable
-                if isinstance(self.source, np.ndarray):
-                    # Operate on grid values
-                    ys = self.y_array * other
-                    xs = self.x_array
-                    source = np.concatenate(([xs], [ys])).transpose()
-                    # Retrieve inputs, outputs and interpolation
-                    inputs = self.__inputs__[:]
-                    outputs = self.__outputs__[0] + "*" + str(other)
-                    outputs = "(" + outputs + ")"
-                    interpolation = self.__interpolation__
-                    extrapolation = self.__extrapolation__
-                    # Create new Function object
-                    return Function(
-                        source, inputs, outputs, interpolation, extrapolation
-                    )
-                else:
-                    return Function(lambda x: (self.get_value(x) * other))
-            # Or if it is just a callable
-            elif callable(other):
-                return Function(lambda x: (self.get_value(x) * other(x)))
+        self_source_is_array = isinstance(self.source, np.ndarray)
+        other_source_is_array = (
+            isinstance(other.source, np.ndarray)
+            if isinstance(other, Function)
+            else False
+        )
+        inputs = self.__inputs__[:]
+        interp = self.__interpolation__
+        extrap = self.__extrapolation__
+
+        if (
+            self_source_is_array
+            and other_source_is_array
+            and np.array_equal(self.x_array, other.x_array)
+        ):
+            source = np.column_stack((self.x_array, self.y_array * other.y_array))
+            outputs = f"({self.__outputs__[0]}*{other.__outputs__[0]})"
+            return Function(source, inputs, outputs, interp, extrap)
+        elif isinstance(other, NUMERICAL_TYPES):
+            if not self_source_is_array:
+                return Function(lambda x: (self.get_value_opt(x) * other), inputs)
+            source = np.column_stack((self.x_array, np.multiply(self.y_array, other)))
+            outputs = f"({self.__outputs__[0]}*{other})"
+            return Function(
+                source,
+                inputs,
+                outputs,
+                interp,
+                extrap,
+            )
+        elif callable(other):
+            return Function(lambda x: (self.get_value_opt(x) * other(x)), inputs)
+        else:
+            raise TypeError("Unsupported type for multiplication")
 
     def __rmul__(self, other):
         """Multiplies 'other' by a Function object and returns a new Function
@@ -2331,10 +2205,10 @@ def __pow__(self, other):
                         source, inputs, outputs, interpolation, extrapolation
                     )
                 else:
-                    return Function(lambda x: (self.get_value(x) ** other))
+                    return Function(lambda x: (self.get_value_opt(x) ** other))
             # Or if it is just a callable
             elif callable(other):
-                return Function(lambda x: (self.get_value(x) ** other(x)))
+                return Function(lambda x: (self.get_value_opt(x) ** other(x)))
 
     def __rpow__(self, other):
         """Raises 'other' to the power of a Function object and returns
@@ -2367,10 +2241,10 @@ def __rpow__(self, other):
                 # Create new Function object
                 return Function(source, inputs, outputs, interpolation, extrapolation)
             else:
-                return Function(lambda x: (other ** self.get_value(x)))
+                return Function(lambda x: (other ** self.get_value_opt(x)))
         # Or if it is just a callable
         elif callable(other):
-            return Function(lambda x: (other(x) ** self.get_value(x)))
+            return Function(lambda x: (other(x) ** self.get_value_opt(x)))
 
     def __matmul__(self, other):
         """Operator @ as an alias for composition. Therefore, this
@@ -2545,12 +2419,46 @@ def differentiate(self, x, dx=1e-6, order=1):
             Evaluated derivative.
         """
         if order == 1:
-            return (self.get_value(x + dx) - self.get_value(x - dx)) / (2 * dx)
+            return (self.get_value_opt(x + dx) - self.get_value_opt(x - dx)) / (2 * dx)
         elif order == 2:
             return (
-                self.get_value(x + dx) - 2 * self.get_value(x) + self.get_value(x - dx)
+                self.get_value_opt(x + dx)
+                - 2 * self.get_value_opt(x)
+                + self.get_value_opt(x - dx)
             ) / dx**2
 
+    def differentiate_complex_step(self, x, dx=1e-200, order=1):
+        """Differentiate a Function object at a given point using the complex
+        step method. This method can be faster than ``Function.differentiate``
+        since it requires only one evaluation of the function. However, the
+        evaluated function must accept complex numbers as input.
+
+        Parameters
+        ----------
+        x : float
+            Point at which to differentiate.
+        dx : float, optional
+            Step size to use for numerical differentiation, by default 1e-200.
+        order : int, optional
+            Order of differentiation, by default 1. Right now, only first order
+            derivative is supported.
+
+        Returns
+        -------
+        float
+            The real part of the derivative of the function at the given point.
+
+        References
+        ----------
+        [1] https://mdolab.engin.umich.edu/wiki/guide-complex-step-derivative-approximation
+        """
+        if order == 1:
+            return float(self.get_value_opt(x + dx * 1j).imag / dx)
+        else:
+            raise NotImplementedError(
+                "Only 1st order derivatives are supported yet. " "Set order=1."
+            )
+
     def identity_function(self):
         """Returns a Function object that correspond to the identity mapping,
         i.e. f(x) = x.
@@ -2992,189 +2900,188 @@ def savetxt(
             file.write(header_line + newline)
             np.savetxt(file, data_points, fmt=fmt, delimiter=delimiter, newline=newline)
 
-    @staticmethod
-    def _check_user_input(
-        source,
-        inputs=None,
-        outputs=None,
-        interpolation=None,
-        extrapolation=None,
-    ):
-        """
-        Validates and processes the user input parameters for creating or
-        modifying a Function object. This function ensures the inputs, outputs,
-        interpolation, and extrapolation parameters are compatible with the
-        given source. It converts the source to a numpy array if necessary, sets
-        default values and raises warnings or errors for incompatible or
-        ill-defined parameters.
+    # Input validators
+    def __validate_source(self, source):
+        """Used to validate the source parameter for creating a Function object.
 
         Parameters
         ----------
-        source : list, np.ndarray, or callable
-            The source data or Function object. If a list or ndarray, it should
-            contain numeric data. If a Function, its inputs and outputs are
-            checked against the provided inputs and outputs.
-        inputs : list of str or None
-            The names of the input variables. If None, defaults are generated
-            based on the dimensionality of the source.
-        outputs : str or list of str
-            The name(s) of the output variable(s). If a list is provided, it
-            must have a single element.
-        interpolation : str or None
-            The method of interpolation to be used. For multidimensional sources
-            it defaults to 'shepard' if not provided.
-        extrapolation : str or None
-            The method of extrapolation to be used. For multidimensional sources
-            it defaults to 'natural' if not provided.
+        source : np.ndarray, callable, str, Path, Function, list
+            The source data of the Function object. This can be a numpy array,
+            a callable function, a string or Path object to a csv or txt file,
+            a Function object, or a list of numbers.
 
         Returns
         -------
-        tuple
-            A tuple containing the processed inputs, outputs, interpolation, and
-            extrapolation parameters.
+        np.ndarray, callable
+            The validated source parameter.
 
         Raises
         ------
         ValueError
-            If the dimensionality of the source does not match the combined
-            dimensions of inputs and outputs. If the outputs list has more than
-            one element.
-        TypeError
-            If the source is not a list, np.ndarray, Function object, str or
-            Path.
-        Warning
-            If inputs or outputs do not match for a Function source, or if
-            defaults are used for inputs, interpolation,and extrapolation for a
-            multidimensional source.
+            If the source is not a valid type or if the source is not a 2D array
+            or a callable function.
+        """
+        if isinstance(source, Function):
+            return source.get_source()
 
-        Examples
-        --------
-        >>> from rocketpy import Function
-        >>> source = np.array([(1, 1), (2, 4), (3, 9)])
-        >>> inputs = "x"
-        >>> outputs = ["y"]
-        >>> interpolation = 'linear'
-        >>> extrapolation = 'zero'
-        >>> inputs, outputs, interpolation, extrapolation = Function._check_user_input(
-        ...     source, inputs, outputs, interpolation, extrapolation
-        ... )
-        >>> inputs
-        ['x']
-        >>> outputs
-        ['y']
-        >>> interpolation
-        'linear'
-        >>> extrapolation
-        'zero'
-        """
-        # check output type and dimensions
-        if isinstance(outputs, str):
-            outputs = [outputs]
-        if isinstance(inputs, str):
-            inputs = [inputs]
+        if isinstance(source, (str, Path)):
+            # Read csv or txt files and create a numpy array
+            try:
+                source = np.loadtxt(source, delimiter=",", dtype=np.float64)
+            except ValueError:
+                with open(source, "r") as file:
+                    header, *data = file.read().splitlines()
+
+                header = [label.strip("'").strip('"') for label in header.split(",")]
+                source = np.loadtxt(data, delimiter=",", dtype=np.float64)
+
+                if len(source[0]) == len(header):
+                    if self.__inputs__ is None:
+                        self.__inputs__ = header[:-1]
+                    if self.__outputs__ is None:
+                        self.__outputs__ = [header[-1]]
+            except Exception as e:
+                raise ValueError(
+                    "Could not read the csv or txt file to create Function source."
+                ) from e
+
+        if isinstance(source, list) or isinstance(source, np.ndarray):
+            # Triggers an error if source is not a list of numbers
+            source = np.array(source, dtype=np.float64)
+
+            # Checks if 2D array
+            if len(source.shape) != 2:
+                raise ValueError(
+                    "Source must be a 2D array in the form [[x1, x2 ..., xn, y], ...]."
+                )
+            return source
+
+        if isinstance(source, (int, float)):
+            # Convert number source into vectorized lambda function
+            temp = 1 * source
+
+            def source_function(_):
+                return temp
+
+            return source_function
+
+        # If source is a callable function
+        return source
 
-        if len(outputs) > 1:
+    def __validate_inputs(self, inputs):
+        """Used to validate the inputs parameter for creating a Function object.
+        It sets a default value if it is not provided.
+
+        Parameters
+        ----------
+        inputs : list of str, None
+            The name(s) of the input variable(s). If None, defaults to "Scalar".
+
+        Returns
+        -------
+        list
+            The validated inputs parameter.
+        """
+        if self.__dom_dim__ == 1:
+            if inputs is None:
+                return ["Scalar"]
+            if isinstance(inputs, str):
+                return [inputs]
+            if isinstance(inputs, (list, tuple)):
+                if len(inputs) == 1:
+                    return inputs
             raise ValueError(
-                "Output must either be a string or have dimension 1, "
-                + f"it currently has dimension ({len(outputs)})."
+                "Inputs must be a string or a list of strings with "
+                "the length of the domain dimension."
+            )
+        if self.__dom_dim__ > 1:
+            if inputs is None:
+                return [f"Input {i+1}" for i in range(self.__dom_dim__)]
+            if isinstance(inputs, list):
+                if len(inputs) == self.__dom_dim__ and all(
+                    isinstance(i, str) for i in inputs
+                ):
+                    return inputs
+            raise ValueError(
+                "Inputs must be a list of strings with "
+                "the length of the domain dimension."
             )
 
-        # check source for data type
-        # if list or ndarray, check for dimensions, interpolation and extrapolation
-        if isinstance(source, Function):
-            source = source.get_source()
-        if isinstance(source, (list, np.ndarray, str, Path)):
-            # Deal with csv or txt
-            if isinstance(source, (str, Path)):
-                # Convert to numpy array
-                try:
-                    source = np.loadtxt(source, delimiter=",", dtype=float)
-                except ValueError:
-                    with open(source, "r") as file:
-                        header, *data = file.read().splitlines()
-
-                    header = [
-                        label.strip("'").strip('"') for label in header.split(",")
-                    ]
-                    source = np.loadtxt(data, delimiter=",", dtype=float)
-
-                    if len(source[0]) == len(header):
-                        if inputs == ["Scalar"]:
-                            inputs = header[:-1]
-                        if outputs == ["Scalar"]:
-                            outputs = [header[-1]]
-                except Exception as e:
-                    raise ValueError(
-                        "The source file is not a valid csv or txt file."
-                    ) from e
-
-            else:
-                # this will also trigger an error if the source is not a list of
-                # numbers or if the array is not homogeneous
-                source = np.array(source, dtype=np.float64)
-
-            # check dimensions
-            source_dim = source.shape[1]
-
-            # check interpolation and extrapolation
-
-            ## single dimension
-            if source_dim == 2:
-                # possible interpolation values: linear, polynomial, akima and spline
-                if interpolation is None:
-                    interpolation = "spline"
-                elif interpolation.lower() not in [
-                    "spline",
-                    "linear",
-                    "polynomial",
-                    "akima",
-                ]:
-                    warnings.warn(
-                        "Interpolation method for single dimensional functions was "
-                        + f"set to 'spline', the {interpolation} method is not supported."
-                    )
-                    interpolation = "spline"
-
-                # possible extrapolation values: constant, natural, zero
-                if extrapolation is None:
-                    extrapolation = "constant"
-                elif extrapolation.lower() not in ["constant", "natural", "zero"]:
-                    warnings.warn(
-                        "Extrapolation method for single dimensional functions was "
-                        + f"set to 'constant', the {extrapolation} method is not supported."
-                    )
-                    extrapolation = "constant"
-
-            ## multiple dimensions
-            elif source_dim > 2:
-                # check for inputs and outputs
-                if inputs == ["Scalar"]:
-                    inputs = [f"Input {i+1}" for i in range(source_dim - 1)]
-
-                if interpolation not in [None, "shepard"]:
-                    warnings.warn(
-                        (
-                            "Interpolation method for multidimensional functions was"
-                            "set to 'shepard', other methods are not supported yet."
-                        ),
-                    )
-                interpolation = "shepard"
+    def __validate_outputs(self, outputs):
+        """Used to validate the outputs parameter for creating a Function object.
+        It sets a default value if it is not provided.
 
-                if extrapolation not in [None, "natural"]:
-                    warnings.warn(
-                        "Extrapolation method for multidimensional functions was set"
-                        "to 'natural', other methods are not supported yet."
-                    )
-                extrapolation = "natural"
+        Parameters
+        ----------
+        outputs : str, list of str, None
+            The name of the output variables. If None, defaults to "Scalar".
 
-            # check input dimensions
-            in_out_dim = len(inputs) + len(outputs)
-            if source_dim != in_out_dim:
+        Returns
+        -------
+        list
+            The validated outputs parameter.
+        """
+        if outputs is None:
+            return ["Scalar"]
+        if isinstance(outputs, str):
+            return [outputs]
+        if isinstance(outputs, (list, tuple)):
+            if len(outputs) > 1:
                 raise ValueError(
-                    f"Source dimension ({source_dim}) does not match input "
-                    + f"and output dimension ({in_out_dim})."
+                    "Output must either be a string or a list of strings with "
+                    + f"one item. It currently has dimension ({len(outputs)})."
+                )
+            return outputs
+
+    def __validate_interpolation(self, interpolation):
+        if self.__dom_dim__ == 1:
+            # possible interpolation values: linear, polynomial, akima and spline
+            if interpolation is None:
+                interpolation = "spline"
+            elif interpolation.lower() not in [
+                "spline",
+                "linear",
+                "polynomial",
+                "akima",
+            ]:
+                warnings.warn(
+                    "Interpolation method set to 'spline' because the "
+                    f"{interpolation} method is not supported."
+                )
+                interpolation = "spline"
+        ## multiple dimensions
+        elif self.__dom_dim__ > 1:
+            if interpolation not in [None, "shepard"]:
+                warnings.warn(
+                    (
+                        "Interpolation method set to 'shepard'. Only 'shepard' "
+                        "interpolation is supported for multiple dimensions."
+                    ),
+                )
+            interpolation = "shepard"
+        return interpolation
+
+    def __validate_extrapolation(self, extrapolation):
+        if self.__dom_dim__ == 1:
+            if extrapolation is None:
+                extrapolation = "constant"
+            elif extrapolation.lower() not in ["constant", "natural", "zero"]:
+                warnings.warn(
+                    "Extrapolation method set to 'constant' because the "
+                    f"{extrapolation} method is not supported."
+                )
+                extrapolation = "constant"
+
+        ## multiple dimensions
+        elif self.__dom_dim__ > 1:
+            if extrapolation not in [None, "natural"]:
+                warnings.warn(
+                    "Extrapolation method set to 'natural'. Other methods "
+                    "are not supported yet."
                 )
-        return inputs, outputs, interpolation, extrapolation
+            extrapolation = "natural"
+        return extrapolation
 
 
 class PiecewiseFunction(Function):
@@ -3258,7 +3165,7 @@ def calc_output(func, inputs):
             """
             output = np.zeros(len(inputs))
             for j, value in enumerate(inputs):
-                output[j] = func.get_value(value)
+                output[j] = func.get_value_opt(value)
             return output
 
         input_data = []
diff --git a/rocketpy/motors/solid_motor.py b/rocketpy/motors/solid_motor.py
index db3527a95..4c55c1ee4 100644
--- a/rocketpy/motors/solid_motor.py
+++ b/rocketpy/motors/solid_motor.py
@@ -195,7 +195,7 @@ def __init__(
         grain_separation,
         grains_center_of_mass_position,
         center_of_dry_mass_position,
-        nozzle_position=0,
+        nozzle_position=0.0,
         burn_time=None,
         throat_radius=0.01,
         reshape_thrust_curve=False,
diff --git a/rocketpy/plots/environment_analysis_plots.py b/rocketpy/plots/environment_analysis_plots.py
index 9fbf68d95..26727aba9 100644
--- a/rocketpy/plots/environment_analysis_plots.py
+++ b/rocketpy/plots/environment_analysis_plots.py
@@ -1454,7 +1454,7 @@ def wind_speed_profile_grid(self, clear_range_limits=False):
             if self.env_analysis.forecast:
                 forecast = self.env_analysis.forecast
                 y = self.env_analysis.average_wind_speed_profile_by_hour[hour][1]
-                x = forecast[hour].wind_speed.get_value(y) * convert_units(
+                x = forecast[hour].wind_speed.get_value_opt(y) * convert_units(
                     1, "m/s", self.env_analysis.unit_system["wind_speed"]
                 )
                 ax.plot(x, y, "b--")
diff --git a/rocketpy/plots/monte_carlo_plots.py b/rocketpy/plots/monte_carlo_plots.py
new file mode 100644
index 000000000..587f98b11
--- /dev/null
+++ b/rocketpy/plots/monte_carlo_plots.py
@@ -0,0 +1,165 @@
+import matplotlib.pyplot as plt
+
+from ..tools import generate_monte_carlo_ellipses
+
+
+class _MonteCarloPlots:
+    """Class to plot the Monte Carlo analysis results."""
+
+    def __init__(self, monte_carlo):
+        self.monte_carlo = monte_carlo
+
+    def ellipses(
+        self,
+        image=None,
+        actual_landing_point=None,
+        perimeter_size=3000,
+        xlim=(-3000, 3000),
+        ylim=(-3000, 3000),
+        save=False,
+    ):
+        """
+        Plot the error ellipses for the apogee and impact points of the rocket.
+
+        Parameters
+        ----------
+        image : str, optional
+            Path to the background image, usually a map of the launch site.
+        actual_landing_point : tuple, optional
+            Actual landing point of the rocket in (x, y) meters.
+        perimeter_size : int, optional
+            Size of the perimeter to be plotted. Default is 3000.
+        xlim : tuple, optional
+            Limits of the x-axis. Default is (-3000, 3000). Values in meters.
+        ylim : tuple, optional
+            Limits of the y-axis. Default is (-3000, 3000). Values in meters.
+        save : bool, optional
+            Whether to save the plot as a file. Default is False. If True, the
+            plot is saved and not displayed. If False, the plot is displayed.
+
+        Returns
+        -------
+        None
+        """
+
+        # Import background map
+        if image is not None:
+            try:
+                from imageio import imread
+
+                img = imread(image)
+            except ImportError:
+                raise ImportError(
+                    "The 'imageio' package is required to add background images. Please install it."
+                )
+            except FileNotFoundError:
+                raise FileNotFoundError(
+                    "The image file was not found. Please check the path."
+                )
+
+        impact_ellipses, apogee_ellipses, apogee_x, apogee_y, impact_x, impact_y = (
+            generate_monte_carlo_ellipses(self.monte_carlo.results)
+        )
+
+        # Create plot figure
+        plt.figure(figsize=(8, 6), dpi=150)
+        ax = plt.subplot(111)
+
+        for ell in impact_ellipses:
+            ax.add_artist(ell)
+        for ell in apogee_ellipses:
+            ax.add_artist(ell)
+
+        # Draw points
+        plt.scatter(0, 0, s=30, marker="*", color="black", label="Launch Point")
+        plt.scatter(
+            apogee_x, apogee_y, s=5, marker="^", color="green", label="Simulated Apogee"
+        )
+        plt.scatter(
+            impact_x,
+            impact_y,
+            s=5,
+            marker="v",
+            color="blue",
+            label="Simulated Landing Point",
+        )
+
+        if actual_landing_point:
+            plt.scatter(
+                actual_landing_point[0],
+                actual_landing_point[1],
+                s=20,
+                marker="X",
+                color="red",
+                label="Measured Landing Point",
+            )
+
+        plt.legend()
+        ax.set_title(
+            "1$\\sigma$, 2$\\sigma$ and 3$\\sigma$ Monte Carlo Ellipses: Apogee and Landing Points"
+        )
+        ax.set_ylabel("North (m)")
+        ax.set_xlabel("East (m)")
+
+        # Add background image to plot
+        # TODO: In the future, integrate with other libraries to plot the map (e.g. cartopy, ee, etc.)
+        # You can translate the basemap by changing dx and dy (in meters)
+        dx = 0
+        dy = 0
+        if image is not None:
+            plt.imshow(
+                img,
+                zorder=0,
+                extent=[
+                    -perimeter_size - dx,
+                    perimeter_size - dx,
+                    -perimeter_size - dy,
+                    perimeter_size - dy,
+                ],
+            )
+
+        plt.axhline(0, color="black", linewidth=0.5)
+        plt.axvline(0, color="black", linewidth=0.5)
+        plt.xlim(*xlim)
+        plt.ylim(*ylim)
+
+        if save:
+            plt.savefig(
+                f"{self.monte_carlo.filename}.png", bbox_inches="tight", pad_inches=0
+            )
+        else:
+            plt.show()
+
+    def all(self, keys=None):
+        """
+        Plot the histograms of the Monte Carlo simulation results.
+
+        Parameters
+        ----------
+        keys : str, list or tuple, optional
+            The keys of the results to be plotted. If None, all results will be
+            plotted. Default is None.
+
+        Returns
+        -------
+        None
+        """
+        if keys is None:
+            keys = self.monte_carlo.results.keys()
+        elif isinstance(keys, str):
+            keys = [keys]
+        elif isinstance(keys, (list, tuple)):
+            keys = list(set(keys).intersection(self.monte_carlo.results.keys()))
+            if len(keys) == 0:
+                raise ValueError(
+                    "The specified 'keys' are not available in the results."
+                )
+        else:
+            raise ValueError("The 'keys' argument must be a string, list, or tuple.")
+
+        for key in keys:
+            plt.figure()
+            plt.hist(self.monte_carlo.results[key])
+            plt.title(f"Histogram of {key}")
+            plt.ylabel("Number of Occurrences")
+            plt.show()
diff --git a/rocketpy/plots/rocket_plots.py b/rocketpy/plots/rocket_plots.py
index e57fe87e4..b96cd8c9c 100644
--- a/rocketpy/plots/rocket_plots.py
+++ b/rocketpy/plots/rocket_plots.py
@@ -135,10 +135,22 @@ def drag_curves(self):
         None
         """
 
-        x_power_drag_off = self.rocket.power_off_drag.x_array
-        y_power_drag_off = self.rocket.power_off_drag.y_array
-        x_power_drag_on = self.rocket.power_on_drag.x_array
-        y_power_drag_on = self.rocket.power_on_drag.y_array
+        try:
+            x_power_drag_on = self.rocket.power_on_drag.x_array
+            y_power_drag_on = self.rocket.power_on_drag.y_array
+        except AttributeError:
+            x_power_drag_on = np.linspace(0, 2, 50)
+            y_power_drag_on = np.array(
+                [self.rocket.power_on_drag.source(x) for x in x_power_drag_on]
+            )
+        try:
+            x_power_drag_off = self.rocket.power_off_drag.x_array
+            y_power_drag_off = self.rocket.power_off_drag.y_array
+        except AttributeError:
+            x_power_drag_off = np.linspace(0, 2, 50)
+            y_power_drag_off = np.array(
+                [self.rocket.power_off_drag.source(x) for x in x_power_drag_off]
+            )
 
         fig, ax = plt.subplots()
         ax.plot(x_power_drag_on, y_power_drag_on, label="Power on Drag")
diff --git a/rocketpy/prints/monte_carlo_prints.py b/rocketpy/prints/monte_carlo_prints.py
new file mode 100644
index 000000000..6249626ce
--- /dev/null
+++ b/rocketpy/prints/monte_carlo_prints.py
@@ -0,0 +1,27 @@
+class _MonteCarloPrints:
+    """Class to print the monte carlo analysis results."""
+
+    def __init__(self, monte_carlo):
+        self.monte_carlo = monte_carlo
+
+    def all(self):
+        """Print the mean and standard deviation of each parameter in the results
+        dictionary or of the variables passed as argument.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        None
+
+        """
+        print("Monte Carlo Simulation by RocketPy")
+        print("Data Source: ", self.monte_carlo.filename)
+        print("Number of simulations: ", self.monte_carlo.num_of_loaded_sims)
+        print("Results: \n")
+        print(f"{'Parameter':>25} {'Mean':>15} {'Std. Dev.':>15}")
+        print("-" * 60)
+        for key, value in self.monte_carlo.processed_results.items():
+            print(f"{key:>25} {value[0]:>15.3f} {value[1]:>15.3f}")
diff --git a/rocketpy/rocket/aero_surface.py b/rocketpy/rocket/aero_surface.py
index a5ea26638..aa32ef77e 100644
--- a/rocketpy/rocket/aero_surface.py
+++ b/rocketpy/rocket/aero_surface.py
@@ -34,6 +34,37 @@ def __init__(self, name):
         self.name = name
         return None
 
+    # Defines beta parameter
+    @staticmethod
+    def _beta(mach):
+        """Defines a parameter that is often used in aerodynamic
+        equations. It is commonly used in the Prandtl factor which
+        corrects subsonic force coefficients for compressible flow.
+        This is applied to the lift coefficient of the nose cone,
+        fins and tails/transitions as in [1].
+
+        Parameters
+        ----------
+        mach : int, float
+            Number of mach.
+
+        Returns
+        -------
+        beta : int, float
+            Value that characterizes flow speed based on the mach number.
+
+        References
+        ----------
+        [1] Barrowman, James S. https://arc.aiaa.org/doi/10.2514/6.1979-504
+        """
+
+        if mach < 0.8:
+            return np.sqrt(1 - mach**2)
+        elif mach < 1.1:
+            return np.sqrt(1 - 0.8**2)
+        else:
+            return np.sqrt(mach**2 - 1)
+
     @abstractmethod
     def evaluate_center_of_pressure(self):
         """Evaluates the center of pressure of the aerodynamic surface in local
@@ -367,7 +398,7 @@ def evaluate_geometrical_parameters(self):
         return None
 
     def evaluate_nose_shape(self):
-        """Calculates and saves nose cone's shape as lists and reavulates the
+        """Calculates and saves nose cone's shape as lists and re-evaluates the
         nose cone's length for a given bluffness ratio. The shape is saved as
         two vectors, one for the x coordinates and one for the y coordinates.
 
@@ -381,7 +412,9 @@ def evaluate_nose_shape(self):
 
         # Calculate a function to find the tangential intersection point between the circle and nosecone curve.
         def find_x_intercept(x):
-            return x + self.y_nosecone(x) * self.y_nosecone.differentiate(x)
+            return x + self.y_nosecone(x) * self.y_nosecone.differentiate_complex_step(
+                x
+            )
 
         # Calculate a function to find the radius of the nosecone curve
         def find_radius(x):
@@ -411,11 +444,11 @@ def test_circle(x):
                     r_circle, circle_center, x_init = 0, 0, 0
                 else:
                     # Find the intersection point between circle and nosecone curve
-                    x_init = fsolve(lambda x: find_radius(x) - r_circle, r_circle)[0]
+                    x_init = fsolve(lambda x: find_radius(x[0]) - r_circle, r_circle)[0]
                     circle_center = find_x_intercept(x_init)
             else:
                 # Find the intersection point between circle and nosecone curve
-                x_init = fsolve(lambda x: find_radius(x) - r_circle, r_circle)[0]
+                x_init = fsolve(lambda x: find_radius(x[0]) - r_circle, r_circle)[0]
                 circle_center = find_x_intercept(x_init)
 
         # Calculate a function to create the circle at the correct position
@@ -463,7 +496,7 @@ def evaluate_lift_coefficient(self):
         # It must be set as a Function because it will be called and treated
         # as a function of mach in the simulation.
         self.clalpha = Function(
-            lambda mach: 2 * self.radius_ratio**2,
+            lambda mach: 2 / self._beta(mach) * self.radius_ratio**2,
             "Mach",
             f"Lift coefficient derivative for {self.name}",
         )
@@ -770,14 +803,16 @@ def evaluate_lift_coefficient(self):
             )
 
             # Differentiating at alpha = 0 to get cl_alpha
-            clalpha2D_incompressible = self.airfoil_cl.differentiate(x=1e-3, dx=1e-3)
+            clalpha2D_incompressible = self.airfoil_cl.differentiate_complex_step(
+                x=1e-3, dx=1e-3
+            )
 
             # Convert to radians if needed
             if self.airfoil[1] == "degrees":
                 clalpha2D_incompressible *= 180 / np.pi
 
         # Correcting for compressible flow (apply Prandtl-Glauert correction)
-        clalpha2D = Function(lambda mach: clalpha2D_incompressible / self.__beta(mach))
+        clalpha2D = Function(lambda mach: clalpha2D_incompressible / self._beta(mach))
 
         # Diederich's Planform Correlation Parameter
         FD = 2 * np.pi * self.AR / (clalpha2D * np.cos(self.gamma_c))
@@ -853,30 +888,6 @@ def evaluate_roll_parameters(self):
         self.roll_parameters = [clf_delta, cld_omega, self.cant_angle_rad]
         return self.roll_parameters
 
-    # Defines beta parameter
-    def __beta(_, mach):
-        """Defines a parameter that is often used in aerodynamic
-        equations. It is commonly used in the Prandtl factor which
-        corrects subsonic force coefficients for compressible flow.
-
-        Parameters
-        ----------
-        mach : int, float
-            Number of mach.
-
-        Returns
-        -------
-        beta : int, float
-            Value that characterizes flow speed based on the mach number.
-        """
-
-        if mach < 0.8:
-            return np.sqrt(1 - mach**2)
-        elif mach < 1.1:
-            return np.sqrt(1 - 0.8**2)
-        else:
-            return np.sqrt(mach**2 - 1)
-
     # Defines number of fins  factor
     def __fin_num_correction(_, n):
         """Calculates a correction factor for the lift coefficient of multiple
@@ -1744,6 +1755,7 @@ def evaluate_lift_coefficient(self):
         # as a function of mach in the simulation.
         self.clalpha = Function(
             lambda mach: 2
+            / self._beta(mach)
             * (
                 (self.bottom_radius / self.rocket_radius) ** 2
                 - (self.top_radius / self.rocket_radius) ** 2
@@ -1978,7 +1990,7 @@ def __init__(
             Default is False.
         deployment_level : float, optional
             Initial deployment level, ranging from 0 to 1. Deployment level is
-            the fraction of the total airbrake area that is deployed. Default
+            the fraction of the total airbrake area that is Deployment. Default
             is 0.
         name : str, optional
             Name of the air brakes. Default is "AirBrakes".
diff --git a/rocketpy/rocket/parachute.py b/rocketpy/rocket/parachute.py
index c1bff2638..a051c0ec3 100644
--- a/rocketpy/rocket/parachute.py
+++ b/rocketpy/rocket/parachute.py
@@ -72,6 +72,11 @@ class Parachute:
     Parachute.lag : float
         Time, in seconds, between the parachute ejection system is triggered
         and the parachute is fully opened.
+    Parachute.noise : tuple, list
+        List in the format (mean, standard deviation, time-correlation).
+        The values are used to add noise to the pressure signal which is passed
+        to the trigger function. Default value is (0, 0, 0). Units are in
+        pascal.
     Parachute.noise_bias : float
         Mean value of the noise added to the pressure signal, which is
         passed to the trigger function. Unit is in pascal.
@@ -161,6 +166,7 @@ def __init__(
         self.trigger = trigger
         self.sampling_rate = sampling_rate
         self.lag = lag
+        self.noise = noise
         self.noise_signal = [[-1e-6, np.random.normal(noise[0], noise[1])]]
         self.noisy_pressure_signal = []
         self.clean_pressure_signal = []
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index 117a6d95f..da660bd5c 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -4,7 +4,7 @@
 
 from rocketpy.control.controller import _Controller
 from rocketpy.mathutils.function import Function
-from rocketpy.mathutils.vector_matrix import Vector
+from rocketpy.mathutils.vector_matrix import Vector, Matrix
 from rocketpy.motors.motor import EmptyMotor
 from rocketpy.plots.rocket_plots import _RocketPlots
 from rocketpy.prints.rocket_prints import _RocketPrints
@@ -73,6 +73,9 @@ class Rocket:
         for more information
         regarding the coordinate system.
         Expressed in meters as a function of time.
+    Rocket.com_to_cdm_function : Function
+        Function of time expressing the z-coordinate of the center of mass
+        relative to the center of dry mass.
     Rocket.reduced_mass : Function
         Function of time expressing the reduced mass of the rocket,
         defined as the product of the propellant mass and the mass
@@ -147,6 +150,11 @@ class Rocket:
         defined rocket coordinate system.
         See :doc:`Positions and Coordinate Systems </user/positions>`
         for more information.
+    Rocket.nozzle_to_cdm : float
+        Distance between the nozzle exit and the rocket's center of dry mass
+        position, in meters.
+    Rocket.nozzle_gyration_tensor: Matrix
+        Matrix representing the nozzle gyration tensor.
     Rocket.center_of_propellant_position : Function
         Position of the propellant's center of mass relative to the user defined
         rocket reference system. See
@@ -542,7 +550,11 @@ def evaluate_stability_margin(self):
         """
         self.stability_margin.set_source(
             lambda mach, time: (
-                (self.center_of_mass(time) - self.cp_position(mach)) / (2 * self.radius)
+                (
+                    self.center_of_mass.get_value_opt(time)
+                    - self.cp_position.get_value_opt(mach)
+                )
+                / (2 * self.radius)
             )
             * self._csys
         )
@@ -560,7 +572,10 @@ def evaluate_static_margin(self):
         """
         # Calculate static margin
         self.static_margin.set_source(
-            lambda time: (self.center_of_mass(time) - self.cp_position(0))
+            lambda time: (
+                self.center_of_mass.get_value_opt(time)
+                - self.cp_position.get_value_opt(0)
+            )
             / (2 * self.radius)
         )
         # Change sign if coordinate system is upside down
@@ -723,8 +738,133 @@ def evaluate_inertias(self):
             self.I_23,
         )
 
+    def evaluate_nozzle_to_cdm(self):
+        """Evaluates the distance between the nozzle exit and the rocket's
+        center of dry mass.
+
+        Returns
+        -------
+        self.nozzle_to_cdm : float
+            Distance between the nozzle exit and the rocket's center of dry
+            mass position, in meters.
+        """
+        self.nozzle_to_cdm = (
+            -(self.nozzle_position - self.center_of_dry_mass_position) * self._csys
+        )
+        return self.nozzle_to_cdm
+
     def evaluate_nozzle_gyration_tensor(self):
-        pass
+        """Calculates and returns the nozzle gyration tensor relative to the
+        rocket's center of dry mass. The gyration tensor is saved and returned
+        in units of kg*m².
+
+        Returns
+        -------
+        self.nozzle_gyration_tensor : Matrix
+            Matrix containing the nozzle gyration tensor.
+        """
+        S_noz_33 = 0.5 * self.motor.nozzle_radius**2
+        S_noz_11 = S_noz_22 = 0.5 * S_noz_33 + 0.25 * self.nozzle_to_cdm**2
+        S_noz_12, S_noz_13, S_noz_23 = 0, 0, 0  # Due to axis symmetry
+        self.nozzle_gyration_tensor = Matrix(
+            [
+                [S_noz_11, S_noz_12, S_noz_13],
+                [S_noz_12, S_noz_22, S_noz_23],
+                [S_noz_13, S_noz_23, S_noz_33],
+            ]
+        )
+        return self.nozzle_gyration_tensor
+
+    def evaluate_com_to_cdm_function(self):
+        """Evaluates the z-coordinate of the center of mass (COM) relative to
+        the center of dry mass (CDM).
+
+        Notes
+        -----
+        1. The `com_to_cdm_function` plus `center_of_mass` should be equal
+        to `center_of_dry_mass_position` at every time step.
+        2. The `com_to_cdm_function` is a function of time and will usually
+        already be discretized.
+
+        Returns
+        -------
+        self.com_to_cdm_function : Function
+            Function of time expressing the z-coordinate of the center of mass
+            relative to the center of dry mass.
+        """
+        self.com_to_cdm_function = (
+            -1
+            * (
+                (self.center_of_propellant_position - self.center_of_dry_mass_position)
+                * self._csys
+            )
+            * self.motor.propellant_mass
+            / self.total_mass
+        )
+        self.com_to_cdm_function.set_inputs("Time (s)")
+        self.com_to_cdm_function.set_outputs("Z Coordinate COM to CDM (m)")
+        self.com_to_cdm_function.set_title("Z Coordinate COM to CDM")
+        return self.com_to_cdm_function
+
+    def get_inertia_tensor_at_time(self, t):
+        """Returns a Matrix representing the inertia tensor of the rocket with
+        respect to the rocket's center of mass at a given time. It evaluates
+        each inertia tensor component at the given time and returns a Matrix
+        with the computed values.
+
+        Parameters
+        ----------
+        t : float
+            Time at which the inertia tensor is to be evaluated.
+
+        Returns
+        -------
+        Matrix
+            Inertia tensor of the rocket at time t.
+        """
+        I_11 = self.I_11.get_value_opt(t)
+        I_12 = self.I_12.get_value_opt(t)
+        I_13 = self.I_13.get_value_opt(t)
+        I_22 = self.I_22.get_value_opt(t)
+        I_23 = self.I_23.get_value_opt(t)
+        I_33 = self.I_33.get_value_opt(t)
+        return Matrix(
+            [
+                [I_11, I_12, I_13],
+                [I_12, I_22, I_23],
+                [I_13, I_23, I_33],
+            ]
+        )
+
+    def get_inertia_tensor_derivative_at_time(self, t):
+        """Returns a Matrix representing the time derivative of the inertia
+        tensor of the rocket with respect to the rocket's center of mass at a
+        given time. It evaluates each inertia tensor component's derivative at
+        the given time and returns a Matrix with the computed values.
+
+        Parameters
+        ----------
+        t : float
+            Time at which the inertia tensor derivative is to be evaluated.
+
+        Returns
+        -------
+        Matrix
+            Inertia tensor time derivative of the rocket at time t.
+        """
+        I_11_dot = self.I_11.differentiate_complex_step(t)
+        I_12_dot = self.I_12.differentiate_complex_step(t)
+        I_13_dot = self.I_13.differentiate_complex_step(t)
+        I_22_dot = self.I_22.differentiate_complex_step(t)
+        I_23_dot = self.I_23.differentiate_complex_step(t)
+        I_33_dot = self.I_33.differentiate_complex_step(t)
+        return Matrix(
+            [
+                [I_11_dot, I_12_dot, I_13_dot],
+                [I_12_dot, I_22_dot, I_23_dot],
+                [I_13_dot, I_23_dot, I_33_dot],
+            ]
+        )
 
     def add_motor(self, motor, position):
         """Adds a motor to the rocket.
@@ -767,6 +907,7 @@ def add_motor(self, motor, position):
         self.evaluate_dry_mass()
         self.evaluate_total_mass()
         self.evaluate_center_of_dry_mass()
+        self.evaluate_nozzle_to_cdm()
         self.evaluate_center_of_mass()
         self.evaluate_dry_inertias()
         self.evaluate_inertias()
@@ -775,6 +916,8 @@ def add_motor(self, motor, position):
         self.evaluate_center_of_pressure()
         self.evaluate_stability_margin()
         self.evaluate_static_margin()
+        self.evaluate_com_to_cdm_function()
+        self.evaluate_nozzle_gyration_tensor()
 
     def add_surfaces(self, surfaces, positions):
         """Adds one or more aerodynamic surfaces to the rocket. The aerodynamic
@@ -943,7 +1086,7 @@ def add_trapezoidal_fins(
         tip_chord,
         span,
         position,
-        cant_angle=0,
+        cant_angle=0.0,
         sweep_length=None,
         sweep_angle=None,
         radius=None,
diff --git a/rocketpy/simulation/__init__.py b/rocketpy/simulation/__init__.py
index 46c3b40ed..b1aecdd99 100644
--- a/rocketpy/simulation/__init__.py
+++ b/rocketpy/simulation/__init__.py
@@ -1,2 +1,3 @@
 from .flight import Flight
 from .flight_data_importer import FlightDataImporter
+from .monte_carlo import MonteCarlo
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 8204c4696..417be86af 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -13,7 +13,10 @@
 from ..plots.flight_plots import _FlightPlots
 from ..prints.flight_prints import _FlightPrints
 from ..tools import (
+    calculate_cubic_hermite_coefficients,
     find_closest,
+    find_root_linear_interpolation,
+    find_roots_cubic_function,
     quaternions_to_nutation,
     quaternions_to_precession,
     quaternions_to_spin,
@@ -183,13 +186,13 @@ class Flight:
     Flight.function_evaluations : array
         List that stores number of derivative function evaluations
         during numerical integration in cumulative manner.
-    Flight.function_evaluations_per_time_step : array
+    Flight.function_evaluations_per_time_step : list
         List that stores number of derivative function evaluations
         per time step during numerical integration.
     Flight.time_steps : array
         List of time steps taking during numerical integration in
         seconds.
-    Flight.FlightPhases : Flight.FlightPhases
+    Flight.flight_phases : Flight.FlightPhases
         Stores and manages flight phases.
     Flight.wind_velocity_x : Function
         Wind velocity X (East) experienced by the rocket as a
@@ -488,8 +491,8 @@ def __init__(
         rocket,
         environment,
         rail_length,
-        inclination=80,
-        heading=90,
+        inclination=80.0,
+        heading=90.0,
         initial_solution=None,
         terminate_on_apogee=False,
         max_time=600,
@@ -581,13 +584,7 @@ def __init__(
         -------
         None
         """
-        # Fetch helper classes and functions
-        FlightPhases = self.FlightPhases
-        TimeNodes = self.TimeNodes
-        time_iterator = self.time_iterator
-
-        # Save rocket, parachutes, environment, maximum simulation time
-        # and termination events
+        # Save arguments
         self.env = environment
         self.rocket = rocket
         self.rail_length = rail_length
@@ -606,40 +603,50 @@ def __init__(
         self.terminate_on_apogee = terminate_on_apogee
         self.name = name
         self.equations_of_motion = equations_of_motion
-        # Flight initialization
+
+        # Controller initialization
         self.__init_controllers()
-        self.__init_post_process_variables()
+
+        # Flight initialization
         self.__init_solution_monitors()
         self.__init_equations_of_motion()
-
-        # Initialize prints and plots objects
-        self.prints = _FlightPrints(self)
-        self.plots = _FlightPlots(self)
-
-        # Initialize solver monitors
         self.__init_solver_monitors()
 
         # Create known flight phases
-        self.FlightPhases = FlightPhases()
-        self.FlightPhases.add_phase(
+        self.flight_phases = self.FlightPhases()
+        self.flight_phases.add_phase(
             self.t_initial, self.initial_derivative, clear=False
         )
-        self.FlightPhases.add_phase(self.max_time)
+        self.flight_phases.add_phase(self.max_time)
 
         # Simulate flight
-        for phase_index, phase in time_iterator(self.FlightPhases):
-            # print('\nCurrent Flight Phase List')
-            # print(self.FlightPhases)
-            # print('\n\tCurrent Flight Phase')
-            # print('\tIndex: ', phase_index, ' | Phase: ', phase)
+        self.__simulate(verbose)
+
+        # Initialize prints and plots objects
+        self.prints = _FlightPrints(self)
+        self.plots = _FlightPlots(self)
+
+    def __repr__(self):
+        return (
+            f"<Flight(rocket= {self.rocket}, "
+            f"environment= {self.env}, "
+            f"rail_length= {self.rail_length}, "
+            f"inclination= {self.inclination}, "
+            f"heading = {self.heading},"
+            f"name= {self.name})>"
+        )
+
+    def __simulate(self, verbose):
+        """Simulate the flight trajectory."""
+        for phase_index, phase in self.time_iterator(self.flight_phases):
             # Determine maximum time for this flight phase
-            phase.time_bound = self.FlightPhases[phase_index + 1].t
+            phase.time_bound = self.flight_phases[phase_index + 1].t
 
             # Evaluate callbacks
             for callback in phase.callbacks:
                 callback(self)
 
-            # Create solver for this flight phase
+            # Create solver for this flight phase # TODO: allow different integrators
             self.function_evaluations.append(0)
             phase.solver = integrate.LSODA(
                 phase.derivative,
@@ -651,49 +658,39 @@ def __init__(
                 rtol=self.rtol,
                 atol=self.atol,
             )
-            # print('\n\tSolver Initialization Details')
-            # print('\t_initial Time: ', phase.t)
-            # print('\t_initial State: ', self.y_sol)
-            # print('\tTime Bound: ', phase.time_bound)
-            # print('\tMin Step: ', self.min_time_step)
-            # print('\tMax Step: ', self.max_time_step)
-            # print('\tTolerances: ', self.rtol, self.atol)
 
             # Initialize phase time nodes
-            phase.TimeNodes = TimeNodes()
-            # Add first time node to permanent list
-            phase.TimeNodes.add_node(phase.t, [], [], [])
+            phase.time_nodes = self.TimeNodes()
+            # Add first time node to the time_nodes list
+            phase.time_nodes.add_node(phase.t, [], [])
             # Add non-overshootable parachute time nodes
             if self.time_overshoot is False:
-                phase.TimeNodes.add_parachutes(
+                # TODO: move parachutes to controllers
+                phase.time_nodes.add_parachutes(
                     self.parachutes, phase.t, phase.time_bound
                 )
-                phase.TimeNodes.add_sensors(
+                phase.time_nodes.add_sensors(
                     self.rocket.sensors, phase.t, phase.time_bound
                 )
-                phase.TimeNodes.add_controllers(
+                phase.time_nodes.add_controllers(
                     self._controllers, phase.t, phase.time_bound
                 )
-            # Add lst time node to permanent list
-            phase.TimeNodes.add_node(phase.time_bound, [], [], [])
-            # Sort time nodes
-            phase.TimeNodes.sort()
-            # Merge equal time nodes
-            phase.TimeNodes.merge()
+            # Add last time node to the time_nodes list
+            phase.time_nodes.add_node(phase.time_bound, [], [], [])
+            # Organize time nodes with sort() and merge()
+            phase.time_nodes.sort()
+            phase.time_nodes.merge()
             # Clear triggers from first time node if necessary
             if phase.clear:
-                phase.TimeNodes[0].parachutes = []
-                phase.TimeNodes[0].callbacks = []
-
-            # print('\n\tPhase Time Nodes')
-            # print('\tTime Nodes Length: ', str(len(phase.TimeNodes)), ' | Time Nodes Preview: ', phase.TimeNodes[0:3])
+                phase.time_nodes[0].parachutes = []
+                phase.time_nodes[0].callbacks = []
 
             # Iterate through time nodes
-            for node_index, node in time_iterator(phase.TimeNodes):
-                # print('\n\t\tCurrent Time Node')
-                # print('\t\tIndex: ', node_index, ' | Time Node: ', node)
+            for node_index, node in self.time_iterator(phase.time_nodes):
                 # Determine time bound for this time node
-                node.time_bound = phase.TimeNodes[node_index + 1].t
+                node.time_bound = phase.time_nodes[node_index + 1].t
+                # NOTE: Setting the time bound and status for the phase solver,
+                # and updating its internal state for the next integration step.
                 phase.solver.t_bound = node.time_bound
                 phase.solver._lsoda_solver._integrator.rwork[0] = phase.solver.t_bound
                 phase.solver._lsoda_solver._integrator.call_args[4] = (
@@ -702,6 +699,7 @@ def __init__(
                 phase.solver.status = "running"
 
                 # Feed required parachute and discrete controller triggers
+                # TODO: parachutes should be moved to controllers
                 for callback in node.callbacks:
                     callback(self)
 
@@ -733,30 +731,24 @@ def __init__(
 
                 for parachute in node.parachutes:
                     # Calculate and save pressure signal
-                    pressure = self.env.pressure.get_value_opt(self.y_sol[2])
-                    parachute.clean_pressure_signal.append([node.t, pressure])
-                    # Calculate and save noise
-                    noise = parachute.noise_function()
-                    parachute.noise_signal.append([node.t, noise])
-                    parachute.noisy_pressure_signal.append([node.t, pressure + noise])
-                    # Gets height above ground level considering noise
-                    hAGL = (
-                        self.env.barometric_height(pressure + noise)
-                        - self.env.elevation
+                    noisy_pressure, height_above_ground_level = (
+                        self.__calculate_and_save_pressure_signals(
+                            parachute, node.t, self.y_sol[2]
+                        )
                     )
                     if parachute.triggerfunc(
-                        pressure + noise, hAGL, self.y_sol, self.sensors
+                        noisy_pressure,
+                        height_above_ground_level,
+                        self.y_sol,
+                        self.sensors,
                     ):
-                        # print('\nEVENT DETECTED')
-                        # print('Parachute Triggered')
-                        # print('Name: ', parachute.name, ' | Lag: ', parachute.lag)
                         # Remove parachute from flight parachutes
                         self.parachutes.remove(parachute)
                         # Create flight phase for time after detection and before inflation
                         # Must only be created if parachute has any lag
                         i = 1
                         if parachute.lag != 0:
-                            self.FlightPhases.add_phase(
+                            self.flight_phases.add_phase(
                                 node.t,
                                 phase.derivative,
                                 clear=True,
@@ -769,7 +761,7 @@ def __init__(
                                 self, "parachute_cd_s", parachute_cd_s
                             )
                         ]
-                        self.FlightPhases.add_phase(
+                        self.flight_phases.add_phase(
                             node.t + parachute.lag,
                             self.u_dot_parachute,
                             callbacks,
@@ -777,37 +769,24 @@ def __init__(
                             index=phase_index + i,
                         )
                         # Prepare to leave loops and start new flight phase
-                        phase.TimeNodes.flush_after(node_index)
-                        phase.TimeNodes.add_node(self.t, [], [], [])
+                        phase.time_nodes.flush_after(node_index)
+                        phase.time_nodes.add_node(self.t, [], [], [])
                         phase.solver.status = "finished"
                         # Save parachute event
                         self.parachute_events.append([self.t, parachute])
 
                 # Step through simulation
                 while phase.solver.status == "running":
-                    # Step
+                    # Execute solver step, log solution and function evaluations
                     phase.solver.step()
-                    # Save step result
                     self.solution += [[phase.solver.t, *phase.solver.y]]
-                    # Step step metrics
-                    self.function_evaluations_per_time_step.append(
-                        phase.solver.nfev - self.function_evaluations[-1]
-                    )
                     self.function_evaluations.append(phase.solver.nfev)
-                    self.time_steps.append(phase.solver.step_size)
+
                     # Update time and state
                     self.t = phase.solver.t
                     self.y_sol = phase.solver.y
                     if verbose:
-                        print(
-                            "Current Simulation Time: {:3.4f} s".format(self.t),
-                            end="\r",
-                        )
-                    # print('\n\t\t\tCurrent Step Details')
-                    # print('\t\t\tIState: ', phase.solver._lsoda_solver._integrator.istate)
-                    # print('\t\t\tTime: ', phase.solver.t)
-                    # print('\t\t\tAltitude: ', phase.solver.y[2])
-                    # print('\t\t\tEvals: ', self.function_evaluations_per_time_step[-1])
+                        print(f"Current Simulation Time: {self.t:3.4f} s", end="\r")
 
                     # Check for first out of rail event
                     if len(self.out_of_rail_state) == 1 and (
@@ -816,12 +795,7 @@ def __init__(
                         + (self.y_sol[2] - self.env.elevation) ** 2
                         >= self.effective_1rl**2
                     ):
-                        # Rocket is out of rail
                         # Check exactly when it went out using root finding
-                        # States before and after
-                        # t0 -> 0
-                        # print('\nEVENT DETECTED')
-                        # print('Rocket is Out of Rail!')
                         # Disconsider elevation
                         self.solution[-2][3] -= self.env.elevation
                         self.solution[-1][3] -= self.env.elevation
@@ -851,24 +825,23 @@ def __init__(
                         self.solution[-2][3] += self.env.elevation
                         self.solution[-1][3] += self.env.elevation
                         # Cubic Hermite interpolation (ax**3 + bx**2 + cx + d)
-                        D = float(phase.solver.step_size)
-                        d = float(y0)
-                        c = float(yp0)
-                        b = float((3 * y1 - yp1 * D - 2 * c * D - 3 * d) / (D**2))
-                        a = float(-(2 * y1 - yp1 * D - c * D - 2 * d) / (D**3)) + 1e-5
+                        a, b, c, d = calculate_cubic_hermite_coefficients(
+                            0,
+                            float(phase.solver.step_size),
+                            y0,
+                            yp0,
+                            y1,
+                            yp1,
+                        )
+                        a += 1e-5  # TODO: why??
                         # Find roots
-                        d0 = b**2 - 3 * a * c
-                        d1 = 2 * b**3 - 9 * a * b * c + 27 * d * a**2
-                        c1 = ((d1 + (d1**2 - 4 * d0**3) ** (0.5)) / 2) ** (1 / 3)
-                        t_roots = []
-                        for k in [0, 1, 2]:
-                            c2 = c1 * (-1 / 2 + 1j * (3**0.5) / 2) ** k
-                            t_roots.append(-(1 / (3 * a)) * (b + c2 + d0 / c2))
+                        t_roots = find_roots_cubic_function(a, b, c, d)
                         # Find correct root
-                        valid_t_root = []
-                        for t_root in t_roots:
-                            if 0 < t_root.real < t1 and abs(t_root.imag) < 0.001:
-                                valid_t_root.append(t_root.real)
+                        valid_t_root = [
+                            t_root.real
+                            for t_root in t_roots
+                            if 0 < t_root.real < t1 and abs(t_root.imag) < 0.001
+                        ]
                         if len(valid_t_root) > 1:
                             raise ValueError(
                                 "Multiple roots found when solving for rail exit time."
@@ -885,31 +858,23 @@ def __init__(
                         self.out_of_rail_time = self.t
                         self.out_of_rail_time_index = len(self.solution) - 1
                         self.out_of_rail_state = self.y_sol
-                        self.out_of_rail_velocity = (
-                            self.y_sol[3] ** 2 + self.y_sol[4] ** 2 + self.y_sol[5] ** 2
-                        ) ** (0.5)
                         # Create new flight phase
-                        self.FlightPhases.add_phase(
+                        self.flight_phases.add_phase(
                             self.t,
                             self.u_dot_generalized,
                             index=phase_index + 1,
                         )
                         # Prepare to leave loops and start new flight phase
-                        phase.TimeNodes.flush_after(node_index)
-                        phase.TimeNodes.add_node(self.t, [], [], [])
+                        phase.time_nodes.flush_after(node_index)
+                        phase.time_nodes.add_node(self.t, [], [], [])
                         phase.solver.status = "finished"
 
                     # Check for apogee event
                     if len(self.apogee_state) == 1 and self.y_sol[5] < 0:
-                        # print('\nPASSIVE EVENT DETECTED')
-                        # print('Rocket Has Reached Apogee!')
-                        # Apogee reported
                         # Assume linear vz(t) to detect when vz = 0
-                        vz0 = self.solution[-2][6]
-                        t0 = self.solution[-2][0]
-                        vz1 = self.solution[-1][6]
-                        t1 = self.solution[-1][0]
-                        t_root = -(t1 - t0) * vz0 / (vz1 - vz0) + t0
+                        t0, vz0 = self.solution[-2][0], self.solution[-2][6]
+                        t1, vz1 = self.solution[-1][0], self.solution[-1][6]
+                        t_root = find_root_linear_interpolation(t0, t1, vz0, vz1, 0)
                         # Fetch state at t_root
                         interpolator = phase.solver.dense_output()
                         self.apogee_state = interpolator(t_root)
@@ -918,88 +883,66 @@ def __init__(
                         self.apogee_x = self.apogee_state[0]
                         self.apogee_y = self.apogee_state[1]
                         self.apogee = self.apogee_state[2]
+
                         if self.terminate_on_apogee:
-                            # print('Terminate on Apogee Activated!')
-                            self.t = t_root
-                            self.t_final = self.t
-                            self.state = self.apogee_state
+                            self.t = self.t_final = t_root
                             # Roll back solution
-                            self.solution[-1] = [self.t, *self.state]
+                            self.solution[-1] = [self.t, *self.apogee_state]
                             # Set last flight phase
-                            self.FlightPhases.flush_after(phase_index)
-                            self.FlightPhases.add_phase(self.t)
+                            self.flight_phases.flush_after(phase_index)
+                            self.flight_phases.add_phase(self.t)
                             # Prepare to leave loops and start new flight phase
-                            phase.TimeNodes.flush_after(node_index)
-                            phase.TimeNodes.add_node(self.t, [], [], [])
+                            phase.time_nodes.flush_after(node_index)
+                            phase.time_nodes.add_node(self.t, [], [], [])
                             phase.solver.status = "finished"
                     # Check for impact event
                     if self.y_sol[2] < self.env.elevation:
-                        # print('\nPASSIVE EVENT DETECTED')
-                        # print('Rocket Has Reached Ground!')
-                        # Impact reported
-                        # Check exactly when it went out using root finding
-                        # States before and after
-                        # t0 -> 0
-                        # Disconsider elevation
-                        self.solution[-2][3] -= self.env.elevation
-                        self.solution[-1][3] -= self.env.elevation
-                        # Get points
-                        y0 = self.solution[-2][3]
-                        yp0 = self.solution[-2][6]
-                        t1 = self.solution[-1][0] - self.solution[-2][0]
-                        y1 = self.solution[-1][3]
-                        yp1 = self.solution[-1][6]
-                        # Put elevation back
-                        self.solution[-2][3] += self.env.elevation
-                        self.solution[-1][3] += self.env.elevation
+                        # Check exactly when it happened using root finding
                         # Cubic Hermite interpolation (ax**3 + bx**2 + cx + d)
-                        D = float(phase.solver.step_size)
-                        d = float(y0)
-                        c = float(yp0)
-                        b = float((3 * y1 - yp1 * D - 2 * c * D - 3 * d) / (D**2))
-                        a = float(-(2 * y1 - yp1 * D - c * D - 2 * d) / (D**3))
+                        a, b, c, d = calculate_cubic_hermite_coefficients(
+                            x0=0,  # t0
+                            x1=float(phase.solver.step_size),  # t1 - t0
+                            y0=float(self.solution[-2][3] - self.env.elevation),  # z0
+                            yp0=float(self.solution[-2][6]),  # vz0
+                            y1=float(self.solution[-1][3] - self.env.elevation),  # z1
+                            yp1=float(self.solution[-1][6]),  # vz1
+                        )
                         # Find roots
-                        d0 = b**2 - 3 * a * c
-                        d1 = 2 * b**3 - 9 * a * b * c + 27 * d * a**2
-                        c1 = ((d1 + (d1**2 - 4 * d0**3) ** (0.5)) / 2) ** (1 / 3)
-                        t_roots = []
-                        for k in [0, 1, 2]:
-                            c2 = c1 * (-1 / 2 + 1j * (3**0.5) / 2) ** k
-                            t_roots.append(-(1 / (3 * a)) * (b + c2 + d0 / c2))
+                        t_roots = find_roots_cubic_function(a, b, c, d)
                         # Find correct root
-                        valid_t_root = []
-                        for t_root in t_roots:
-                            if 0 < t_root.real < t1 and abs(t_root.imag) < 0.001:
-                                valid_t_root.append(t_root.real)
+                        t1 = self.solution[-1][0] - self.solution[-2][0]
+                        valid_t_root = [
+                            t_root.real
+                            for t_root in t_roots
+                            if abs(t_root.imag) < 0.001 and 0 < t_root.real < t1
+                        ]
                         if len(valid_t_root) > 1:
                             raise ValueError(
                                 "Multiple roots found when solving for impact time."
                             )
                         # Determine impact state at t_root
-                        self.t = valid_t_root[0] + self.solution[-2][0]
+                        self.t = self.t_final = valid_t_root[0] + self.solution[-2][0]
                         interpolator = phase.solver.dense_output()
-                        self.y_sol = interpolator(self.t)
+                        self.y_sol = self.impact_state = interpolator(self.t)
                         # Roll back solution
                         self.solution[-1] = [self.t, *self.y_sol]
                         # Save impact state
-                        self.impact_state = self.y_sol
                         self.x_impact = self.impact_state[0]
                         self.y_impact = self.impact_state[1]
                         self.z_impact = self.impact_state[2]
                         self.impact_velocity = self.impact_state[5]
-                        self.t_final = self.t
                         # Set last flight phase
-                        self.FlightPhases.flush_after(phase_index)
-                        self.FlightPhases.add_phase(self.t)
+                        self.flight_phases.flush_after(phase_index)
+                        self.flight_phases.add_phase(self.t)
                         # Prepare to leave loops and start new flight phase
-                        phase.TimeNodes.flush_after(node_index)
-                        phase.TimeNodes.add_node(self.t, [], [], [])
+                        phase.time_nodes.flush_after(node_index)
+                        phase.time_nodes.add_node(self.t, [], [], [])
                         phase.solver.status = "finished"
 
                     # List and feed overshootable time nodes
                     if self.time_overshoot:
                         # Initialize phase overshootable time nodes
-                        overshootable_nodes = TimeNodes()
+                        overshootable_nodes = self.TimeNodes()
                         # Add overshootable parachute time nodes
                         overshootable_nodes.add_parachutes(
                             self.parachutes, self.solution[-2][0], self.t
@@ -1007,68 +950,47 @@ def __init__(
                         # Add last time node (always skipped)
                         overshootable_nodes.add_node(self.t, [], [], [])
                         if len(overshootable_nodes) > 1:
-                            # Sort overshootable time nodes
+                            # Sort and merge equal overshootable time nodes
                             overshootable_nodes.sort()
-                            # Merge equal overshootable time nodes
                             overshootable_nodes.merge()
                             # Clear if necessary
                             if overshootable_nodes[0].t == phase.t and phase.clear:
                                 overshootable_nodes[0].parachutes = []
                                 overshootable_nodes[0].callbacks = []
-                            # print('\n\t\t\t\tOvershootable Time Nodes')
-                            # print('\t\t\t\tInterval: ', self.solution[-2][0], self.t)
-                            # print('\t\t\t\tOvershootable Nodes Length: ', str(len(overshootable_nodes)), ' | Overshootable Nodes: ', overshootable_nodes)
                             # Feed overshootable time nodes trigger
                             interpolator = phase.solver.dense_output()
                             for (
                                 overshootable_index,
                                 overshootable_node,
-                            ) in time_iterator(overshootable_nodes):
-                                # print('\n\t\t\t\tCurrent Overshootable Node')
-                                # print('\t\t\t\tIndex: ', overshootable_index, ' | Overshootable Node: ', overshootable_node)
+                            ) in self.time_iterator(overshootable_nodes):
                                 # Calculate state at node time
-                                overshootable_node.y = interpolator(
+                                overshootable_node.y_sol = interpolator(
                                     overshootable_node.t
                                 )
-                                # Calculate and save pressure signal
-                                pressure = self.env.pressure.get_value_opt(
-                                    overshootable_node.y[2]
-                                )
                                 for parachute in overshootable_node.parachutes:
-                                    # Save pressure signal
-                                    parachute.clean_pressure_signal.append(
-                                        [overshootable_node.t, pressure]
-                                    )
-                                    # Calculate and save noise
-                                    noise = parachute.noise_function()
-                                    parachute.noise_signal.append(
-                                        [overshootable_node.t, noise]
-                                    )
-                                    parachute.noisy_pressure_signal.append(
-                                        [overshootable_node.t, pressure + noise]
-                                    )
-                                    # Gets height above ground level considering noise
-                                    hAGL = (
-                                        self.env.barometric_height(pressure + noise)
-                                        - self.env.elevation
+                                    # Calculate and save pressure signal
+                                    noisy_pressure, height_above_ground_level = (
+                                        self.__calculate_and_save_pressure_signals(
+                                            parachute,
+                                            overshootable_node.t,
+                                            overshootable_node.y_sol[2],
+                                        )
                                     )
 
+                                    # Check for parachute trigger
                                     if parachute.triggerfunc(
-                                        pressure + noise,
-                                        hAGL,
-                                        overshootable_node.y,
+                                        noisy_pressure,
+                                        height_above_ground_level,
+                                        overshootable_node.y_sol,
                                         self.sensors,
                                     ):
-                                        # print('\nEVENT DETECTED')
-                                        # print('Parachute Triggered')
-                                        # print('Name: ', parachute.name, ' | Lag: ', parachute.lag)
                                         # Remove parachute from flight parachutes
                                         self.parachutes.remove(parachute)
                                         # Create flight phase for time after detection and before inflation
                                         # Must only be created if parachute has any lag
                                         i = 1
                                         if parachute.lag != 0:
-                                            self.FlightPhases.add_phase(
+                                            self.flight_phases.add_phase(
                                                 overshootable_node.t,
                                                 phase.derivative,
                                                 clear=True,
@@ -1081,7 +1003,7 @@ def __init__(
                                                 self, "parachute_cd_s", parachute_cd_s
                                             )
                                         ]
-                                        self.FlightPhases.add_phase(
+                                        self.flight_phases.add_phase(
                                             overshootable_node.t + parachute.lag,
                                             self.u_dot_parachute,
                                             callbacks,
@@ -1090,17 +1012,17 @@ def __init__(
                                         )
                                         # Rollback history
                                         self.t = overshootable_node.t
-                                        self.y_sol = overshootable_node.y
+                                        self.y_sol = overshootable_node.y_sol
                                         self.solution[-1] = [
                                             overshootable_node.t,
-                                            *overshootable_node.y,
+                                            *overshootable_node.y_sol,
                                         ]
                                         # Prepare to leave loops and start new flight phase
                                         overshootable_nodes.flush_after(
                                             overshootable_index
                                         )
-                                        phase.TimeNodes.flush_after(node_index)
-                                        phase.TimeNodes.add_node(self.t, [], [], [])
+                                        phase.time_nodes.flush_after(node_index)
+                                        phase.time_nodes.add_node(self.t, [], [], [])
                                         phase.solver.status = "finished"
                                         # Save parachute event
                                         self.parachute_events.append(
@@ -1112,61 +1034,64 @@ def __init__(
                         phase.derivative(self.t, self.y_sol, post_processing=True)
 
         self.t_final = self.t
-        self._calculate_pressure_signal()
+        self.__transform_pressure_signals_lists_to_functions()
         if self._controllers:
-            self.__cache_post_process_variables()
+            # cache post process variables
+            self.__evaluate_post_process = np.array(self.__post_processed_variables)
         if self.sensors:
             self.__cache_sensor_data()
         if verbose:
-            print("Simulation Completed at Time: {:3.4f} s".format(self.t))
-
-    def __init_post_process_variables(self):
-        """Initialize post-process variables."""
-        # Initialize all variables calculated after initialization.
-        # Important to do so that MATLAB® can access them
-        self._drift = Function(0)
-        self._bearing = Function(0)
-        self._latitude = Function(0)
-        self._longitude = Function(0)
-        # Initialize state derivatives, force and atmospheric arrays
-        self.ax_list = []
-        self.ay_list = []
-        self.az_list = []
-        self.alpha1_list = []
-        self.alpha2_list = []
-        self.alpha3_list = []
-        self.R1_list = []
-        self.R2_list = []
-        self.R3_list = []
-        self.M1_list = []
-        self.M2_list = []
-        self.M3_list = []
-        self.pressure_list = []
-        self.density_list = []
-        self.dynamic_viscosity_list = []
-        self.speed_of_sound_list = []
-        self.wind_velocity_x_list = []
-        self.wind_velocity_y_list = []
+            print(f"\n>>> Simulation Completed at Time: {self.t:3.4f} s")
+
+    def __calculate_and_save_pressure_signals(self, parachute, t, z):
+        """Gets noise and pressure signals and saves them in the parachute
+        object given the current time and altitude.
+
+        Parameters
+        ----------
+        parachute : Parachute
+            The parachute object to calculate signals for.
+        t : float
+            The current time in seconds.
+        z : float
+            The altitude above sea level in meters.
+
+        Returns
+        -------
+        tuple[float, float]
+            The noisy pressure and height above ground level.
+        """
+        # Calculate pressure and noise
+        pressure = self.env.pressure.get_value_opt(z)
+        noise = parachute.noise_function()
+        noisy_pressure = pressure + noise
+
+        # Stores in the parachute object
+        parachute.clean_pressure_signal.append([t, pressure])
+        parachute.noise_signal.append([t, noise])
+
+        # Gets height above ground level considering noise
+        height_above_ground_level = (
+            self.env.barometric_height.get_value_opt(noisy_pressure)
+            - self.env.elevation
+        )
+
+        return noisy_pressure, height_above_ground_level
 
     def __init_solution_monitors(self):
         # Initialize solution monitors
         self.out_of_rail_time = 0
         self.out_of_rail_time_index = 0
         self.out_of_rail_state = np.array([0])
-        self.out_of_rail_velocity = 0
         self.apogee_state = np.array([0])
         self.apogee_time = 0
-        self.apogee_x = 0
-        self.apogee_y = 0
-        self.apogee = 0
         self.x_impact = 0
         self.y_impact = 0
         self.impact_velocity = 0
         self.impact_state = np.array([0])
         self.parachute_events = []
         self.post_processed = False
-
-        return None
+        self.__post_processed_variables = []
 
     def __init_flight_state(self):
         """Initialize flight state variables."""
@@ -1228,8 +1153,6 @@ def __init_flight_state(self):
     def __init_solver_monitors(self):
         # Initialize solver monitors
         self.function_evaluations = []
-        self.function_evaluations_per_time_step = []
-        self.time_steps = []
         # Initialize solution state
         self.solution = []
         self.__init_flight_state()
@@ -1242,6 +1165,7 @@ def __init_solver_monitors(self):
     def __init_equations_of_motion(self):
         """Initialize equations of motion."""
         if self.equations_of_motion == "solid_propulsion":
+            # NOTE: The u_dot is faster, but only works for solid propulsion
             self.u_dot_generalized = self.u_dot
 
     def __init_controllers(self):
@@ -1249,7 +1173,7 @@ def __init_controllers(self):
         self._controllers = self.rocket._controllers[:]
         self.sensors = self.rocket.sensors.get_components()
         if self._controllers or self.sensors:
-            if self.time_overshoot == True:
+            if self.time_overshoot:
                 self.time_overshoot = False
                 warnings.warn(
                     "time_overshoot has been set to False due to the presence "
@@ -1264,29 +1188,6 @@ def __init_controllers(self):
             sensor._reset(self.rocket)  # resets noise and measurement list
             self.sensor_data[sensor] = []
 
-    def __cache_post_process_variables(self):
-        """Cache post-process variables for simulations with controllers."""
-        self.__retrieve_arrays = [
-            self.ax_list,
-            self.ay_list,
-            self.az_list,
-            self.alpha1_list,
-            self.alpha2_list,
-            self.alpha3_list,
-            self.R1_list,
-            self.R2_list,
-            self.R3_list,
-            self.M1_list,
-            self.M2_list,
-            self.M3_list,
-            self.pressure_list,
-            self.density_list,
-            self.dynamic_viscosity_list,
-            self.speed_of_sound_list,
-            self.wind_velocity_x_list,
-            self.wind_velocity_y_list,
-        ]
-
     def __cache_sensor_data(self):
         """Cache sensor data for simulations with sensors."""
         sensor_data = {}
@@ -1331,25 +1232,34 @@ def effective_2rl(self):
 
     @cached_property
     def frontal_surface_wind(self):
-        # Surface wind magnitude in the frontal direction at the rail's elevation
-        wind_u = self.env.wind_velocity_x(self.env.elevation)
-        wind_v = self.env.wind_velocity_y(self.env.elevation)
+        """Frontal wind velocity at the surface level. The frontal wind is
+        defined as the wind blowing in the direction of the rocket's heading.
+
+        Returns
+        -------
+        float
+            Wind velocity in the frontal direction at the surface level.
+        """
+        wind_u = self.env.wind_velocity_x.get_value_opt(self.env.elevation)
+        wind_v = self.env.wind_velocity_y.get_value_opt(self.env.elevation)
         heading_rad = self.heading * np.pi / 180
-        frontal_surface_wind = wind_u * np.sin(heading_rad) + wind_v * np.cos(
-            heading_rad
-        )
-        return frontal_surface_wind
+        return wind_u * np.sin(heading_rad) + wind_v * np.cos(heading_rad)
 
     @cached_property
     def lateral_surface_wind(self):
-        # Surface wind magnitude in the lateral direction at the rail's elevation
-        wind_u = self.env.wind_velocity_x(self.env.elevation)
-        wind_v = self.env.wind_velocity_y(self.env.elevation)
+        """Lateral wind velocity at the surface level. The lateral wind is
+        defined as the wind blowing perpendicular to the rocket's heading.
+
+        Returns
+        -------
+        float
+            Wind velocity in the lateral direction at the surface level.
+        """
+        wind_u = self.env.wind_velocity_x.get_value_opt(self.env.elevation)
+        wind_v = self.env.wind_velocity_y.get_value_opt(self.env.elevation)
         heading_rad = self.heading * np.pi / 180
-        lateral_surface_wind = -wind_u * np.cos(heading_rad) + wind_v * np.sin(
-            heading_rad
-        )
-        return lateral_surface_wind
+
+        return -wind_u * np.cos(heading_rad) + wind_v * np.sin(heading_rad)
 
     def udot_rail1(self, t, u, post_processing=False):
         """Calculates derivative of u state vector with respect to time
@@ -1395,7 +1305,9 @@ def udot_rail1(self, t, u, post_processing=False):
         R3 = -0.5 * rho * (free_stream_speed**2) * self.rocket.area * (drag_coeff)
 
         # Calculate Linear acceleration
-        a3 = (R3 + thrust) / M - (e0**2 - e1**2 - e2**2 + e3**2) * self.env.gravity(z)
+        a3 = (R3 + thrust) / M - (
+            e0**2 - e1**2 - e2**2 + e3**2
+        ) * self.env.gravity.get_value_opt(z)
         if a3 > 0:
             ax = 2 * (e1 * e3 + e0 * e2) * a3
             ay = 2 * (e2 * e3 - e0 * e1) * a3
@@ -1407,12 +1319,7 @@ def udot_rail1(self, t, u, post_processing=False):
             # Use u_dot post processing code for forces, moments and env data
             self.u_dot_generalized(t, u, post_processing=True)
             # Save feasible accelerations
-            self.ax_list[-1] = [t, ax]
-            self.ay_list[-1] = [t, ay]
-            self.az_list[-1] = [t, az]
-            self.alpha1_list[-1] = [t, 0]
-            self.alpha2_list[-1] = [t, 0]
-            self.alpha3_list[-1] = [t, 0]
+            self.__post_processed_variables[-1][1:7] = [ax, ay, az, 0, 0, 0]
 
         return [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
 
@@ -1466,8 +1373,7 @@ def u_dot(self, t, u, post_processing=False):
         # Retrieve integration data
         x, y, z, vx, vy, vz, e0, e1, e2, e3, omega1, omega2, omega3 = u
         # Determine lift force and moment
-        R1, R2 = 0, 0
-        M1, M2, M3 = 0, 0, 0
+        R1, R2, M1, M2, M3 = 0, 0, 0, 0, 0
         # Determine current behavior
         if t < self.rocket.motor.burn_out_time:
             # Motor burning
@@ -1487,7 +1393,6 @@ def u_dot(self, t, u, post_processing=False):
             M2 -= self.rocket.thrust_eccentricity_y * thrust
         else:
             # Motor stopped
-            # Retrieve important motor quantities
             # Inertias
             Tz, Ti, Tzdot, Tidot = 0, 0, 0, 0
             # Mass
@@ -1507,17 +1412,13 @@ def u_dot(self, t, u, post_processing=False):
         # b = -self.rocket.distance_rocket_propellant
         b = (
             -(
-                self.rocket.center_of_propellant_position(0)
+                self.rocket.center_of_propellant_position.get_value_opt(0)
                 - self.rocket.center_of_dry_mass_position
             )
             * self.rocket._csys
         )
-        # c = -self.rocket.distance_rocket_nozzle
-        c = (
-            -(self.rocket.nozzle_position - self.rocket.center_of_dry_mass_position)
-            * self.rocket._csys
-        )
-        a = b * Mt / M
+        c = self.rocket.nozzle_to_cdm
+        a = self.rocket.com_to_cdm_function.get_value_opt(t)
         rN = self.rocket.motor.nozzle_radius
         # Prepare transformation matrix
         a11 = 1 - 2 * (e2**2 + e3**2)
@@ -1531,8 +1432,6 @@ def u_dot(self, t, u, post_processing=False):
         a33 = 1 - 2 * (e1**2 + e2**2)
         # Transformation matrix: (123) -> (XYZ)
         K = [[a11, a12, a13], [a21, a22, a23], [a31, a32, a33]]
-        # Transformation matrix: (XYZ) -> (123) or K transpose
-        Kt = [[a11, a21, a31], [a12, a22, a32], [a13, a23, a33]]
 
         # Calculate Forces and Moments
         # Get freestream speed
@@ -1553,7 +1452,7 @@ def u_dot(self, t, u, post_processing=False):
         R3 = -0.5 * rho * (free_stream_speed**2) * self.rocket.area * drag_coeff
         for air_brakes in self.rocket.air_brakes:
             if air_brakes.deployment_level > 0:
-                air_brakes_cd = air_brakes.drag_coefficient(
+                air_brakes_cd = air_brakes.drag_coefficient.get_value_opt(
                     air_brakes.deployment_level, free_stream_mach
                 )
                 air_brakes_force = (
@@ -1567,7 +1466,6 @@ def u_dot(self, t, u, post_processing=False):
                     R3 = air_brakes_force  # Substitutes rocket drag coefficient
                 else:
                     R3 += air_brakes_force
-        # R3 += self.__computeDragForce(z, Vector(vx, vy, vz))
         # Off center moment
         M1 += self.rocket.cp_eccentricity_y * R3
         M2 -= self.rocket.cp_eccentricity_x * R3
@@ -1608,7 +1506,9 @@ def u_dot(self, t, u, post_processing=False):
                 comp_stream_vz_bn = comp_stream_vz_b / comp_stream_speed
                 if -1 * comp_stream_vz_bn < 1:
                     comp_attack_angle = np.arccos(-comp_stream_vz_bn)
-                    c_lift = aero_surface.cl(comp_attack_angle, free_stream_mach)
+                    c_lift = aero_surface.cl.get_value_opt(
+                        comp_attack_angle, free_stream_mach
+                    )
                     # component lift force magnitude
                     comp_lift = (
                         0.5 * rho * (comp_stream_speed**2) * reference_area * c_lift
@@ -1631,14 +1531,14 @@ def u_dot(self, t, u, post_processing=False):
                     * reference_area
                     * 2
                     * surface_radius
-                    * clf_delta(free_stream_mach)
+                    * clf_delta.get_value_opt(free_stream_mach)
                     * cant_angle_rad
                 )
                 M3d = (
                     (1 / 2 * rho * free_stream_speed)
                     * reference_area
                     * (2 * surface_radius) ** 2
-                    * cld_omega(free_stream_mach)
+                    * cld_omega.get_value_opt(free_stream_mach)
                     * omega3
                     / 2
                 )
@@ -1683,7 +1583,7 @@ def u_dot(self, t, u, post_processing=False):
             (R3 - b * Mt * (alpha2 - omega1 * omega3) + thrust) / M,
         ]
         ax, ay, az = np.dot(K, L)
-        az -= self.env.gravity(z)  # Include gravity
+        az -= self.env.gravity.get_value_opt(z)  # Include gravity
 
         # Create u_dot
         u_dot = [
@@ -1703,34 +1603,8 @@ def u_dot(self, t, u, post_processing=False):
         ]
 
         if post_processing:
-            # Accelerations
-            self.ax_list.append([t, ax])
-            self.ay_list.append([t, ay])
-            self.az_list.append([t, az])
-            self.alpha1_list.append([t, alpha1])
-            self.alpha2_list.append([t, alpha2])
-            self.alpha3_list.append([t, alpha3])
-            # Dynamics variables
-            self.R1_list.append([t, R1])
-            self.R2_list.append([t, R2])
-            self.R3_list.append([t, R3])
-            self.M1_list.append([t, M1])
-            self.M2_list.append([t, M2])
-            self.M3_list.append([t, M3])
-            # Atmospheric Conditions
-            self.wind_velocity_x_list.append(
-                [t, self.env.wind_velocity_x.get_value_opt(z)]
-            )
-            self.wind_velocity_y_list.append(
-                [t, self.env.wind_velocity_y.get_value_opt(z)]
-            )
-            self.density_list.append([t, self.env.density.get_value_opt(z)])
-            self.dynamic_viscosity_list.append(
-                [t, self.env.dynamic_viscosity.get_value_opt(z)]
-            )
-            self.pressure_list.append([t, self.env.pressure.get_value_opt(z)])
-            self.speed_of_sound_list.append(
-                [t, self.env.speed_of_sound.get_value_opt(z)]
+            self.__post_processed_variables.append(
+                [t, ax, ay, az, alpha1, alpha2, alpha3, R1, R2, R3, M1, M2, M3]
             )
 
         return u_dot
@@ -1768,73 +1642,26 @@ def u_dot_generalized(self, t, u, post_processing=False):
         w = Vector([omega1, omega2, omega3])  # Angular velocity vector
 
         # Retrieve necessary quantities
-        rho = self.env.density.get_value_opt(z)
+        ## Rocket mass
         total_mass = self.rocket.total_mass.get_value_opt(t)
         total_mass_dot = self.rocket.total_mass_flow_rate.get_value_opt(t)
-        total_mass_ddot = self.rocket.total_mass_flow_rate.differentiate(t)
+        total_mass_ddot = self.rocket.total_mass_flow_rate.differentiate_complex_step(t)
         ## CM position vector and time derivatives relative to CDM in body frame
-        r_CM_z = (
-            -1
-            * (
-                (
-                    self.rocket.center_of_propellant_position
-                    - self.rocket.center_of_dry_mass_position
-                )
-                * self.rocket._csys
-            )
-            * self.rocket.motor.propellant_mass
-            / total_mass
-        )
-        r_CM = Vector([0, 0, r_CM_z.get_value_opt(t)])
-        r_CM_dot = Vector([0, 0, r_CM_z.differentiate(t)])
+        r_CM_z = self.rocket.com_to_cdm_function
+        r_CM_t = r_CM_z.get_value_opt(t)
+        r_CM = Vector([0, 0, r_CM_t])
+        r_CM_dot = Vector([0, 0, r_CM_z.differentiate_complex_step(t)])
         r_CM_ddot = Vector([0, 0, r_CM_z.differentiate(t, order=2)])
+        ## Nozzle position vector
+        r_NOZ = Vector([0, 0, self.rocket.nozzle_to_cdm])
         ## Nozzle gyration tensor
-        r_NOZ = (
-            -(self.rocket.nozzle_position - self.rocket.center_of_dry_mass_position)
-            * self.rocket._csys
-        )
-        S_noz_33 = 0.5 * self.rocket.motor.nozzle_radius**2
-        S_noz_11 = 0.5 * S_noz_33 + 0.25 * r_NOZ**2
-        S_noz_22 = S_noz_11
-        S_noz_12 = 0
-        S_noz_13 = 0
-        S_noz_23 = 0
-        S_nozzle = Matrix(
-            [
-                [S_noz_11, S_noz_12, S_noz_13],
-                [S_noz_12, S_noz_22, S_noz_23],
-                [S_noz_13, S_noz_23, S_noz_33],
-            ]
-        )
+        S_nozzle = self.rocket.nozzle_gyration_tensor
         ## Inertia tensor
-        I_11 = self.rocket.I_11.get_value_opt(t)
-        I_12 = self.rocket.I_12.get_value_opt(t)
-        I_13 = self.rocket.I_13.get_value_opt(t)
-        I_22 = self.rocket.I_22.get_value_opt(t)
-        I_23 = self.rocket.I_23.get_value_opt(t)
-        I_33 = self.rocket.I_33.get_value_opt(t)
-        I = Matrix(
-            [
-                [I_11, I_12, I_13],
-                [I_12, I_22, I_23],
-                [I_13, I_23, I_33],
-            ]
-        )
+        I = self.rocket.get_inertia_tensor_at_time(t)
         ## Inertia tensor time derivative in the body frame
-        I_11_dot = self.rocket.I_11.differentiate(t)
-        I_12_dot = self.rocket.I_12.differentiate(t)
-        I_13_dot = self.rocket.I_13.differentiate(t)
-        I_22_dot = self.rocket.I_22.differentiate(t)
-        I_23_dot = self.rocket.I_23.differentiate(t)
-        I_33_dot = self.rocket.I_33.differentiate(t)
-        I_dot = Matrix(
-            [
-                [I_11_dot, I_12_dot, I_13_dot],
-                [I_12_dot, I_22_dot, I_23_dot],
-                [I_13_dot, I_23_dot, I_33_dot],
-            ]
-        )
-        ## Inertia tensor relative to CM
+        I_dot = self.rocket.get_inertia_tensor_derivative_at_time(t)
+
+        # Calculate the Inertia tensor relative to CM
         H = (r_CM.cross_matrix @ -r_CM.cross_matrix) * total_mass
         I_CM = I - H
 
@@ -1851,7 +1678,9 @@ def u_dot_generalized(self, t, u, post_processing=False):
         wind_velocity_y = self.env.wind_velocity_y.get_value_opt(z)
         wind_velocity = Vector([wind_velocity_x, wind_velocity_y, 0])
         free_stream_speed = abs((wind_velocity - Vector(v)))
-        free_stream_mach = free_stream_speed / self.env.speed_of_sound.get_value_opt(z)
+        speed_of_sound = self.env.speed_of_sound.get_value_opt(z)
+        free_stream_mach = free_stream_speed / speed_of_sound
+
         if t < self.rocket.motor.burn_out_time:
             drag_coeff = self.rocket.power_on_drag.get_value_opt(free_stream_mach)
         else:
@@ -1859,7 +1688,7 @@ def u_dot_generalized(self, t, u, post_processing=False):
         R3 += -0.5 * rho * (free_stream_speed**2) * self.rocket.area * drag_coeff
         for air_brakes in self.rocket.air_brakes:
             if air_brakes.deployment_level > 0:
-                air_brakes_cd = air_brakes.drag_coefficient(
+                air_brakes_cd = air_brakes.drag_coefficient.get_value_opt(
                     air_brakes.deployment_level, free_stream_mach
                 )
                 air_brakes_force = (
@@ -1898,18 +1727,18 @@ def u_dot_generalized(self, t, u, post_processing=False):
             comp_stream_velocity = comp_wind_vb - comp_vb
             comp_stream_vx_b, comp_stream_vy_b, comp_stream_vz_b = comp_stream_velocity
             comp_stream_speed = abs(comp_stream_velocity)
-            comp_stream_mach = (
-                comp_stream_speed / self.env.speed_of_sound.get_value_opt(z)
-            )
+            comp_stream_mach = comp_stream_speed / speed_of_sound
             # Component attack angle and lift force
             comp_attack_angle = 0
             comp_lift, comp_lift_xb, comp_lift_yb = 0, 0, 0
-            if comp_stream_vx_b**2 + comp_stream_vy_b**2 != 0:
+            if comp_stream_vx_b**2 + comp_stream_vy_b**2 != 0:  # TODO: maybe try/except
                 # Normalize component stream velocity in body frame
                 comp_stream_vz_bn = comp_stream_vz_b / comp_stream_speed
                 if -1 * comp_stream_vz_bn < 1:
                     comp_attack_angle = np.arccos(-comp_stream_vz_bn)
-                    c_lift = aero_surface.cl(comp_attack_angle, comp_stream_mach)
+                    c_lift = aero_surface.cl.get_value_opt(
+                        comp_attack_angle, comp_stream_mach
+                    )
                     # Component lift force magnitude
                     comp_lift = (
                         0.5 * rho * (comp_stream_speed**2) * reference_area * c_lift
@@ -1922,8 +1751,8 @@ def u_dot_generalized(self, t, u, post_processing=False):
                     R1 += comp_lift_xb
                     R2 += comp_lift_yb
                     # Add to total moment
-                    M1 -= (comp_cpz + r_CM_z.get_value_opt(t)) * comp_lift_yb
-                    M2 += (comp_cpz + r_CM_z.get_value_opt(t)) * comp_lift_xb
+                    M1 -= (comp_cpz + r_CM_t) * comp_lift_yb
+                    M2 += (comp_cpz + r_CM_t) * comp_lift_xb
             # Calculates Roll Moment
             try:
                 clf_delta, cld_omega, cant_angle_rad = aero_surface.roll_parameters
@@ -1932,31 +1761,28 @@ def u_dot_generalized(self, t, u, post_processing=False):
                     * reference_area
                     * 2
                     * surface_radius
-                    * clf_delta(comp_stream_mach)
+                    * clf_delta.get_value_opt(comp_stream_mach)
                     * cant_angle_rad
                 )
                 M3d = (
                     (1 / 2 * rho * comp_stream_speed)
                     * reference_area
                     * (2 * surface_radius) ** 2
-                    * cld_omega(comp_stream_mach)
+                    * cld_omega.get_value_opt(comp_stream_mach)
                     * omega3
                     / 2
                 )
                 M3 += M3f - M3d
             except AttributeError:
                 pass
-        weightB = Kt @ Vector([0, 0, -total_mass * self.env.gravity(z)])
+        weightB = Kt @ Vector([0, 0, -total_mass * self.env.gravity.get_value_opt(z)])
         T00 = total_mass * r_CM
-        T03 = (
-            2 * total_mass_dot * (Vector([0, 0, r_NOZ]) - r_CM)
-            - 2 * total_mass * r_CM_dot
-        )
+        T03 = 2 * total_mass_dot * (r_NOZ - r_CM) - 2 * total_mass * r_CM_dot
         T04 = (
-            self.rocket.motor.thrust(t) * Vector([0, 0, 1])
+            Vector([0, 0, self.rocket.motor.thrust.get_value_opt(t)])
             - total_mass * r_CM_ddot
             - 2 * total_mass_dot * r_CM_dot
-            + total_mass_ddot * (Vector([0, 0, r_NOZ]) - r_CM)
+            + total_mass_ddot * (r_NOZ - r_CM)
         )
         T05 = total_mass_dot * S_nozzle - I_dot
 
@@ -1985,34 +1811,8 @@ def u_dot_generalized(self, t, u, post_processing=False):
         u_dot = [*r_dot, *v_dot, *e_dot, *w_dot]
 
         if post_processing:
-            # Accelerations
-            self.ax_list.append([t, v_dot[0]])
-            self.ay_list.append([t, v_dot[1]])
-            self.az_list.append([t, v_dot[2]])
-            self.alpha1_list.append([t, w_dot[0]])
-            self.alpha2_list.append([t, w_dot[1]])
-            self.alpha3_list.append([t, w_dot[2]])
-            # Dynamics variables
-            self.R1_list.append([t, R1])
-            self.R2_list.append([t, R2])
-            self.R3_list.append([t, R3])
-            self.M1_list.append([t, M1])
-            self.M2_list.append([t, M2])
-            self.M3_list.append([t, M3])
-            # Atmospheric Conditions
-            self.wind_velocity_x_list.append(
-                [t, self.env.wind_velocity_x.get_value_opt(z)]
-            )
-            self.wind_velocity_y_list.append(
-                [t, self.env.wind_velocity_y.get_value_opt(z)]
-            )
-            self.density_list.append([t, self.env.density.get_value_opt(z)])
-            self.dynamic_viscosity_list.append(
-                [t, self.env.dynamic_viscosity.get_value_opt(z)]
-            )
-            self.pressure_list.append([t, self.env.pressure.get_value_opt(z)])
-            self.speed_of_sound_list.append(
-                [t, self.env.speed_of_sound.get_value_opt(z)]
+            self.__post_processed_variables.append(
+                [t, *v_dot, *w_dot, R1, R2, R3, M1, M2, M3]
             )
 
         return u_dot
@@ -2040,34 +1840,42 @@ def u_dot_parachute(self, t, u, post_processing=False):
             e0dot, e1dot, e2dot, e3dot, alpha1, alpha2, alpha3].
 
         """
-        # Parachute data
-        cd_s = self.parachute_cd_s
-        ka = 1
-        R = 1.5
-        rho = self.env.density.get_value_opt(u[2])
-        to = 1.2
-        ma = ka * rho * (4 / 3) * np.pi * R**3
-        mp = self.rocket.dry_mass
-        eta = 1
-        Rdot = (6 * R * (1 - eta) / (1.2**6)) * (
-            (1 - eta) * t**5 + eta * (to**3) * (t**2)
-        )
-        Rdot = 0
         # Get relevant state data
-        x, y, z, vx, vy, vz, e0, e1, e2, e3, omega1, omega2, omega3 = u
-        # Get wind data
+        z, vx, vy, vz = u[2:6]
+
+        # Get atmospheric data
+        rho = self.env.density.get_value_opt(z)
         wind_velocity_x = self.env.wind_velocity_x.get_value_opt(z)
         wind_velocity_y = self.env.wind_velocity_y.get_value_opt(z)
-        free_stream_speed = (
-            (wind_velocity_x - vx) ** 2 + (wind_velocity_y - vy) ** 2 + (vz) ** 2
-        ) ** 0.5
+
+        # Get Parachute data
+        cd_s = self.parachute_cd_s
+
+        # Get the mass of the rocket
+        mp = self.rocket.dry_mass
+
+        # Define constants
+        ka = 1  # Added mass coefficient (depends on parachute's porosity)
+        R = 1.5  # Parachute radius
+        # to = 1.2
+        # eta = 1
+        # Rdot = (6 * R * (1 - eta) / (1.2**6)) * (
+        #     (1 - eta) * t**5 + eta * (to**3) * (t**2)
+        # )
+        # Rdot = 0
+
+        # Calculate added mass
+        ma = ka * rho * (4 / 3) * np.pi * R**3
+
+        # Calculate freestream speed
         freestream_x = vx - wind_velocity_x
         freestream_y = vy - wind_velocity_y
         freestream_z = vz
+        free_stream_speed = (freestream_x**2 + freestream_y**2 + freestream_z**2) ** 0.5
+
         # Determine drag force
-        pseudoD = (
-            -0.5 * rho * cd_s * free_stream_speed - ka * rho * 4 * np.pi * (R**2) * Rdot
-        )
+        pseudoD = -0.5 * rho * cd_s * free_stream_speed
+        # pseudoD = pseudoD - ka * rho * 4 * np.pi * (R**2) * Rdot
         Dx = pseudoD * freestream_x
         Dy = pseudoD * freestream_y
         Dz = pseudoD * freestream_z
@@ -2078,35 +1886,10 @@ def u_dot_parachute(self, t, u, post_processing=False):
         u_dot = [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
 
         if post_processing:
-            # Accelerations
-            self.ax_list.append([t, ax])
-            self.ay_list.append([t, ay])
-            self.az_list.append([t, az])
-            self.alpha1_list.append([t, 0])
-            self.alpha2_list.append([t, 0])
-            self.alpha3_list.append([t, 0])
-            # Dynamics variables
-            self.R1_list.append([t, Dx])
-            self.R2_list.append([t, Dy])
-            self.R3_list.append([t, Dz])
-            self.M1_list.append([t, 0])
-            self.M2_list.append([t, 0])
-            self.M3_list.append([t, 0])
-            # Atmospheric Conditions
-            self.wind_velocity_x_list.append(
-                [t, self.env.wind_velocity_x.get_value_opt(z)]
-            )
-            self.wind_velocity_y_list.append(
-                [t, self.env.wind_velocity_y.get_value_opt(z)]
-            )
-            self.density_list.append([t, self.env.density.get_value_opt(z)])
-            self.dynamic_viscosity_list.append(
-                [t, self.env.dynamic_viscosity.get_value_opt(z)]
-            )
-            self.pressure_list.append([t, self.env.pressure.get_value_opt(z)])
-            self.speed_of_sound_list.append(
-                [t, self.env.speed_of_sound.get_value_opt(z)]
+            self.__post_processed_variables.append(
+                [t, ax, ay, az, 0, 0, 0, Dx, Dy, Dz, 0, 0, 0]
             )
+
         return [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
 
     @cached_property
@@ -2114,11 +1897,29 @@ def solution_array(self):
         """Returns solution array of the rocket flight."""
         return np.array(self.solution)
 
+    @property
+    def function_evaluations_per_time_step(self):
+        """Get the number of function evaluations per time step. This method
+        calculates the difference between consecutive function evaluations
+        during numerical integration and returns it as a list.
+
+        Returns
+        -------
+        list
+            The list of differences in function evaluations per time step.
+        """
+        return np.diff(self.function_evaluations).tolist()
+
     @cached_property
     def time(self):
         """Returns time array from solution."""
         return self.solution_array[:, 0]
 
+    @cached_property
+    def time_steps(self):
+        """Returns time step array."""
+        return np.diff(self.time)
+
     def get_solution_at_time(self, t, atol=1e-3):
         """Returns the solution state vector at a given time. If the time is
         not found in the solution, the closest time is used and a warning is
@@ -2226,51 +2027,51 @@ def w3(self):
     @funcify_method("Time (s)", "Ax (m/s²)", "spline", "zero")
     def ax(self):
         """Rocket x acceleration as a Function of time."""
-        return self.retrieve_acceleration_arrays[0]
+        return self.__evaluate_post_process[:, [0, 1]]
 
     @funcify_method("Time (s)", "Ay (m/s²)", "spline", "zero")
     def ay(self):
         """Rocket y acceleration as a Function of time."""
-        return self.retrieve_acceleration_arrays[1]
+        return self.__evaluate_post_process[:, [0, 2]]
 
     @funcify_method("Time (s)", "Az (m/s²)", "spline", "zero")
     def az(self):
         """Rocket z acceleration as a Function of time."""
-        return self.retrieve_acceleration_arrays[2]
+        return self.__evaluate_post_process[:, [0, 3]]
 
     @funcify_method("Time (s)", "α1 (rad/s²)", "spline", "zero")
     def alpha1(self):
         """Rocket angular acceleration α1 as a Function of time."""
-        return self.retrieve_acceleration_arrays[3]
+        return self.__evaluate_post_process[:, [0, 4]]
 
     @funcify_method("Time (s)", "α2 (rad/s²)", "spline", "zero")
     def alpha2(self):
         """Rocket angular acceleration α2 as a Function of time."""
-        return self.retrieve_acceleration_arrays[4]
+        return self.__evaluate_post_process[:, [0, 5]]
 
     @funcify_method("Time (s)", "α3 (rad/s²)", "spline", "zero")
     def alpha3(self):
         """Rocket angular acceleration α3 as a Function of time."""
-        return self.retrieve_acceleration_arrays[5]
+        return self.__evaluate_post_process[:, [0, 6]]
 
     # Process third type of outputs - Temporary values
     @funcify_method("Time (s)", "R1 (N)", "spline", "zero")
     def R1(self):
         """Aerodynamic force along the first axis that is perpendicular to the
         rocket's axis of symmetry as a Function of time."""
-        return self.retrieve_temporary_values_arrays[0]
+        return self.__evaluate_post_process[:, [0, 7]]
 
     @funcify_method("Time (s)", "R2 (N)", "spline", "zero")
     def R2(self):
         """Aerodynamic force along the second axis that is perpendicular to the
         rocket's axis of symmetry as a Function of time."""
-        return self.retrieve_temporary_values_arrays[1]
+        return self.__evaluate_post_process[:, [0, 8]]
 
     @funcify_method("Time (s)", "R3 (N)", "spline", "zero")
     def R3(self):
         """Aerodynamic force along the rocket's axis of symmetry as a
         Function of time."""
-        return self.retrieve_temporary_values_arrays[2]
+        return self.__evaluate_post_process[:, [0, 9]]
 
     @funcify_method("Time (s)", "M1 (Nm)", "spline", "zero")
     def M1(self):
@@ -2278,54 +2079,51 @@ def M1(self):
         perpendicular to the rocket's axis of symmetry as a Function of
         time.
         """
-        return self.retrieve_temporary_values_arrays[3]
+        return self.__evaluate_post_process[:, [0, 10]]
 
     @funcify_method("Time (s)", "M2 (Nm)", "spline", "zero")
     def M2(self):
         """Aerodynamic bending moment in the same direction as the axis that is
         perpendicular to the rocket's axis of symmetry as a Function
         of time."""
-        return self.retrieve_temporary_values_arrays[4]
+        return self.__evaluate_post_process[:, [0, 11]]
 
     @funcify_method("Time (s)", "M3 (Nm)", "spline", "zero")
     def M3(self):
         """Aerodynamic bending moment in the same direction as the rocket's
         axis of symmetry as a Function of time."""
-        return self.retrieve_temporary_values_arrays[5]
+        return self.__evaluate_post_process[:, [0, 12]]
 
     @funcify_method("Time (s)", "Pressure (Pa)", "spline", "constant")
     def pressure(self):
         """Air pressure felt by the rocket as a Function of time."""
-        return self.retrieve_temporary_values_arrays[6]
+        return [(t, self.env.pressure.get_value_opt(z)) for t, z in self.z]
 
     @funcify_method("Time (s)", "Density (kg/m³)", "spline", "constant")
     def density(self):
         """Air density felt by the rocket as a Function of time."""
-        return self.retrieve_temporary_values_arrays[7]
+        return [(t, self.env.density.get_value_opt(z)) for t, z in self.z]
 
     @funcify_method("Time (s)", "Dynamic Viscosity (Pa s)", "spline", "constant")
     def dynamic_viscosity(self):
         """Air dynamic viscosity felt by the rocket as a Function of
         time."""
-        return self.retrieve_temporary_values_arrays[8]
+        return [(t, self.env.dynamic_viscosity.get_value_opt(z)) for t, z in self.z]
 
     @funcify_method("Time (s)", "Speed of Sound (m/s)", "spline", "constant")
     def speed_of_sound(self):
-        """Speed of sound in the air felt by the rocket as a Function
-        of time."""
-        return self.retrieve_temporary_values_arrays[9]
+        """Speed of sound in the air felt by the rocket as a Function of time."""
+        return [(t, self.env.speed_of_sound.get_value_opt(z)) for t, z in self.z]
 
     @funcify_method("Time (s)", "Wind Velocity X (East) (m/s)", "spline", "constant")
     def wind_velocity_x(self):
-        """Wind velocity in the X direction (east) as a Function of
-        time."""
-        return self.retrieve_temporary_values_arrays[10]
+        """Wind velocity in the X direction (east) as a Function of time."""
+        return [(t, self.env.wind_velocity_x.get_value_opt(z)) for t, z in self.z]
 
     @funcify_method("Time (s)", "Wind Velocity Y (North) (m/s)", "spline", "constant")
     def wind_velocity_y(self):
-        """Wind velocity in the y direction (north) as a Function of
-        time."""
-        return self.retrieve_temporary_values_arrays[11]
+        """Wind velocity in the y direction (north) as a Function of time."""
+        return [(t, self.env.wind_velocity_y.get_value_opt(z)) for t, z in self.z]
 
     # Process fourth type of output - values calculated from previous outputs
 
@@ -2336,6 +2134,11 @@ def speed(self):
         """Rocket speed, or velocity magnitude, as a Function of time."""
         return (self.vx**2 + self.vy**2 + self.vz**2) ** 0.5
 
+    @property
+    def out_of_rail_velocity(self):
+        """Velocity at which the rocket leaves the launch rail."""
+        return self.speed.get_value_opt(self.out_of_rail_time)
+
     @cached_property
     def max_speed_time(self):
         """Time at which the rocket reaches its maximum speed."""
@@ -2345,7 +2148,7 @@ def max_speed_time(self):
     @cached_property
     def max_speed(self):
         """Maximum speed reached by the rocket."""
-        return self.speed(self.max_speed_time)
+        return self.speed.get_value_opt(self.max_speed_time)
 
     # Accelerations
     @funcify_method("Time (s)", "acceleration Magnitude (m/s²)")
@@ -2371,7 +2174,7 @@ def max_acceleration_power_on_time(self):
     @cached_property
     def max_acceleration_power_on(self):
         """Maximum acceleration reached by the rocket during motor burn."""
-        return self.acceleration(self.max_acceleration_power_on_time)
+        return self.acceleration.get_value_opt(self.max_acceleration_power_on_time)
 
     @cached_property
     def max_acceleration_power_off_time(self):
@@ -2388,7 +2191,7 @@ def max_acceleration_power_off_time(self):
     @cached_property
     def max_acceleration_power_off(self):
         """Maximum acceleration reached by the rocket after motor burn."""
-        return self.acceleration(self.max_acceleration_power_off_time)
+        return self.acceleration.get_value_opt(self.max_acceleration_power_off_time)
 
     @cached_property
     def max_acceleration_time(self):
@@ -2441,13 +2244,13 @@ def attitude_angle(self):
         attitude_angle = (180 / np.pi) * np.arctan2(
             self.attitude_vector_z[:, 1], horizontal_attitude_proj[:, 1]
         )
-        attitude_angle = np.column_stack([self.time, attitude_angle])
-        return attitude_angle
+        return np.column_stack([self.time, attitude_angle])
 
     # Lateral Attitude Angle
     @funcify_method("Time (s)", "Lateral Attitude Angle (°)")
     def lateral_attitude_angle(self):
         """Rocket lateral attitude angle as a Function of time."""
+        # TODO: complex method, it should be defined elsewhere.
         lateral_vector_angle = (np.pi / 180) * (self.heading - 90)
         lateral_vector_x = np.sin(lateral_vector_angle)
         lateral_vector_y = np.cos(lateral_vector_angle)
@@ -2503,24 +2306,17 @@ def theta(self):
     @funcify_method("Time (s)", "Freestream Velocity X (m/s)", "spline", "constant")
     def stream_velocity_x(self):
         """Freestream velocity X component as a Function of time."""
-        stream_velocity_x = np.column_stack(
-            (self.time, self.wind_velocity_x[:, 1] - self.vx[:, 1])
-        )
-        return stream_velocity_x
+        return np.column_stack((self.time, self.wind_velocity_x[:, 1] - self.vx[:, 1]))
 
     @funcify_method("Time (s)", "Freestream Velocity Y (m/s)", "spline", "constant")
     def stream_velocity_y(self):
         """Freestream velocity Y component as a Function of time."""
-        stream_velocity_y = np.column_stack(
-            (self.time, self.wind_velocity_y[:, 1] - self.vy[:, 1])
-        )
-        return stream_velocity_y
+        return np.column_stack((self.time, self.wind_velocity_y[:, 1] - self.vy[:, 1]))
 
     @funcify_method("Time (s)", "Freestream Velocity Z (m/s)", "spline", "constant")
     def stream_velocity_z(self):
         """Freestream velocity Z component as a Function of time."""
-        stream_velocity_z = np.column_stack((self.time, -self.vz[:, 1]))
-        return stream_velocity_z
+        return np.column_stack((self.time, -self.vz[:, 1]))
 
     @funcify_method("Time (s)", "Freestream Speed (m/s)", "spline", "constant")
     def free_stream_speed(self):
@@ -2536,7 +2332,7 @@ def free_stream_speed(self):
     @cached_property
     def apogee_freestream_speed(self):
         """Freestream speed at apogee in m/s."""
-        return self.free_stream_speed(self.apogee_time)
+        return self.free_stream_speed.get_value_opt(self.apogee_time)
 
     # Mach Number
     @funcify_method("Time (s)", "Mach Number", "spline", "zero")
@@ -2553,7 +2349,7 @@ def max_mach_number_time(self):
     @cached_property
     def max_mach_number(self):
         """Maximum Mach number."""
-        return self.mach_number(self.max_mach_number_time)
+        return self.mach_number.get_value_opt(self.max_mach_number_time)
 
     # Stability Margin
     @cached_property
@@ -2565,7 +2361,7 @@ def max_stability_margin_time(self):
     @cached_property
     def max_stability_margin(self):
         """Maximum stability margin."""
-        return self.stability_margin(self.max_stability_margin_time)
+        return self.stability_margin.get_value_opt(self.max_stability_margin_time)
 
     @cached_property
     def min_stability_margin_time(self):
@@ -2576,7 +2372,7 @@ def min_stability_margin_time(self):
     @cached_property
     def min_stability_margin(self):
         """Minimum stability margin."""
-        return self.stability_margin(self.min_stability_margin_time)
+        return self.stability_margin.get_value_opt(self.min_stability_margin_time)
 
     @property
     def initial_stability_margin(self):
@@ -2586,7 +2382,7 @@ def initial_stability_margin(self):
         -------
         float
         """
-        return self.stability_margin(self.time[0])
+        return self.stability_margin.get_value_opt(self.time[0])
 
     @property
     def out_of_rail_stability_margin(self):
@@ -2596,7 +2392,7 @@ def out_of_rail_stability_margin(self):
         -------
         float
         """
-        return self.stability_margin(self.out_of_rail_time)
+        return self.stability_margin.get_value_opt(self.out_of_rail_time)
 
     # Reynolds Number
     @funcify_method("Time (s)", "Reynolds Number", "spline", "zero")
@@ -2615,7 +2411,7 @@ def max_reynolds_number_time(self):
     @cached_property
     def max_reynolds_number(self):
         """Maximum Reynolds number."""
-        return self.reynolds_number(self.max_reynolds_number_time)
+        return self.reynolds_number.get_value_opt(self.max_reynolds_number_time)
 
     # Dynamic Pressure
     @funcify_method("Time (s)", "Dynamic Pressure (Pa)", "spline", "zero")
@@ -2632,7 +2428,7 @@ def max_dynamic_pressure_time(self):
     @cached_property
     def max_dynamic_pressure(self):
         """Maximum dynamic pressure."""
-        return self.dynamic_pressure(self.max_dynamic_pressure_time)
+        return self.dynamic_pressure.get_value_opt(self.max_dynamic_pressure_time)
 
     # Total Pressure
     @funcify_method("Time (s)", "Total Pressure (Pa)", "spline", "zero")
@@ -2648,7 +2444,7 @@ def max_total_pressure_time(self):
     @cached_property
     def max_total_pressure(self):
         """Maximum total pressure."""
-        return self.total_pressure(self.max_total_pressure_time)
+        return self.total_pressure.get_value_opt(self.max_total_pressure_time)
 
     # Dynamics functions and variables
 
@@ -2691,7 +2487,7 @@ def translational_energy(self):
         # Redefine total_mass time grid to allow for efficient Function algebra
         total_mass = deepcopy(self.rocket.total_mass)
         total_mass.set_discrete_based_on_model(self.vz)
-        translational_energy = 0.5 * total_mass * (self.vx**2 + self.vy**2 + self.vz**2)
+        translational_energy = 0.5 * total_mass * (self.speed**2)
         return translational_energy
 
     @funcify_method("Time (s)", "Kinetic Energy (J)", "spline", "zero")
@@ -2705,16 +2501,15 @@ def potential_energy(self):
         """Potential energy as a Function of time in relation to sea
         level."""
         # Constants
-        GM = 3.986004418e14
+        GM = 3.986004418e14  # TODO: this constant should come from Environment.
         # Redefine total_mass time grid to allow for efficient Function algebra
         total_mass = deepcopy(self.rocket.total_mass)
         total_mass.set_discrete_based_on_model(self.z)
-        potential_energy = (
+        return (
             GM
             * total_mass
             * (1 / (self.z + self.env.earth_radius) - 1 / self.env.earth_radius)
         )
-        return potential_energy
 
     # Total Mechanical Energy
     @funcify_method("Time (s)", "Mechanical Energy (J)", "spline", "constant")
@@ -2754,7 +2549,7 @@ def angle_of_attack(self):
             for i in self.time
         ]
         # Define freestream speed list
-        free_stream_speed = [self.free_stream_speed(i) for i in self.time]
+        free_stream_speed = [self.free_stream_speed.get_value_opt(i) for i in self.time]
         free_stream_speed = np.nan_to_num(free_stream_speed)
 
         # Normalize dot product
@@ -2766,9 +2561,8 @@ def angle_of_attack(self):
 
         # Calculate angle of attack and convert to degrees
         angle_of_attack = np.rad2deg(np.arccos(dot_product_normalized))
-        angle_of_attack = np.column_stack([self.time, angle_of_attack])
 
-        return angle_of_attack
+        return np.column_stack([self.time, angle_of_attack])
 
     # Frequency response and stability variables
     @funcify_method("Frequency (Hz)", "ω1 Fourier Amplitude", "spline", "zero")
@@ -2916,6 +2710,7 @@ def latitude(self):
         )
         return np.column_stack((self.time, latitude))
 
+    # TODO: haversine should be defined in tools.py so we just invoke it in here.
     @funcify_method("Time (s)", "Longitude (°)", "linear", "constant")
     def longitude(self):
         """Rocket longitude coordinate, in degrees, as a Function of
@@ -2938,121 +2733,6 @@ def longitude(self):
 
         return np.column_stack((self.time, longitude))
 
-    @cached_property
-    def __retrieve_arrays(self):
-        """post processing function to retrieve arrays from the integration
-        scheme and store them in lists for further analysis.
-
-        Returns
-        -------
-        temp_values: list
-            List containing the following arrays: ``ax`` , ``ay`` , ``az`` ,
-            ``alpha1`` , ``alpha2`` , ``alpha3`` , ``R1`` , ``R2`` , ``R3`` ,
-            ``M1`` , ``M2`` , ``M3`` , ``pressure`` , ``density`` ,
-            ``dynamic_viscosity`` , ``speed_of_sound`` , ``wind_velocity_x`` ,
-            ``wind_velocity_y``.
-        """
-        # Go through each time step and calculate forces and atmospheric values
-        # Get flight phases
-        for phase_index, phase in self.time_iterator(self.FlightPhases):
-            init_time = phase.t
-            final_time = self.FlightPhases[phase_index + 1].t
-            current_derivative = phase.derivative
-            # Call callback functions
-            for callback in phase.callbacks:
-                callback(self)
-            # find index of initial and final time of phase in solution array
-            init_time_index = find_closest(self.time, init_time)
-            final_time_index = find_closest(self.time, final_time) + 1
-            # Loop through time steps solution array
-            for step in self.solution[init_time_index:final_time_index]:
-                if init_time != step[0] or (
-                    init_time == self.t_initial and step[0] == self.t_initial
-                ):
-                    # Call derivatives in post processing mode
-                    current_derivative(step[0], step[1:], post_processing=True)
-
-        temp_values = [
-            self.ax_list,
-            self.ay_list,
-            self.az_list,
-            self.alpha1_list,
-            self.alpha2_list,
-            self.alpha3_list,
-            self.R1_list,
-            self.R2_list,
-            self.R3_list,
-            self.M1_list,
-            self.M2_list,
-            self.M3_list,
-            self.pressure_list,
-            self.density_list,
-            self.dynamic_viscosity_list,
-            self.speed_of_sound_list,
-            self.wind_velocity_x_list,
-            self.wind_velocity_y_list,
-        ]
-
-        return temp_values
-
-    @cached_property
-    def retrieve_acceleration_arrays(self):
-        """Retrieve acceleration arrays from the integration scheme
-
-        Returns
-        -------
-        ax_list: list
-            acceleration in x direction
-        ay_list: list
-            acceleration in y direction
-        az_list: list
-            acceleration in z direction
-        alpha1_list: list
-            angular acceleration in x direction
-        alpha2_list: list
-            angular acceleration in y direction
-        alpha3_list: list
-            angular acceleration in z direction
-        """
-        return self.__retrieve_arrays[:6]
-
-    @cached_property
-    def retrieve_temporary_values_arrays(self):
-        """Retrieve temporary values arrays from the integration scheme.
-        Currently, the following temporary values are retrieved: ``R1`` , ``R2``
-        ``R3`` , ``M1`` , ``M2`` , ``M3`` , ``pressure`` , ``density`` ,
-        ``dynamic_viscosity`` , ``speed_of_sound`` .
-
-        Returns
-        -------
-        self.R1_list: list
-            R1 values.
-        self.R2_list: list
-            R2 values.
-        self.R3_list: list
-            R3 values are the aerodynamic force values in the rocket's axis
-            direction.
-        self.M1_list: list
-            M1 values.
-        self.M2_list: list
-            Aerodynamic bending moment in e2 direction at each time step.
-        self.M3_list: list
-            Aerodynamic bending moment in e3 direction at each time step.
-        self.pressure_list: list
-            Air pressure at each time step.
-        self.density_list: list
-            Air density at each time step.
-        self.dynamic_viscosity_list: list
-            Dynamic viscosity at each time step.
-        self.speed_of_sound_list: list
-            Speed of sound at each time step.
-        self.wind_velocity_x_list: list
-            Wind velocity in x direction at each time step.
-        self.wind_velocity_y_list: list
-            Wind velocity in y direction at each time step.
-        """
-        return self.__retrieve_arrays[6:]
-
     def get_controller_observed_variables(self):
         """Retrieve the observed variables related to air brakes from the
         controllers. If there is only one set of observed variables, it is
@@ -3068,7 +2748,7 @@ def get_controller_observed_variables(self):
         )
 
     @cached_property
-    def __calculate_rail_button_forces(self):
+    def __calculate_rail_button_forces(self):  # TODO: complex method.
         """Calculate the forces applied to the rail buttons while rocket is
         still on the launch rail. It will return 0 if no rail buttons are
         defined.
@@ -3155,7 +2835,7 @@ def __calculate_rail_button_forces(self):
             rail_button2_shear_force,
         )
 
-    def _calculate_pressure_signal(self):
+    def __transform_pressure_signals_lists_to_functions(self):
         """Calculate the pressure signal from the pressure sensor.
         It creates a signal_function attribute in the parachute object.
         Parachute works as a subclass of Rocket class.
@@ -3166,23 +2846,47 @@ def _calculate_pressure_signal(self):
         """
         # Transform parachute sensor feed into functions
         for parachute in self.rocket.parachutes:
+            # TODO: these Functions do not need input validation
             parachute.clean_pressure_signal_function = Function(
                 parachute.clean_pressure_signal,
                 "Time (s)",
                 "Pressure - Without Noise (Pa)",
                 "linear",
             )
-            parachute.noisy_pressure_signal_function = Function(
-                parachute.noisy_pressure_signal,
-                "Time (s)",
-                "Pressure - With Noise (Pa)",
-                "linear",
-            )
             parachute.noise_signal_function = Function(
                 parachute.noise_signal, "Time (s)", "Pressure Noise (Pa)", "linear"
             )
+            parachute.noisy_pressure_signal_function = (
+                parachute.clean_pressure_signal_function
+                + parachute.noise_signal_function
+            )
 
-        return None
+    @cached_property
+    def __evaluate_post_process(self):
+        """Evaluate all post-processing variables by running the simulation
+        again but with the post-processing flag set to True.
+
+        Returns
+        -------
+        np.array
+            An array containing all post-processed variables evaluated at each
+            time step. Each element of the array is a list containing:
+            [t, ax, ay, az, alpha1, alpha2, alpha3, R1, R2, R3, M1, M2, M3]
+        """
+        self.__post_processed_variables = []
+        for phase_index, phase in self.time_iterator(self.flight_phases):
+            init_time = phase.t
+            final_time = self.flight_phases[phase_index + 1].t
+            current_derivative = phase.derivative
+            for callback in phase.callbacks:
+                callback(self)
+            for step in self.solution:
+                if init_time < step[0] <= final_time or (
+                    init_time == self.t_initial and step[0] == self.t_initial
+                ):
+                    current_derivative(step[0], step[1:], post_processing=True)
+
+        return np.array(self.__post_processed_variables)
 
     def post_process(self, interpolation="spline", extrapolation="natural"):
         """This method is **deprecated** and is only kept here for backwards
@@ -3198,12 +2902,10 @@ def post_process(self, interpolation="spline", extrapolation="natural"):
         -------
         None
         """
-        # Register post processing
+        # TODO: add a deprecation warning maybe?
         self.post_processed = True
 
-        return None
-
-    def calculate_stall_wind_velocity(self, stall_angle):
+    def calculate_stall_wind_velocity(self, stall_angle):  # TODO: move to utilities
         """Function to calculate the maximum wind velocity before the angle of
         attack exceeds a desired angle, at the instant of departing rail launch.
         Can be helpful if you know the exact stall angle of all aerodynamics
@@ -3214,15 +2916,15 @@ def calculate_stall_wind_velocity(self, stall_angle):
         stall_angle : float
             Angle, in degrees, for which you would like to know the maximum wind
             speed before the angle of attack exceeds it
+
         Return
         ------
         None
         """
         v_f = self.out_of_rail_velocity
 
-        # Convert angle to radians
-        theta = self.inclination * 3.14159265359 / 180
-        stall_angle = stall_angle * 3.14159265359 / 180
+        theta = np.radians(self.inclination)
+        stall_angle = np.radians(stall_angle)
 
         c = (math.cos(stall_angle) ** 2 - math.cos(theta) ** 2) / math.sin(
             stall_angle
@@ -3236,16 +2938,13 @@ def calculate_stall_wind_velocity(self, stall_angle):
             ** 0.5
         ) / 2
 
-        # Convert stall_angle to degrees
-        stall_angle = stall_angle * 180 / np.pi
+        stall_angle = np.degrees(stall_angle)
         print(
             "Maximum wind velocity at Rail Departure time before angle"
             + f" of attack exceeds {stall_angle:.3f}°: {w_v:.3f} m/s"
         )
 
-        return None
-
-    def export_pressures(self, file_name, time_step):
+    def export_pressures(self, file_name, time_step):  # TODO: move out
         """Exports the pressure experienced by the rocket during the flight to
         an external file, the '.csv' format is recommended, as the columns will
         be separated by commas. It can handle flights with or without
@@ -3277,12 +2976,12 @@ def export_pressures(self, file_name, time_step):
             if len(self.rocket.parachutes) == 0:
                 print("No parachutes in the rocket, saving static pressure.")
                 for t in time_points:
-                    file.write(f"{t:f}, {self.pressure(t):.5f}\n")
+                    file.write(f"{t:f}, {self.pressure.get_value_opt(t):.5f}\n")
             else:
                 for parachute in self.rocket.parachutes:
                     for t in time_points:
-                        p_cl = parachute.clean_pressure_signal_function(t)
-                        p_ns = parachute.noisy_pressure_signal_function(t)
+                        p_cl = parachute.clean_pressure_signal_function.get_value_opt(t)
+                        p_ns = parachute.noisy_pressure_signal_function.get_value_opt(t)
                         file.write(f"{t:f}, {p_cl:.5f}, {p_ns:.5f}\n")
                     # We need to save only 1 parachute data
                     break
@@ -3310,6 +3009,7 @@ class attributes which are instances of the Function class. Usage
             will be exported. Otherwise, linear interpolation is carried out to
             calculate values at the desired time steps. Example: 0.001.
         """
+        # TODO: we should move this method to outside of class.
 
         # Fast evaluation for the most basic scenario
         if time_step is None and len(variables) == 0:
@@ -3368,13 +3068,13 @@ class attributes which are instances of the Function class. Usage
                 try:
                     obj = getattr(self.__class__, variable)
                     variable_function = obj.__get__(self, self.__class__)
-                except AttributeError:
+                except AttributeError as exc:
                     raise AttributeError(
-                        "Variable '{}' not found in Flight class".format(variable)
-                    )
+                        f"Variable '{variable}' not found in Flight class"
+                    ) from exc
             variable_points = variable_function(time_points)
             exported_matrix += [variable_points]
-            exported_header += ", " + variable_function.__outputs__[0]
+            exported_header += f", {variable_function.__outputs__[0]}"
 
         exported_matrix = np.array(exported_matrix).T  # Fix matrix orientation
 
@@ -3413,7 +3113,7 @@ def export_sensor_data(self, file_name, sensor=None):
             json.dump(data_dict, file)
         print("Sensor data exported to", file_name)
 
-    def export_kml(
+    def export_kml(  # TODO: should be moved out of this class.
         self,
         file_name="trajectory.kml",
         time_step=None,
@@ -3461,27 +3161,33 @@ def export_kml(
         # Open kml file with simplekml library
         kml = simplekml.Kml(open=1)
         trajectory = kml.newlinestring(name="Rocket Trajectory - Powered by RocketPy")
-        coords = []
+
         if altitude_mode == "relativetoground":
             # In this mode the elevation data will be the Above Ground Level
             # elevation. Only works properly if the ground level is similar to
             # a plane, i.e. it might not work well if the terrain has mountains
-            for t in time_points:
-                coords.append(
-                    (
-                        self.longitude(t),
-                        self.latitude(t),
-                        self.altitude(t),
-                    )
+            coords = [
+                (
+                    self.longitude.get_value_opt(t),
+                    self.latitude.get_value_opt(t),
+                    self.altitude.get_value_opt(t),
                 )
+                for t in time_points
+            ]
             trajectory.coords = coords
             trajectory.altitudemode = simplekml.AltitudeMode.relativetoground
         else:  # altitude_mode == 'absolute'
             # In this case the elevation data will be the Above Sea Level elevation
             # Ensure you use the correct value on self.env.elevation, otherwise
             # the trajectory path can be offset from ground
-            for t in time_points:
-                coords.append((self.longitude(t), self.latitude(t), self.z(t)))
+            coords = [
+                (
+                    self.longitude.get_value_opt(t),
+                    self.latitude.get_value_opt(t),
+                    self.z.get_value_opt(t),
+                )
+                for t in time_points
+            ]
             trajectory.coords = coords
             trajectory.altitudemode = simplekml.AltitudeMode.absolute
         # Modify style of trajectory linestring
@@ -3493,29 +3199,13 @@ def export_kml(
         kml.save(file_name)
         print("File ", file_name, " saved with success!")
 
-        return None
-
     def info(self):
-        """Prints out a summary of the data available about the Flight.
-
-        Returns
-        -------
-        None
-        """
+        """Prints out a summary of the data available about the Flight."""
         self.prints.all()
-        return None
 
     def all_info(self):
-        """Prints out all data and graphs available about the Flight.
-
-        Returns
-        -------
-        None
-        """
-
-        # Print a summary of data about the flight
+        """Prints out all data and graphs available about the Flight."""
         self.info()
-
         self.plots.all()
 
         return None
@@ -3555,7 +3245,7 @@ def display_warning(self, *messages):
             """A simple function to print a warning message."""
             print("WARNING:", *messages)
 
-        def add(self, flight_phase, index=None):
+        def add(self, flight_phase, index=None):  # TODO: quite complex method
             """Add a flight phase to the list. It will be inserted in the
             correct position, according to its initial time. If no index is
             provided, it will be appended to the end of the list. If by any
@@ -3712,6 +3402,8 @@ class FlightPhase:
                 A flag indicating whether to clear the solution after the phase.
             """
 
+            # TODO: add a "name" optional argument to the FlightPhase. Really helps.
+
             def __init__(self, t, derivative=None, callbacks=None, clear=True):
                 self.t = t
                 self.derivative = derivative
@@ -3721,17 +3413,19 @@ def __init__(self, t, derivative=None, callbacks=None, clear=True):
                 self.TimeNodes = None
 
             def __repr__(self):
-                if self.derivative is None:
-                    return "{Initial Time: " + str(self.t) + " | Derivative: None}"
+                name = "None" if self.derivative is None else self.derivative.__name__
                 return (
-                    "{Initial Time: "
-                    + str(self.t)
-                    + " | Derivative: "
-                    + self.derivative.__name__
-                    + "}"
+                    f"<FlightPhase(t= {self.t}, derivative= {name}, "
+                    f"callbacks= {self.callbacks}, clear= {self.clear})>"
                 )
 
     class TimeNodes:
+        """TimeNodes is a class that stores all the time nodes of a simulation.
+        It is meant to work like a python list, but it has some additional
+        methods that are useful for the simulation. Them items stored in are
+        TimeNodes object are instances of the TimeNode class.
+        """
+
         def __init__(self, init_list=[]):
             self.list = init_list[:]
 
@@ -3751,20 +3445,19 @@ def add_node(self, t, parachutes, controllers, sensors):
             self.list.append(self.TimeNode(t, parachutes, controllers, sensors))
 
         def add_parachutes(self, parachutes, t_init, t_end):
-            # Iterate over parachutes
             for parachute in parachutes:
                 # Calculate start of sampling time nodes
-                pcDt = 1 / parachute.sampling_rate
+                sampling_interval = 1 / parachute.sampling_rate
                 parachute_node_list = [
-                    self.TimeNode(i * pcDt, [parachute], [], [])
+                    self.TimeNode(i * sampling_interval, [parachute], [], [])
                     for i in range(
-                        math.ceil(t_init / pcDt), math.floor(t_end / pcDt) + 1
+                        math.ceil(t_init / sampling_interval),
+                        math.floor(t_end / sampling_interval) + 1,
                     )
                 ]
                 self.list += parachute_node_list
 
         def add_controllers(self, controllers, t_init, t_end):
-            # Iterate over controllers
             for controller in controllers:
                 # Calculate start of sampling time nodes
                 controller_time_step = 1 / controller.sampling_rate
@@ -3794,31 +3487,55 @@ def add_sensors(self, sensors, t_init, t_end):
                 self.list += sensor_node_list
 
         def sort(self):
-            self.list.sort(key=(lambda node: node.t))
+            self.list.sort()
 
         def merge(self):
-            # Initialize temporary list
-            self.tmp_list = [self.list[0]]
-            self.copy_list = self.list[1:]
-            # Iterate through all other time nodes
-            for node in self.copy_list:
-                # If there is already another node with similar time: merge
-                if abs(node.t - self.tmp_list[-1].t) < 1e-7:
-                    self.tmp_list[-1].parachutes += node.parachutes
-                    self.tmp_list[-1].callbacks += node.callbacks
-                    self.tmp_list[-1]._component_sensors += node._component_sensors
-                    self.tmp_list[-1]._controllers += node._controllers
-                # Add new node to tmp list if there is none with the same time
-                else:
-                    self.tmp_list.append(node)
-            # Save tmp list to permanent
-            self.list = self.tmp_list
+            """Merge all the time nodes that have the same time. This is made to
+            avoid multiple evaluations of the same time node. This method does
+            not guarantee the order of the nodes in the list, so it is
+            recommended to sort the list before or after using this method.
+            """
+            tmp_dict = {}
+            for node in self.list:
+                time = round(node.t, 7)
+                try:
+                    # Try to access the node and merge if it exists
+                    tmp_dict[time].parachutes += node.parachutes
+                    tmp_dict[time].callbacks += node.callbacks
+                    tmp_dict[-1]._component_sensors += node._component_sensors
+                    tmp_dict[-1]._controllers += node._controllers
+                except KeyError:
+                    # If the node does not exist, add it to the dictionary
+                    tmp_dict[time] = node
+            self.list = list(tmp_dict.values())
 
         def flush_after(self, index):
             del self.list[index + 1 :]
 
         class TimeNode:
+            """TimeNode is a class that represents a time node in the time
+            nodes list. It stores the time, the parachutes and the controllers
+            that are active at that time. This class is supposed to work
+            exclusively within the TimeNodes class.
+            """
+
             def __init__(self, t, parachutes, controllers, sensors):
+                """Create a TimeNode object.
+
+                Parameters
+                ----------
+                t : float
+                    Initial time of the time node.
+                parachutes : list[Parachute]
+                    List containing all the parachutes that should be evaluated
+                    at this time node.
+                controllers : list[_Controller]
+                    List containing all the controllers that should be evaluated
+                    at this time node.
+                sensors : list[ComponentSensor]
+                    List containing all the sensors that should be evaluated
+                    at this time node.
+                """
                 self.t = t
                 self.parachutes = parachutes
                 self.callbacks = []
@@ -3827,13 +3544,28 @@ def __init__(self, t, parachutes, controllers, sensors):
 
             def __repr__(self):
                 return (
-                    "{Initial Time: "
-                    + str(self.t)
-                    + " | Parachutes: "
-                    + str(len(self.parachutes))
-                    + " | Controllers: "
-                    + str(len(self._controllers))
-                    + " | Sensors: "
-                    + str(len(self._component_sensors))
-                    + "}"
+                    f"<TimeNode("
+                    f"t: {self.t}, "
+                    f"parachutes: {len(self.parachutes)}, "
+                    f"controllers: {len(self._controllers)}, "
+                    f"sensors: {len(self._component_sensors)})>"
                 )
+
+            def __lt__(self, other):
+                """Allows the comparison of two TimeNode objects based on their
+                initial time. This is particularly useful for sorting a list of
+                TimeNode objects.
+
+                Parameters
+                ----------
+                other : TimeNode
+                    Another TimeNode object to compare with.
+
+                Returns
+                -------
+                bool
+                    True if the initial time of the current TimeNode is less
+                    than the initial time of the other TimeNode, False
+                    otherwise.
+                """
+                return self.t < other.t
diff --git a/rocketpy/simulation/monte_carlo.py b/rocketpy/simulation/monte_carlo.py
new file mode 100644
index 000000000..5bc8dcef9
--- /dev/null
+++ b/rocketpy/simulation/monte_carlo.py
@@ -0,0 +1,876 @@
+"""
+Monte Carlo Simulation Module for RocketPy
+
+This module defines the `MonteCarlo` class, which is used to perform Monte Carlo
+simulations of rocket flights. The Monte Carlo simulation is a powerful tool for 
+understanding the variability and uncertainty in the performance of rocket flights 
+by running multiple simulations with varied input parameters.
+
+Notes
+-----
+This module is still under active development, and some features or attributes may 
+change in future versions. Users are encouraged to check for updates and read the 
+latest documentation.
+"""
+
+import json
+import warnings
+from time import process_time, time
+
+import numpy as np
+import simplekml
+
+from rocketpy._encoders import RocketPyEncoder
+from rocketpy.plots.monte_carlo_plots import _MonteCarloPlots
+from rocketpy.prints.monte_carlo_prints import _MonteCarloPrints
+from rocketpy.simulation.flight import Flight
+from rocketpy.tools import (
+    generate_monte_carlo_ellipses,
+    generate_monte_carlo_ellipses_coordinates,
+)
+
+# TODO: Create evolution plots to analyze convergence
+
+
+class MonteCarlo:
+    """Class to run a Monte Carlo simulation of a rocket flight.
+
+    Attributes
+    ----------
+    filename : str
+        Represents the initial part of the export filenames or the .txt file
+        containing the outputs of a previous simulation.
+    environment : StochasticEnvironment
+        The stochastic environment object to be iterated over.
+    rocket : StochasticRocket
+        The stochastic rocket object to be iterated over.
+    flight : StochasticFlight
+        The stochastic flight object to be iterated over.
+    export_list : list
+        The list of variables to export at each simulation.
+    inputs_log : list
+        List of dictionaries with the inputs used in each simulation.
+    outputs_log : list
+        List of dictionaries with the outputs of each simulation.
+    errors_log : list
+        List of dictionaries with the errors of each simulation.
+    num_of_loaded_sims : int
+        Number of simulations loaded from output_file currently being used.
+    results : dict
+        Monte Carlo analysis results organized in a dictionary where the keys
+        are the names of the saved attributes, and the values are lists with all
+        the result numbers of the respective attributes.
+    processed_results : dict
+        Dictionary with the mean and standard deviation of each parameter
+        available in the results.
+    prints : _MonteCarloPrints
+        Object with methods to print information about the Monte Carlo simulation.
+        Use help(MonteCarlo.prints) for more information.
+    plots : _MonteCarloPlots
+        Object with methods to plot information about the Monte Carlo simulation.
+        Use help(MonteCarlo.plots) for more information.
+    number_of_simulations : int
+        Number of simulations to be run.
+    total_wall_time : float
+        The total elapsed real-world time from the start to the end of the
+        simulation, including all waiting times and delays.
+    total_cpu_time : float
+        The total CPU time spent running the simulation, excluding the time
+        spent waiting for I/O operations or other processes to complete.
+    """
+
+    def __init__(self, filename, environment, rocket, flight, export_list=None):
+        """
+        Initialize a MonteCarlo object.
+
+        Parameters
+        ----------
+        filename : str
+            Represents the initial part of the export filenames or the .txt file
+            containing the outputs of a previous simulation.
+        environment : StochasticEnvironment
+            The stochastic environment object to be iterated over.
+        rocket : StochasticRocket
+            The stochastic rocket object to be iterated over.
+        flight : StochasticFlight
+            The stochastic flight object to be iterated over.
+        export_list : list, optional
+            The list of variables to export. If None, the default list will be
+            used, which includes the following variables: `apogee`, `apogee_time`,
+            `apogee_x`, `apogee_y`, `t_final`, `x_impact`, `y_impact`,
+            `impact_velocity`, `initial_stability_margin`,
+            `out_of_rail_stability_margin`, `out_of_rail_time`,
+            `out_of_rail_velocity`, `max_mach_number`, `frontal_surface_wind`,
+            `lateral_surface_wind`. Default is None.
+
+        Returns
+        -------
+        None
+        """
+        warnings.warn(
+            "This class is still under testing and some attributes may be "
+            "changed in next versions",
+            UserWarning,
+        )
+
+        self.filename = filename
+        self.environment = environment
+        self.rocket = rocket
+        self.flight = flight
+        self.export_list = []
+        self.inputs_log = []
+        self.outputs_log = []
+        self.errors_log = []
+        self.num_of_loaded_sims = 0
+        self.results = {}
+        self.processed_results = {}
+        self.prints = _MonteCarloPrints(self)
+        self.plots = _MonteCarloPlots(self)
+        self._inputs_dict = {}
+        self._last_print_len = 0  # used to print on the same line
+
+        self.export_list = self.__check_export_list(export_list)
+
+        try:
+            self.import_inputs()
+        except FileNotFoundError:
+            self._input_file = f"{filename}.inputs.txt"
+
+        try:
+            self.import_outputs()
+        except FileNotFoundError:
+            self._output_file = f"{filename}.outputs.txt"
+
+        try:
+            self.import_errors()
+        except FileNotFoundError:
+            self._error_file = f"{filename}.errors.txt"
+
+    def simulate(self, number_of_simulations, append=False):
+        """
+        Runs the Monte Carlo simulation and saves all data.
+
+        Parameters
+        ----------
+        number_of_simulations : int
+            Number of simulations to be run, must be non-negative.
+        append : bool, optional
+            If True, the results will be appended to the existing files. If
+            False, the files will be overwritten. Default is False.
+
+        Returns
+        -------
+        None
+
+        Notes
+        -----
+        If you need to stop the simulations after starting them, you can
+        interrupt the process and the files will be saved with the results
+        until the last iteration. You can then load the results and continue
+        the simulation by running the ``simulate`` method again with the
+        same number of simulations and setting `append=True`.
+
+        Important
+        ---------
+        If you use `append=False` and the files already exist, they will be
+        overwritten. Make sure to save the files with the results before
+        running the simulation again with `append=False`.
+        """
+        # Create data files for inputs, outputs and error logging
+        open_mode = "a" if append else "w"
+        input_file = open(self._input_file, open_mode, encoding="utf-8")
+        output_file = open(self._output_file, open_mode, encoding="utf-8")
+        error_file = open(self._error_file, open_mode, encoding="utf-8")
+
+        # initialize counters
+        self.number_of_simulations = number_of_simulations
+        self.__iteration_count = self.num_of_loaded_sims if append else 0
+        self.__start_time = time()
+        self.__start_cpu_time = process_time()
+
+        # Begin display
+        print("Starting Monte Carlo analysis", end="\r")
+
+        try:
+            while self.__iteration_count < self.number_of_simulations:
+                self.__run_single_simulation(input_file, output_file)
+        except KeyboardInterrupt:
+            print("Keyboard Interrupt, files saved.")
+            error_file.write(json.dumps(self._inputs_dict, cls=RocketPyEncoder) + "\n")
+            self.__close_files(input_file, output_file, error_file)
+        except Exception as error:
+            print(f"Error on iteration {self.__iteration_count}: {error}")
+            error_file.write(json.dumps(self._inputs_dict, cls=RocketPyEncoder) + "\n")
+            self.__close_files(input_file, output_file, error_file)
+            raise error
+        finally:
+            self.total_cpu_time = process_time() - self.__start_cpu_time
+            self.total_wall_time = time() - self.__start_time
+
+        self.__terminate_simulation(input_file, output_file, error_file)
+
+    # Auxiliary methods
+
+    def __run_single_simulation(self, input_file, output_file):
+        """
+        Runs a single simulation and saves the inputs and outputs to the
+        respective files.
+
+        Parameters
+        ----------
+        input_file : str
+            The file object to write the inputs.
+        output_file : str
+            The file object to write the outputs.
+
+        Returns
+        -------
+        None
+        """
+        self.__iteration_count += 1
+
+        monte_carlo_flight = Flight(
+            rocket=self.rocket.create_object(),
+            environment=self.environment.create_object(),
+            rail_length=self.flight._randomize_rail_length(),
+            inclination=self.flight._randomize_inclination(),
+            heading=self.flight._randomize_heading(),
+            initial_solution=self.flight.initial_solution,
+            terminate_on_apogee=self.flight.terminate_on_apogee,
+        )
+
+        self._inputs_dict = dict(
+            item
+            for d in [
+                self.environment.last_rnd_dict,
+                self.rocket.last_rnd_dict,
+                self.flight.last_rnd_dict,
+            ]
+            for item in d.items()
+        )
+
+        self.__export_flight_data(
+            flight=monte_carlo_flight,
+            inputs_dict=self._inputs_dict,
+            input_file=input_file,
+            output_file=output_file,
+        )
+
+        average_time = (process_time() - self.__start_cpu_time) / self.__iteration_count
+        estimated_time = int(
+            (self.number_of_simulations - self.__iteration_count) * average_time
+        )
+        self.__reprint(
+            f"Current iteration: {self.__iteration_count:06d} | "
+            f"Average Time per Iteration: {average_time:.3f} s | "
+            f"Estimated time left: {estimated_time} s",
+            end="\r",
+            flush=True,
+        )
+
+    def __close_files(self, input_file, output_file, error_file):
+        """
+        Closes all the files.
+
+        Parameters
+        ----------
+        input_file : str
+            The file object to write the inputs.
+        output_file : str
+            The file object to write the outputs.
+        error_file : str
+            The file object to write the errors.
+
+        Returns
+        -------
+        None
+        """
+        input_file.close()
+        output_file.close()
+        error_file.close()
+
+    def __terminate_simulation(self, input_file, output_file, error_file):
+        """
+        Terminates the simulation, closes the files and prints the results.
+
+        Parameters
+        ----------
+        input_file : str
+            The file object to write the inputs.
+        output_file : str
+            The file object to write the outputs.
+        error_file : str
+            The file object to write the errors.
+
+        Returns
+        -------
+        None
+        """
+        final_string = (
+            f"Completed {self.__iteration_count} iterations. Total CPU time: "
+            f"{process_time() - self.__start_cpu_time:.1f} s. Total wall time: "
+            f"{time() - self.__start_time:.1f} s\n"
+        )
+
+        self.__reprint(final_string + "Saving results.", flush=True)
+
+        # close files to guarantee saving
+        self.__close_files(input_file, output_file, error_file)
+
+        # resave the files on self and calculate post simulation attributes
+        self.input_file = f"{self.filename}.inputs.txt"
+        self.output_file = f"{self.filename}.outputs.txt"
+        self.error_file = f"{self.filename}.errors.txt"
+
+        print(f"Results saved to {self._output_file}")
+
+    def __export_flight_data(
+        self,
+        flight,
+        inputs_dict,
+        input_file,
+        output_file,
+    ):
+        """
+        Exports the flight data to the respective files.
+
+        Parameters
+        ----------
+        flight : Flight
+            The Flight object containing the flight data.
+        inputs_dict : dict
+            Dictionary containing the inputs used in the simulation.
+        input_file : str
+            The file object to write the inputs.
+        output_file : str
+            The file object to write the outputs.
+
+        Returns
+        -------
+        None
+        """
+        results = {
+            export_item: getattr(flight, export_item)
+            for export_item in self.export_list
+        }
+
+        input_file.write(json.dumps(inputs_dict, cls=RocketPyEncoder) + "\n")
+        output_file.write(json.dumps(results, cls=RocketPyEncoder) + "\n")
+
+    def __check_export_list(self, export_list):
+        """
+        Checks if the export_list is valid and returns a valid list. If no
+        export_list is provided, the standard list is used.
+
+        Parameters
+        ----------
+        export_list : list
+            The list of variables to export. If None, the default list will be
+            used. Default is None.
+
+        Returns
+        -------
+        list
+            Validated export list.
+        """
+        standard_output = set(
+            {
+                "apogee",
+                "apogee_time",
+                "apogee_x",
+                "apogee_y",
+                "t_final",
+                "x_impact",
+                "y_impact",
+                "impact_velocity",
+                "initial_stability_margin",
+                "out_of_rail_stability_margin",
+                "out_of_rail_time",
+                "out_of_rail_velocity",
+                "max_mach_number",
+                "frontal_surface_wind",
+                "lateral_surface_wind",
+            }
+        )
+        # NOTE: exportables needs to be updated with Flight numerical properties
+        #       example: You added the property 'inclination' to Flight, so you may
+        #       need to add it to exportables as well. But don't add other types.
+        exportables = set(
+            {
+                "inclination",
+                "heading",
+                "effective1rl",
+                "effective2rl",
+                "out_of_rail_time",
+                "out_of_rail_time_index",
+                "out_of_rail_state",
+                "out_of_rail_velocity",
+                "rail_button1_normal_force",
+                "max_rail_button1_normal_force",
+                "rail_button1_shear_force",
+                "max_rail_button1_shear_force",
+                "rail_button2_normal_force",
+                "max_rail_button2_normal_force",
+                "rail_button2_shear_force",
+                "max_rail_button2_shear_force",
+                "out_of_rail_static_margin",
+                "apogee_state",
+                "apogee_time",
+                "apogee_x",
+                "apogee_y",
+                "apogee",
+                "x_impact",
+                "y_impact",
+                "z_impact",
+                "impact_velocity",
+                "impact_state",
+                "parachute_events",
+                "apogee_freestream_speed",
+                "final_static_margin",
+                "frontal_surface_wind",
+                "initial_static_margin",
+                "lateral_surface_wind",
+                "max_acceleration",
+                "max_acceleration_time",
+                "max_dynamic_pressure_time",
+                "max_dynamic_pressure",
+                "max_mach_number_time",
+                "max_mach_number",
+                "max_reynolds_number_time",
+                "max_reynolds_number",
+                "max_speed_time",
+                "max_speed",
+                "max_total_pressure_time",
+                "max_total_pressure",
+                "t_final",
+            }
+        )
+        if export_list:
+            for attr in set(export_list):
+                if not isinstance(attr, str):
+                    raise TypeError("Variables in export_list must be strings.")
+
+                # Checks if attribute is not valid
+                if attr not in exportables:
+                    raise ValueError(
+                        f"Attribute '{attr}' can not be exported. Check export_list."
+                    )
+        else:
+            # No export list provided, using default list instead.
+            export_list = standard_output
+
+        return export_list
+
+    def __reprint(self, msg, end="\n", flush=False):
+        """
+        Prints a message on the same line as the previous one and replaces the
+        previous message with the new one, deleting the extra characters from
+        the previous message.
+
+        Parameters
+        ----------
+        msg : str
+            Message to be printed.
+        end : str, optional
+            String appended after the message. Default is a new line.
+        flush : bool, optional
+            If True, the output is flushed. Default is False.
+
+        Returns
+        -------
+        None
+        """
+        len_msg = len(msg)
+        if len_msg < self._last_print_len:
+            msg += " " * (self._last_print_len - len_msg)
+        else:
+            self._last_print_len = len_msg
+
+        print(msg, end=end, flush=flush)
+
+    # Properties and setters
+
+    @property
+    def input_file(self):
+        """String representing the filepath of the input file"""
+        return self._input_file
+
+    @input_file.setter
+    def input_file(self, value):
+        """
+        Setter for input_file. Sets/updates inputs_log.
+
+        Parameters
+        ----------
+        value : str
+            The filepath of the input file.
+
+        Returns
+        -------
+        None
+        """
+        self._input_file = value
+        self.set_inputs_log()
+
+    @property
+    def output_file(self):
+        """String representing the filepath of the output file"""
+        return self._output_file
+
+    @output_file.setter
+    def output_file(self, value):
+        """
+        Setter for output_file. Sets/updates outputs_log, num_of_loaded_sims,
+        results, and processed_results.
+
+        Parameters
+        ----------
+        value : str
+            The filepath of the output file.
+
+        Returns
+        -------
+        None
+        """
+        self._output_file = value
+        self.set_outputs_log()
+        self.set_num_of_loaded_sims()
+        self.set_results()
+        self.set_processed_results()
+
+    @property
+    def error_file(self):
+        """String representing the filepath of the error file"""
+        return self._error_file
+
+    @error_file.setter
+    def error_file(self, value):
+        """
+        Setter for error_file. Sets/updates errors_log.
+
+        Parameters
+        ----------
+        value : str
+            The filepath of the error file.
+
+        Returns
+        -------
+        None
+        """
+        self._error_file = value
+        self.set_errors_log()
+
+    # Setters for post simulation attributes
+
+    def set_inputs_log(self):
+        """
+        Sets inputs_log from a file into an attribute for easy access.
+
+        Returns
+        -------
+        None
+        """
+        self.inputs_log = []
+        with open(self.input_file, mode="r", encoding="utf-8") as rows:
+            for line in rows:
+                self.inputs_log.append(json.loads(line))
+
+    def set_outputs_log(self):
+        """
+        Sets outputs_log from a file into an attribute for easy access.
+
+        Returns
+        -------
+        None
+        """
+        self.outputs_log = []
+        with open(self.output_file, mode="r", encoding="utf-8") as rows:
+            for line in rows:
+                self.outputs_log.append(json.loads(line))
+
+    def set_errors_log(self):
+        """
+        Sets errors_log from a file into an attribute for easy access.
+
+        Returns
+        -------
+        None
+        """
+        self.errors_log = []
+        with open(self.error_file, mode="r", encoding="utf-8") as errors:
+            for line in errors:
+                self.errors_log.append(json.loads(line))
+
+    def set_num_of_loaded_sims(self):
+        """
+        Determines the number of simulations loaded from output_file being
+        currently used.
+
+        Returns
+        -------
+        None
+        """
+        with open(self.output_file, mode="r", encoding="utf-8") as outputs:
+            self.num_of_loaded_sims = sum(1 for _ in outputs)
+
+    def set_results(self):
+        """
+        Monte Carlo results organized in a dictionary where the keys are the
+        names of the saved attributes, and the values are lists with all the
+        result numbers of the respective attributes. For instance:
+
+            .. code-block:: python
+
+                {
+                    'apogee': [1000, 1001, 1002, ...],
+                    'max_speed': [100, 101, 102, ...],
+                }
+
+        Returns
+        -------
+        None
+        """
+        self.results = {}
+        for result in self.outputs_log:
+            for key, value in result.items():
+                if key in self.results:
+                    self.results[key].append(value)
+                else:
+                    self.results[key] = [value]
+
+    def set_processed_results(self):
+        """
+        Creates a dictionary with the mean and standard deviation of each
+        parameter available in the results.
+
+        Returns
+        -------
+        None
+        """
+        self.processed_results = {}
+        for result, values in self.results.items():
+            mean = np.mean(values)
+            stdev = np.std(values)
+            self.processed_results[result] = (mean, stdev)
+
+    # Import methods
+
+    def import_outputs(self, filename=None):
+        """
+        Import Monte Carlo results from .txt file and save it into a dictionary.
+
+        Parameters
+        ----------
+        filename : str, optional
+            Name or directory path to the file to be imported. If none,
+            self.filename will be used.
+
+        Returns
+        -------
+        None
+
+        Notes
+        -----
+        Notice that you can import the outputs, inputs, and errors from the a
+        file without the need to run simulations. You can use previously saved
+        files to process analyze the results or to continue a simulation.
+        """
+        filepath = filename if filename else self.filename
+
+        try:
+            with open(f"{filepath}.outputs.txt", "r+", encoding="utf-8"):
+                self.output_file = f"{filepath}.outputs.txt"
+        except FileNotFoundError:
+            with open(filepath, "r+", encoding="utf-8"):
+                self.output_file = filepath
+
+        print(
+            f"A total of {self.num_of_loaded_sims} simulations results were "
+            f"loaded from the following output file: {self.output_file}\n"
+        )
+
+    def import_inputs(self, filename=None):
+        """
+        Import Monte Carlo inputs from .txt file and save it into a dictionary.
+
+        Parameters
+        ----------
+        filename : str, optional
+            Name or directory path to the file to be imported. If none,
+            self.filename will be used.
+
+        Returns
+        -------
+        None
+        """
+        filepath = filename if filename else self.filename
+
+        try:
+            with open(f"{filepath}.inputs.txt", "r+", encoding="utf-8"):
+                self.input_file = f"{filepath}.inputs.txt"
+        except FileNotFoundError:
+            with open(filepath, "r+", encoding="utf-8"):
+                self.input_file = filepath
+
+        print(f"The following input file was imported: {self.input_file}")
+
+    def import_errors(self, filename=None):
+        """
+        Import Monte Carlo errors from .txt file and save it into a dictionary.
+
+        Parameters
+        ----------
+        filename : str, optional
+            Name or directory path to the file to be imported. If none,
+            self.filename will be used.
+
+        Returns
+        -------
+        None
+        """
+        filepath = filename if filename else self.filename
+
+        try:
+            with open(f"{filepath}.errors.txt", "r+", encoding="utf-8"):
+                self.error_file = f"{filepath}.errors.txt"
+        except FileNotFoundError:
+            with open(filepath, "r+", encoding="utf-8"):
+                self.error_file = filepath
+        print(f"The following error file was imported: {self.error_file}")
+
+    def import_results(self, filename=None):
+        """
+        Import Monte Carlo results from .txt file and save it into a dictionary.
+
+        Parameters
+        ----------
+        filename : str, optional
+            Name or directory path to the file to be imported. If none,
+            self.filename will be used.
+
+        Returns
+        -------
+        None
+        """
+        filepath = filename if filename else self.filename
+
+        self.import_outputs(filename=filepath)
+        self.import_inputs(filename=filepath)
+        self.import_errors(filename=filepath)
+
+    # Export methods
+
+    def export_ellipses_to_kml(
+        self,
+        filename,
+        origin_lat,
+        origin_lon,
+        type="all",  # TODO: Don't use "type" as a parameter name, it's a reserved word
+        resolution=100,
+        color="ff0000ff",
+    ):
+        """
+        Generates a KML file with the ellipses on the impact point, which can be
+        used to visualize the dispersion ellipses on Google Earth.
+
+        Parameters
+        ----------
+        filename : str
+            Name to the KML exported file.
+        origin_lat : float
+            Latitude coordinate of Ellipses' geometric center, in degrees.
+        origin_lon : float
+            Longitude coordinate of Ellipses' geometric center, in degrees.
+        type : str, optional
+            Type of ellipses to be exported. Options are: 'all', 'impact' and
+            'apogee'. Default is 'all', it exports both apogee and impact ellipses.
+        resolution : int, optional
+            Number of points to be used to draw the ellipse. Default is 100. You
+            can increase this number to make the ellipse smoother, but it will
+            increase the file size. It is recommended to keep it below 1000.
+        color : str, optional
+            Color of the ellipse. Default is 'ff0000ff', which is red. Kml files
+            use an 8 digit HEX color format, see its docs.
+
+        Returns
+        -------
+        None
+
+        Notes
+        -----
+        - For further understanding on .kml files, see the official documentation:\
+            https://developers.google.com/kml/documentation/kmlreference
+        - You can set a pair of origin coordinates different from the launch site\
+            to visualize the dispersion as if the rocket was launched from that\
+            point. This is useful to visualize the dispersion ellipses in a\
+            different location. However, this approach is not accurate for\
+            large distances offsets, as the atmospheric conditions may change.
+        """
+        # TODO: The lat and lon should be optional arguments, we can get it from the env
+        (
+            impact_ellipses,
+            apogee_ellipses,
+            *_,
+        ) = generate_monte_carlo_ellipses(self.results)
+        outputs = []
+
+        if type == "all" or type == "impact":
+            outputs = outputs + generate_monte_carlo_ellipses_coordinates(
+                impact_ellipses, origin_lat, origin_lon, resolution=resolution
+            )
+
+        if type == "all" or type == "apogee":
+            outputs = outputs + generate_monte_carlo_ellipses_coordinates(
+                apogee_ellipses, origin_lat, origin_lon, resolution=resolution
+            )
+
+        # TODO: Non-iterable value output is used in an iterating context PylintE1133:
+        kml_data = [[(coord[1], coord[0]) for coord in output] for output in outputs]
+
+        kml = simplekml.Kml()
+
+        for i in range(len(outputs)):
+            if (type == "all" and i < 3) or (type == "impact"):
+                ellipse_name = "Impact \u03C3" + str(i + 1)
+            elif type == "all" and i >= 3:
+                ellipse_name = "Apogee \u03C3" + str(i - 2)
+            else:
+                ellipse_name = "Apogee \u03C3" + str(i + 1)
+
+            mult_ell = kml.newmultigeometry(name=ellipse_name)
+            mult_ell.newpolygon(
+                outerboundaryis=kml_data[i],
+                name="Ellipse " + str(i),
+            )
+            # Setting ellipse style
+            mult_ell.tessellate = 1
+            mult_ell.visibility = 1
+            mult_ell.style.linestyle.color = color
+            mult_ell.style.linestyle.width = 3
+            mult_ell.style.polystyle.color = simplekml.Color.changealphaint(
+                100, simplekml.Color.blue
+            )
+
+        kml.save(filename)
+
+    def info(self):
+        """
+        Print information about the Monte Carlo simulation.
+
+        Returns
+        -------
+        None
+        """
+        self.prints.all()
+
+    def all_info(self):
+        """
+        Print and plot information about the Monte Carlo simulation and its results.
+
+        Returns
+        -------
+        None
+        """
+        self.info()
+        self.plots.ellipses()
+        self.plots.all()
diff --git a/rocketpy/stochastic/__init__.py b/rocketpy/stochastic/__init__.py
new file mode 100644
index 000000000..692eca85f
--- /dev/null
+++ b/rocketpy/stochastic/__init__.py
@@ -0,0 +1,21 @@
+"""
+The rocketpy.stochastic module contains classes that are used to generate
+randomized objects based on the provided information. Each of the classes
+defined here represent one different rocketpy class plus the uncertainties
+associated with each input parameter.
+"""
+
+from .stochastic_aero_surfaces import (
+    StochasticEllipticalFins,
+    StochasticNoseCone,
+    StochasticRailButtons,
+    StochasticTail,
+    StochasticTrapezoidalFins,
+)
+from .stochastic_environment import StochasticEnvironment
+from .stochastic_flight import StochasticFlight
+from .stochastic_generic_motor import StochasticGenericMotor
+from .stochastic_model import StochasticModel
+from .stochastic_parachute import StochasticParachute
+from .stochastic_rocket import StochasticRocket
+from .stochastic_solid_motor import StochasticSolidMotor
diff --git a/rocketpy/stochastic/stochastic_aero_surfaces.py b/rocketpy/stochastic/stochastic_aero_surfaces.py
new file mode 100644
index 000000000..31c1e9efc
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_aero_surfaces.py
@@ -0,0 +1,434 @@
+"""
+Defines the StochasticNoseCone, StochasticTrapezoidalFins,
+StochasticEllipticalFins, StochasticTail and StochasticRailButtons classes.
+"""
+
+from rocketpy.rocket.aero_surface import (
+    EllipticalFins,
+    NoseCone,
+    RailButtons,
+    Tail,
+    TrapezoidalFins,
+)
+
+from .stochastic_model import StochasticModel
+
+
+class StochasticNoseCone(StochasticModel):
+    """The ``StochasticNoseCone`` class inherits from the StochasticModel. This
+    class is used to store a ``NoseCone`` object along with the uncertainty
+    of its parameters.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and
+    :class:`NoseCone <rocketpy.rocket.aero_surface.NoseCone>`
+
+    Attributes
+    ----------
+    object : NoseCone
+        NoseCone object to be used as a base for the Stochastic nose cone.
+    length : tuple, list, int, float
+        Length of the nose cone in meters.
+    kind : list[str]
+        List with a string representing the kind of nose cone.
+    base_radius : tuple, list, int, float
+        Nose cone base radius in meters.
+    bluffness : tuple, list, int, float
+        Bluffness of the nose cone.
+    rocket_radius : tuple, list, int, float
+        The reference rocket radius used for lift coefficient normalization, in
+        meters.
+    name : list[str]
+        List with the name of the NoseCone. This attribute can not be randomized.
+    """
+
+    # TODO: Never vary the kind of the nose cone. Fixed parameter.
+
+    def __init__(
+        self,
+        nosecone,
+        length=None,
+        kind=None,  # TODO: Never vary the kind of the nose cone. Fixed parameter.
+        base_radius=None,
+        bluffness=None,
+        rocket_radius=None,
+    ):
+        """Initializes the Stochastic Nose Cone class.
+
+        See Also
+        --------
+        See the :ref:`stochastic_model` and :ref:`nose_cone_class` for further
+        information.
+
+        Parameters
+        ----------
+        nosecone : NoseCone
+            NoseCone object to be used as a base for the Stochastic nose cone.
+        length : tuple, list, int, float
+            Length of the nose cone in meters.
+        base_radius : tuple, list, int, float
+            Nose cone base radius in meters.
+        bluffness : tuple, list, int, float
+            Bluffness of the nose cone.
+        rocket_radius : tuple, list, int, float
+            The reference rocket radius used for lift coefficient normalization,
+            in meters.
+        """
+        self._validate_kind(kind)
+        super().__init__(
+            nosecone,
+            length=length,
+            kind=kind,
+            base_radius=base_radius,
+            bluffness=bluffness,
+            rocket_radius=rocket_radius,
+            name=None,
+        )
+
+    def _validate_kind(self, kind):
+        """Validates the kind input. If the kind input argument is not None, it
+        must be a list of strings."""
+        if kind is not None:
+            # TODO: Never vary the kind of the nose cone. It is a fixed parameter.
+            assert isinstance(kind, list) and all(
+                isinstance(member, str) for member in kind
+            ), "`kind` must be a list of strings"
+
+    def create_object(self):
+        """Creates and returns a NoseCone object from the randomly generated
+        input arguments.
+
+        Returns
+        -------
+        nosecone : NoseCone
+            NoseCone object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return NoseCone(**generated_dict)
+
+
+class StochasticTrapezoidalFins(StochasticModel):
+    """A Stochastic Trapezoidal Fins class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and
+    :class:`TrapezoidalFins <rocketpy.TrapezoidalFins>`
+
+    Attributes
+    ----------
+    object : TrapezoidalFins
+        TrapezoidalFins object to be used for validation.
+    n : list[int]
+        List with an integer representing the number of fins. This attribute
+        can be randomized.
+    root_chord : tuple, list, int, float
+        Root chord of the fins in meters.
+    tip_chord : tuple, list, int, float
+        Tip chord of the fins in meters.
+    span : tuple, list, int, float
+        Span of the fins in meters.
+    rocket_radius : tuple, list, int, float
+        Rocket radius of the fins in meters.
+    cant_angle : tuple, list, int, float
+        Cant angle of the fins in degrees.
+    sweep_length : tuple, list, int, float
+        Sweep length of the fins in meters.
+    sweep_angle : tuple, list, int, float
+        Sweep angle of the fins in degrees.
+    airfoil : list
+        List of tuples in the form of (airfoil file path, airfoil name).
+    name : list[str]
+        List with the object name. This attribute can not be randomized.
+    """
+
+    def __init__(
+        self,
+        trapezoidal_fins,
+        n=None,  # TODO: Never vary the number of fins. It is a fixed parameter.
+        root_chord=None,
+        tip_chord=None,
+        span=None,
+        rocket_radius=None,
+        cant_angle=None,
+        sweep_length=None,
+        sweep_angle=None,
+        airfoil=None,
+    ):
+        """Initializes the Stochastic Trapezoidal Fins class.
+
+        See Also
+        --------
+        :ref:`stochastic_model`
+
+        Parameters
+        ----------
+        trapezoidal_fins : TrapezoidalFins
+            TrapezoidalFins object to be used for validation.
+        root_chord : tuple, list, int, float
+            Root chord of the fins in meters.
+        tip_chord : tuple, list, int, float
+            Tip chord of the fins in meters.
+        span : tuple, list, int, float
+            Span of the fins in meters.
+        rocket_radius : tuple, list, int, float
+            Rocket radius of the fins in meters.
+        cant_angle : tuple, list, int, float
+            Cant angle of the fins in degrees.
+        sweep_length : tuple, list, int, float
+            Sweep length of the fins in meters.
+        sweep_angle : tuple, list, int, float
+            Sweep angle of the fins in degrees.
+        airfoil : list[tuple]
+            List of tuples in the form of (airfoil file path, airfoil name).
+        """
+        # TODO: never vary the number of fins. It is a fixed parameter.
+        self._validate_positive_int_list("n", n)
+        self._validate_airfoil(airfoil)
+        super().__init__(
+            trapezoidal_fins,
+            n=n,
+            root_chord=root_chord,
+            tip_chord=tip_chord,
+            span=span,
+            rocket_radius=rocket_radius,
+            cant_angle=cant_angle,
+            sweep_length=sweep_length,
+            sweep_angle=sweep_angle,
+            airfoil=airfoil,
+            name=None,
+        )
+
+    def create_object(self):
+        """Creates and returns a TrapezoidalFins object from the randomly
+        generated input arguments.
+
+        Returns
+        -------
+        fins : TrapezoidalFins
+            TrapezoidalFins object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return TrapezoidalFins(**generated_dict)
+
+
+class StochasticEllipticalFins(StochasticModel):
+    """A Stochastic Elliptical Fins class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and
+    :class:`EllipticalFins <rocketpy.EllipticalFins>`
+
+    Attributes
+    ----------
+    object : EllipticalFins
+        EllipticalFins object to be used for validation.
+    n : list[int]
+        List with an integer representing the number of fins. This attribute
+        can be randomized.
+    root_chord : tuple, list, int, float
+        Root chord of the fins in meters.
+    span : tuple, list, int, float
+        Span of the fins in meters.
+    rocket_radius : tuple, list, int, float
+        Rocket radius of the fins in meters.
+    cant_angle : tuple, list, int, float
+        Cant angle of the fins in degrees.
+    airfoil : list
+        List of tuples in the form of (airfoil file path, airfoil name).
+    name : list[str]
+        List with the fins object name. This attribute can not be randomized.
+    """
+
+    def __init__(
+        self,
+        elliptical_fins=None,
+        n=None,
+        root_chord=None,
+        span=None,
+        rocket_radius=None,
+        cant_angle=None,
+        airfoil=None,
+    ):
+        """Initializes the Stochastic Elliptical Fins class.
+
+        See Also
+        --------
+        :ref:`stochastic_model`
+
+        Parameters
+        ----------
+        elliptical_fins : EllipticalFins
+            EllipticalFins object to be used for validation.
+        root_chord : tuple, list, int, float
+            Root chord of the fins in meters.
+        span : tuple, list, int, float
+            Span of the fins in meters.
+        rocket_radius : tuple, list, int, float
+            Rocket radius of the fins in meters.
+        cant_angle : tuple, list, int, float
+            Cant angle of the fins in degrees.
+        airfoil : list[tuple]
+            List of tuples in the form of (airfoil file path, airfoil name).
+        """
+        # TODO: never vary the number of fins. It is a fixed parameter.
+        self._validate_positive_int_list("n", n)
+        self._validate_airfoil(airfoil)
+        super().__init__(
+            elliptical_fins,
+            n=n,
+            root_chord=root_chord,
+            span=span,
+            rocket_radius=rocket_radius,
+            cant_angle=cant_angle,
+            airfoil=airfoil,
+            name=None,
+        )
+
+    def create_object(self):
+        """Creates and returns a EllipticalFins object from the randomly
+        generated input arguments.
+
+        Returns
+        -------
+        fins : EllipticalFins
+            EllipticalFins object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return EllipticalFins(**generated_dict)
+
+
+class StochasticTail(StochasticModel):
+    """A Stochastic Tail class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`Tail <rocketpy.Tail>`
+
+    Attributes
+    ----------
+    object : Tail
+        Tail object to be used for validation.
+    top_radius : tuple, list, int, float
+        Top radius of the tail in meters.
+    bottom_radius : tuple, list, int, float
+        Bottom radius of the tail in meters.
+    length : tuple, list, int, float
+        Length of the tail in meters.
+    rocket_radius : tuple, list, int, float
+        Rocket radius of the tail in meters.
+    name : list[str]
+        List with the name of the tail object. This cannot be randomized.
+    """
+
+    def __init__(
+        self,
+        tail,
+        top_radius=None,
+        bottom_radius=None,
+        length=None,
+        rocket_radius=None,
+    ):
+        """Initializes the Stochastic Tail class.
+
+        See Also
+        --------
+        :ref:`stochastic_model` and :class:`Tail <rocketpy.Tail>`
+
+        Parameters
+        ----------
+        tail : Tail
+            Tail object to be used for validation.
+        top_radius : tuple, list, int, float
+            Top radius of the tail in meters.
+        bottom_radius : tuple, list, int, float
+            Bottom radius of the tail in meters.
+        length : tuple, list, int, float
+            Length of the tail in meters.
+        rocket_radius : tuple, list, int, float
+            Rocket radius of the tail in meters.
+        """
+        super().__init__(
+            tail,
+            top_radius=top_radius,
+            bottom_radius=bottom_radius,
+            length=length,
+            rocket_radius=rocket_radius,
+            name=None,
+        )
+
+    def create_object(self):
+        """Creates and returns a Tail object from the randomly generated input
+        arguments.
+
+        Returns
+        -------
+        Tail
+            Tail object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return Tail(**generated_dict)
+
+
+class StochasticRailButtons(StochasticModel):
+    """A Stochastic RailButtons class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`RailButtons <rocketpy.rocket.RailButtons>`
+
+    Attributes
+    ----------
+    object : RailButtons
+        RailButtons object to be used for validation.
+    rail_buttons : list
+        List of RailButton objects.
+    buttons_distance : tuple, list, int, float
+        Distance between the buttons in meters.
+    angular_position : tuple, list, int, float
+        Angular position of the buttons in degrees.
+    name : list[str]
+        List with the name of the object. This attribute can not be randomized.
+    """
+
+    def __init__(
+        self,
+        rail_buttons=None,
+        buttons_distance=None,
+        angular_position=None,
+    ):
+        """Initializes the Stochastic RailButtons class.
+
+        See Also
+        --------
+        :ref:`stochastic_model`
+
+        Parameters
+        ----------
+        rail_buttons : RailButtons
+            RailButtons object to be used for validation.
+        buttons_distance : tuple, list, int, float
+            Distance between the buttons in meters.
+        angular_position : tuple, list, int, float
+            Angular position of the buttons in degrees.
+        """
+        super().__init__(
+            rail_buttons,
+            buttons_distance=buttons_distance,
+            angular_position=angular_position,
+            name=None,
+        )
+
+    def create_object(self):
+        """Creates and returns a RailButtons object from the randomly generated
+        input arguments.
+
+        Returns
+        -------
+        rail_buttons : RailButtons
+            RailButtons object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return RailButtons(**generated_dict)
diff --git a/rocketpy/stochastic/stochastic_environment.py b/rocketpy/stochastic/stochastic_environment.py
new file mode 100644
index 000000000..e36c19cf4
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_environment.py
@@ -0,0 +1,188 @@
+"""Defines the StochasticEnvironment class."""
+
+from .stochastic_model import StochasticModel
+
+
+class StochasticEnvironment(StochasticModel):
+    """A Stochastic Environment class that inherits from StochasticModel. This
+    class is used to store an Environment object and the uncertainty of their
+    parameters.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`Environment <rocketpy.environment.Environment>`
+
+    Attributes
+    ----------
+    object : Environment
+        Environment object to be used as a base for the stochastic model.
+    elevation : tuple, list, int, float
+        Elevation of the launch site in meters.
+    gravity : tuple, list, int, float
+        Gravitational acceleration in meters per second squared.
+    latitude : tuple, list, int, float
+        Latitude of the launch site in degrees.
+    longitude : tuple, list, int, float
+        Longitude of the launch site in degrees.
+    ensemble_member : list[int]
+        List of integers representing the ensemble members to be selected.
+    date : list[tuple]
+        List of dates, which are tuples of four elements
+        (year, month, day, hour). This attribute can not be randomized.
+    datum : list[str]
+        List of datum. This attribute can not be randomized.
+    timezone : list[pytz.timezone]
+        List with the timezone. This attribute can not be randomized.
+    wind_velocity_x_factor : tuple, list, int, float
+        Factor to multiply the wind velocity in the x direction. This should
+        be used only when the wind velocity is defined as a constant value.
+    wind_velocity_y_factor : tuple, list, int, float
+        Factor to multiply the wind velocity in the y direction. This should
+        be used only when the wind velocity is defined as a constant value.
+    """
+
+    def __init__(
+        self,
+        environment,
+        elevation=None,
+        gravity=None,
+        latitude=None,
+        longitude=None,
+        ensemble_member=None,
+        wind_velocity_x_factor=(1, 0),
+        wind_velocity_y_factor=(1, 0),
+    ):
+        """Initializes the Stochastic Environment class.
+
+        See Also
+        --------
+        :ref:`stochastic_model`
+
+        Parameters
+        ----------
+        environment : Environment
+            Environment object to be used for validation.
+        date : list, optional
+            List of dates, which are tuples of four elements
+            (year, month, day, hour).
+        elevation : int, float, tuple, list, optional
+            Elevation of the launch site in meters.
+        gravity : int, float, tuple, list, optional
+            Gravitational acceleration in meters per second squared.
+        latitude : int, float, tuple, list, optional
+            Latitude of the launch site in degrees.
+        longitude : int, float, tuple, list, optional
+            Longitude of the launch site in degrees.
+        ensemble_member : list, optional
+            List of integers representing the ensemble member to be selected.
+        wind_velocity_x_factor : tuple, list, int, float, optional
+            Factor to multiply the wind velocity in the x direction. This should
+            be used only when the wind velocity is defined as a constant value.
+        wind_velocity_y_factor : tuple, list, int, float, optional
+            Factor to multiply the wind velocity in the y direction. This should
+            be used only when the wind velocity is defined as a constant value.
+        """
+
+        super().__init__(
+            environment,
+            date=None,
+            elevation=elevation,
+            gravity=gravity,
+            latitude=latitude,
+            longitude=longitude,
+            ensemble_member=ensemble_member,
+            wind_velocity_x_factor=wind_velocity_x_factor,
+            wind_velocity_y_factor=wind_velocity_y_factor,
+            datum=None,
+            timezone=None,
+        )
+        self._validate_ensemble(ensemble_member, environment)
+
+    def _validate_ensemble(self, ensemble_member, environment):
+        """Validates the ensemble member input argument. If the environment
+        does not have ensemble members, the ensemble member input argument
+        must be None. If the environment has ensemble members, the ensemble
+        member input argument must be a list of positive integers, and the
+        integers must be in the range from 0 to the number of ensemble members
+        minus one.
+
+        Parameters
+        ----------
+        ensemble_member : list
+            List of integers representing the ensemble members to be selected.
+        environment : Environment
+            Environment object to be used for validation.
+
+        Returns
+        -------
+        None
+
+        Raises
+        ------
+        AssertionError
+            If the environment does not have ensemble members and the
+            ensemble_member input argument is not None.
+        """
+        valid_atmospheric_types = ["Ensemble", "Reanalysis"]
+
+        if environment.atmospheric_model_type not in valid_atmospheric_types:
+            if ensemble_member is not None:
+                raise AssertionError(
+                    f"Environment with {environment.atmospheric_model_type} "
+                    "does not have ensemble members"
+                )
+            return
+
+        if ensemble_member is not None:
+            assert isinstance(ensemble_member, list), "`ensemble_member` must be a list"
+            assert all(
+                isinstance(member, int) and member >= 0 for member in ensemble_member
+            ), "`ensemble_member` must be a list of positive integers"
+            assert (
+                0
+                <= min(ensemble_member)
+                <= max(ensemble_member)
+                < environment.num_ensemble_members
+            ), (
+                "`ensemble_member` must be in the range from 0 to "
+                + f"{environment.num_ensemble_members - 1}"
+            )
+            setattr(self, "ensemble_member", ensemble_member)
+        else:
+            # if no ensemble member is provided, get it from the environment
+            setattr(self, "ensemble_member", environment.ensemble_member)
+
+    def create_object(self):
+        """Creates an Environment object from the randomly generated input
+        arguments. The environment object is not recreated to avoid having to
+        reestablish the atmospheric model. Instead, attributes are changed
+        directly.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        Environment
+            Environment object with the randomly generated input arguments.
+
+        Notes
+        -----
+        This method is overwriting the create_object method from the
+        `StochasticModel` class to handle the special case of the ensemble
+        member attribute.
+        """
+        generated_dict = next(self.dict_generator())
+        for key, value in generated_dict.items():
+            # special case for ensemble member
+            # TODO: Generalize create_object() with a env.ensemble_member setter
+            if key == "ensemble_member":
+                self.object.select_ensemble_member(value)
+            else:
+                if "factor" in key:
+                    # get original attribute value and multiply by factor
+                    attribute_name = f"_{key.replace('_factor', '')}"
+                    value = getattr(self, attribute_name) * value
+                setattr(self.object, key, value)
+        return self.object
diff --git a/rocketpy/stochastic/stochastic_flight.py b/rocketpy/stochastic/stochastic_flight.py
new file mode 100644
index 000000000..df1c31d45
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_flight.py
@@ -0,0 +1,131 @@
+"""Defines the StochasticFlight class."""
+
+from rocketpy.simulation import Flight
+
+from .stochastic_model import StochasticModel
+
+
+class StochasticFlight(StochasticModel):
+    """A Stochastic Flight class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`Flight <rocketpy.simulation.Flight>`
+
+    Attributes
+    ----------
+    flight : Flight
+        The Flight object to be used as a base for the Stochastic flight.
+    rail_length : int, float, tuple, list
+        The rail length of the flight.
+    inclination : int, float, tuple, list
+        The inclination of the launch rail.
+    heading : int, float, tuple, list
+        The heading of the launch rail.
+    initial_solution : tuple, list
+        The initial solution of the flight. This is a tuple of 14 elements that
+        represent the initial conditions of the flight. This attribute can not
+        be randomized.
+    terminate_on_apogee : bool
+        Whether or not the flight should terminate on apogee. This attribute
+        can not be randomized.
+    """
+
+    def __init__(
+        self,
+        flight,
+        rail_length=None,
+        inclination=None,
+        heading=None,
+        initial_solution=None,
+        terminate_on_apogee=None,
+    ):
+        """Initializes the Stochastic Flight class.
+
+        See Also
+        --------
+        :ref:`stochastic_model` and :class:`Flight <rocketpy.simulation.Flight>`
+
+        Parameters
+        ----------
+        flight : Flight
+            The Flight object to be used as a base for the Stochastic flight.
+        rail_length : int, float, tuple, list, optional
+            The rail length of the flight.
+        inclination : int, float, tuple, list, optional
+            The inclination of the launch rail.
+        heading : int, float, tuple, list, optional
+            The heading of the launch rail.
+        initial_solution : tuple, list, optional
+            The initial solution of the flight. This is a tuple of 14 elements
+            that represent the initial conditions of the flight. This attribute
+            can not be randomized.
+        terminate_on_apogee : bool, optional
+            Whether or not the flight should terminate on apogee. This attribute
+            can not be randomized.
+        """
+        if terminate_on_apogee is not None:
+            assert isinstance(
+                terminate_on_apogee, bool
+            ), "`terminate_on_apogee` must be a boolean"
+        super().__init__(
+            flight,
+            rail_length=rail_length,
+            inclination=inclination,
+            heading=heading,
+        )
+
+        self.initial_solution = initial_solution
+        self.terminate_on_apogee = terminate_on_apogee
+
+    def _validate_initial_solution(self, initial_solution):
+        if initial_solution is not None:
+            if isinstance(initial_solution, (tuple, list)):
+                assert len(initial_solution) == 14, (
+                    "`initial_solution` must be a 14 element tuple, the "
+                    "elements are:\n t_initial, x_init, y_init, z_init, "
+                    "vx_init, vy_init, vz_init, e0_init, e1_init, e2_init, "
+                    "e3_init, w1Init, w2Init, w3Init"
+                )
+                assert all(
+                    isinstance(i, (int, float)) for i in initial_solution
+                ), "`initial_solution` must be a tuple of numbers"
+            else:
+                raise TypeError("`initial_solution` must be a tuple of numbers")
+
+    # TODO: these methods call dict_generator a lot of times unnecessarily
+    def _randomize_rail_length(self):
+        """Randomizes the rail length of the flight."""
+        generated_dict = next(self.dict_generator())
+        return generated_dict["rail_length"]
+
+    def _randomize_inclination(self):
+        """Randomizes the inclination of the flight."""
+        generated_dict = next(self.dict_generator())
+        return generated_dict["inclination"]
+
+    def _randomize_heading(self):
+        """Randomizes the heading of the flight."""
+        generated_dict = next(self.dict_generator())
+        return generated_dict["heading"]
+
+    def create_object(self):
+        """Creates and returns a Flight object from the randomly generated input
+        arguments.
+
+        Returns
+        -------
+        flight : Flight
+            Flight object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        # TODO: maybe we should use generated_dict["rail_length"] instead
+        return Flight(
+            environment=self.object.env,
+            rail_length=self._randomize_rail_length(),
+            rocket=self.object.rocket,
+            inclination=generated_dict["inclination"],
+            heading=generated_dict["heading"],
+            initial_solution=self.initial_solution,
+            terminate_on_apogee=self.terminate_on_apogee,
+        )
diff --git a/rocketpy/stochastic/stochastic_generic_motor.py b/rocketpy/stochastic/stochastic_generic_motor.py
new file mode 100644
index 000000000..bf8b79aa1
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_generic_motor.py
@@ -0,0 +1,193 @@
+"""Defines the StochasticGenericMotor class."""
+
+from rocketpy.motors import GenericMotor
+
+from .stochastic_motor_model import StochasticMotorModel
+
+
+class StochasticGenericMotor(StochasticMotorModel):
+    """A Stochastic Generic Motor class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and
+    :class:`GenericMotor <rocketpy.motors.GenericMotor>`
+
+    Attributes
+    ----------
+    object : GenericMotor
+        GenericMotor object to be used as a base for the stochastic model.
+    thrust_source : list
+        List of strings representing the thrust source to be selected.
+    total_impulse : int, float, tuple, list
+        Total impulse of the motor in newton seconds.
+    burn_start_time : int, float, tuple, list
+        Burn start time of the motor in seconds.
+    burn_out_time : int, float, tuple, list
+        Burn out time of the motor in seconds.
+    dry_mass : int, float, tuple, list
+        Dry mass of the motor in kilograms.
+    dry_I_11 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_22 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_33 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_12 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_13 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_23 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    chamber_radius : int, float, tuple, list
+        Chamber radius of the motor in meters.
+    chamber_height : int, float, tuple, list
+        Chamber height of the motor in meters.
+    chamber_position : int, float, tuple, list
+        Chamber position of the motor in meters.
+    nozzle_radius : int, float, tuple, list
+        Nozzle radius of the motor in meters.
+    nozzle_position : int, float, tuple, list
+        Nozzle position of the motor in meters.
+    center_of_dry_mass_position : int, float, tuple, list
+        Center of dry mass position of the motor in meters.
+    interpolation_method : str
+        Interpolation method to be used. This attribute can not be randomized.
+    coordinate_system_orientation : str
+        Coordinate system orientation to be used. This attribute can not be
+        randomized.
+    """
+
+    def __init__(
+        self,
+        generic_motor,
+        thrust_source=None,
+        total_impulse=None,
+        burn_start_time=None,
+        burn_out_time=None,
+        propellant_initial_mass=None,
+        dry_mass=None,
+        dry_inertia_11=None,
+        dry_inertia_22=None,
+        dry_inertia_33=None,
+        dry_inertia_12=None,
+        dry_inertia_13=None,
+        dry_inertia_23=None,
+        chamber_radius=None,
+        chamber_height=None,
+        chamber_position=None,
+        nozzle_radius=None,
+        nozzle_position=None,
+        center_of_dry_mass_position=None,
+    ):
+        """Initializes the Stochastic Generic Motor class.
+
+        See Also
+        --------
+        :ref:`stochastic_model` and
+        :class:`GenericMotor <rocketpy.motors.GenericMotor>`
+
+        Parameters
+        ----------
+        generic_motor : GenericMotor
+            GenericMotor object to be used for validation.
+        thrust_source : list, optional
+            List of strings representing the thrust source to be selected.
+        total_impulse : int, float, tuple, list, optional
+            Total impulse of the motor in newton seconds.
+        burn_start_time : int, float, tuple, list, optional
+            Burn start time of the motor in seconds.
+        burn_out_time : int, float, tuple, list, optional
+            Burn out time of the motor in seconds.
+        dry_mass : int, float, tuple, list, optional
+            Dry mass of the motor in kilograms.
+        dry_I_11 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_22 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_33 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_12 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_13 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_23 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        chamber_radius : int, float, tuple, list, optional
+            Chamber radius of the motor in meters.
+        chamber_height : int, float, tuple, list, optional
+            Chamber height of the motor in meters.
+        chamber_position : int, float, tuple, list, optional
+            Position of the motor chamber in meters.
+        nozzle_radius : int, float, tuple, list, optional
+            Nozzle radius of the motor in meters.
+        nozzle_position : int, float, tuple, list, optional
+            Nozzle position of the motor in meters.
+        center_of_dry_mass_position : int, float, tuple, list, optional
+            Center of dry mass position of the motor in meters.
+        """
+        super().__init__(
+            generic_motor,
+            thrust_source=thrust_source,
+            total_impulse=total_impulse,
+            burn_start_time=burn_start_time,
+            burn_out_time=burn_out_time,
+            propellant_initial_mass=propellant_initial_mass,
+            dry_mass=dry_mass,
+            dry_I_11=dry_inertia_11,
+            dry_I_22=dry_inertia_22,
+            dry_I_33=dry_inertia_33,
+            dry_I_12=dry_inertia_12,
+            dry_I_13=dry_inertia_13,
+            dry_I_23=dry_inertia_23,
+            chamber_radius=chamber_radius,
+            chamber_height=chamber_height,
+            chamber_position=chamber_position,
+            nozzle_radius=nozzle_radius,
+            nozzle_position=nozzle_position,
+            center_of_dry_mass_position=center_of_dry_mass_position,
+            interpolate=None,
+            coordinate_system_orientation=None,
+        )
+
+    def create_object(self):
+        """Creates a `GenericMotor` object from the randomly generated input
+        arguments.
+
+        Returns
+        -------
+        GenericMotor
+            GenericMotor object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return GenericMotor(
+            thrust_source=generated_dict["thrust_source"],
+            burn_time=(
+                generated_dict["burn_start_time"],
+                generated_dict["burn_out_time"],
+            ),
+            propellant_initial_mass=generated_dict["propellant_initial_mass"],
+            dry_mass=generated_dict["dry_mass"],
+            dry_inertia=(
+                generated_dict["dry_I_11"],
+                generated_dict["dry_I_22"],
+                generated_dict["dry_I_33"],
+                generated_dict["dry_I_12"],
+                generated_dict["dry_I_13"],
+                generated_dict["dry_I_23"],
+            ),
+            chamber_radius=generated_dict["chamber_radius"],
+            chamber_height=generated_dict["chamber_height"],
+            chamber_position=generated_dict["chamber_position"],
+            nozzle_radius=generated_dict["nozzle_radius"],
+            nozzle_position=generated_dict["nozzle_position"],
+            center_of_dry_mass_position=generated_dict["center_of_dry_mass_position"],
+            reshape_thrust_curve=(
+                (generated_dict["burn_start_time"], generated_dict["burn_out_time"]),
+                generated_dict["total_impulse"],
+            ),
+            coordinate_system_orientation=generated_dict[
+                "coordinate_system_orientation"
+            ],
+            interpolation_method=generated_dict["interpolate"],
+        )
diff --git a/rocketpy/stochastic/stochastic_model.py b/rocketpy/stochastic/stochastic_model.py
new file mode 100644
index 000000000..abb3472f2
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_model.py
@@ -0,0 +1,536 @@
+"""
+Defines the `StochasticModel` class, which is used as a base class for all other
+Stochastic classes.
+"""
+
+from random import choice
+
+import numpy as np
+
+from rocketpy.mathutils.function import Function
+
+from ..tools import get_distribution
+
+# TODO: Stop using assert in production code. Use exceptions instead.
+# TODO: Each validation method should have a test case.
+
+
+class StochasticModel:
+    """
+    Base class for all Stochastic classes. This class validates input arguments,
+    saves them as attributes, and generates a dictionary with randomly generated
+    input arguments.
+
+    See also
+    --------
+    :ref:`Working with Stochastic Models <stochastic_usage>`
+
+    Notes
+    -----
+    Please notice that the methods starting with an underscore are not meant to
+    be called directly by the user. These methods may receive breaking changes
+    without notice, so use them at your own risk.
+    """
+
+    # Arguments that are validated only in child classes
+    exception_list = [
+        "initial_solution",
+        "terminate_on_apogee",
+        "date",
+        "ensemble_member",
+    ]
+
+    def __init__(self, object, **kwargs):
+        """
+        Initialize the StochasticModel class with validated input arguments.
+
+        Parameters
+        ----------
+        object : object
+            The main object of the class.
+        **kwargs : dict
+            Dictionary of input arguments for the class. Valid argument types
+            include tuples, lists, ints, floats, or None. Arguments will be
+            validated and saved as class attributes in a specific format, which
+            is described in the
+            ":ref:`Working with Stochastic Models <stochastic_usage>`" page.
+
+        Raises
+        ------
+        AssertionError
+            If the input arguments do not conform to the specified formats.
+        """
+        # TODO: don't use "object" as a variable name, it's a built-in function.
+        #       We can simply change to "obj". Pylint W0622
+
+        self.object = object
+        self.last_rnd_dict = {}
+
+        # TODO: This code block is too complex. Refactor it.
+        for input_name, input_value in kwargs.items():
+            if input_name not in self.exception_list:
+                if input_value is not None:
+                    if "factor" in input_name:
+                        attr_value = self._validate_factors(input_name, input_value)
+                    elif input_name not in self.exception_list:
+                        if isinstance(input_value, tuple):
+                            attr_value = self._validate_tuple(input_name, input_value)
+                        elif isinstance(input_value, list):
+                            attr_value = self._validate_list(input_name, input_value)
+                        elif isinstance(input_value, (int, float)):
+                            attr_value = self._validate_scalar(input_name, input_value)
+                        else:
+                            raise AssertionError(
+                                f"'{input_name}' must be a tuple, list, int, or float"
+                            )
+                else:
+                    attr_value = [getattr(self.object, input_name)]
+                setattr(self, input_name, attr_value)
+
+    def __repr__(self):
+        return f"'{self.__class__.__name__}() object'"
+
+    def _validate_tuple(self, input_name, input_value, getattr=getattr):
+        """
+        Validate tuple arguments.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : tuple
+            Value of the input argument. This is the tuple to be validated.
+        getattr : function
+            Function used to get the attribute value from the object.
+
+        Returns
+        -------
+        tuple
+            Validated tuple in the format (nominal value, standard deviation, \
+                distribution function).
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        assert len(input_value) in [
+            2,
+            3,
+        ], f"'{input_name}': tuple must have length 2 or 3"
+        assert isinstance(
+            input_value[0], (int, float)
+        ), f"'{input_name}': First item of tuple must be an int or float"
+
+        if len(input_value) == 2:
+            return self._validate_tuple_length_two(input_name, input_value, getattr)
+        if len(input_value) == 3:
+            return self._validate_tuple_length_three(input_name, input_value, getattr)
+
+    def _validate_tuple_length_two(self, input_name, input_value, getattr=getattr):
+        """
+        Validate tuples with length 2.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : tuple
+            Value of the input argument.
+        getattr : function
+            Function to get the attribute value from the object.
+
+        Returns
+        -------
+        tuple
+            Validated tuple in the format (nominal value, standard deviation, \
+                distribution function).
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        assert isinstance(
+            input_value[1], (int, float, str)
+        ), f"'{input_name}': second item of tuple must be an int, float, or string."
+
+        if isinstance(input_value[1], str):
+            # if second item is a string, then it is assumed that the first item
+            # is the standard deviation, and the second item is the distribution
+            # function. In this case, the nominal value will be taken from the
+            # object passed.
+            dist_func = get_distribution(input_value[1])
+            return (getattr(self.object, input_name), input_value[0], dist_func)
+        else:
+            # if second item is an int or float, then it is assumed that the
+            # first item is the nominal value and the second item is the
+            # standard deviation. The distribution function will be set to
+            # "normal".
+            return (input_value[0], input_value[1], get_distribution("normal"))
+
+    def _validate_tuple_length_three(self, input_name, input_value, getattr=getattr):
+        """
+        Validate tuples with length 3.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : tuple
+            Value of the input argument.
+        getattr : function
+            Function to get the attribute value from the object.
+
+        Returns
+        -------
+        tuple
+            Validated tuple in the format (nominal value, standard deviation, \
+                distribution function).
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        assert isinstance(input_value[1], (int, float)), (
+            f"'{input_name}': Second item of a tuple with length 3 must be an "
+            "int or float."
+        )
+        assert isinstance(input_value[2], str), (
+            f"'{input_name}': Third item of tuple must be a string containing the "
+            "name of a valid numpy.random distribution function."
+        )
+        dist_func = get_distribution(input_value[2])
+        return (input_value[0], input_value[1], dist_func)
+
+    def _validate_list(self, input_name, input_value, getattr=getattr):
+        """
+        Validate list arguments.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : list
+            Value of the input argument.
+        getattr : function
+            Function to get the attribute value from the object.
+
+        Returns
+        -------
+        list
+            Validated list.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        if not input_value:
+            return [getattr(self.object, input_name)]
+        else:
+            return input_value
+
+    def _validate_scalar(self, input_name, input_value, getattr=getattr):
+        """
+        Validate scalar arguments. If the input is a scalar, the nominal value
+        will be taken from the object passed, and the standard deviation will be
+        the scalar value. The distribution function will be set to "normal".
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : float
+            Value of the input argument.
+        getattr : function
+            Function to get the attribute value from the object.
+
+        Returns
+        -------
+        tuple
+            Validated tuple in the format (nominal value, standard deviation, \
+                distribution function).
+        """
+        return (
+            getattr(self.object, input_name),
+            input_value,
+            get_distribution("normal"),
+        )
+
+    def _validate_factors(self, input_name, input_value):
+        """
+        Validate factor arguments.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : tuple or list
+            Value of the input argument.
+
+        Returns
+        -------
+        tuple or list
+            Validated tuple or list.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        attribute_name = input_name.replace("_factor", "")
+        setattr(self, f"_{attribute_name}", getattr(self.object, attribute_name))
+
+        if isinstance(input_value, tuple):
+            return self._validate_tuple_factor(input_name, input_value)
+        elif isinstance(input_value, list):
+            return self._validate_list_factor(input_name, input_value)
+        else:
+            raise AssertionError(f"`{input_name}`: must be either a tuple or list")
+
+    def _validate_tuple_factor(self, input_name, factor_tuple):
+        """
+        Validate tuple factors.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        factor_tuple : tuple
+            Value of the input argument.
+
+        Returns
+        -------
+        tuple
+            Validated tuple.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        assert len(factor_tuple) in [
+            2,
+            3,
+        ], f"'{input_name}`: Factors tuple must have length 2 or 3"
+        assert all(isinstance(item, (int, float)) for item in factor_tuple[:2]), (
+            f"'{input_name}`: First and second items of Factors tuple must be "
+            "either an int or float"
+        )
+
+        if len(factor_tuple) == 2:
+            return (factor_tuple[0], factor_tuple[1], get_distribution("normal"))
+        elif len(factor_tuple) == 3:
+            assert isinstance(factor_tuple[2], str), (
+                f"'{input_name}`: Third item of tuple must be a string containing "
+                "the name of a valid numpy.random distribution function"
+            )
+            dist_func = get_distribution(factor_tuple[2])
+            return (factor_tuple[0], factor_tuple[1], dist_func)
+
+    def _validate_list_factor(self, input_name, factor_list):
+        """
+        Validate list factors.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        factor_list : list
+            Value of the input argument.
+
+        Returns
+        -------
+        list
+            Validated list.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        assert all(
+            isinstance(item, (int, float)) for item in factor_list
+        ), f"'{input_name}`: Items in list must be either ints or floats"
+        return factor_list
+
+    def _validate_1d_array_like(self, input_name, input_value):
+        """
+        Validate 1D array-like arguments.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : list
+            Value of the input argument.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        if input_value is not None:
+            error_msg = (
+                f"`{input_name}` must be a list of path strings, lists "
+                "with shape (n,2), or Functions."
+            )
+
+            if not isinstance(input_value, list):
+                raise AssertionError(error_msg)
+
+            for member in input_value:
+                if isinstance(member, list):
+                    if len(np.shape(member)) != 2 or np.shape(member)[1] != 2:
+                        raise AssertionError(error_msg)
+                elif not isinstance(member, (str, Function)):
+                    raise AssertionError(error_msg)
+
+    def _validate_positive_int_list(self, input_name, input_value):
+        """
+        Validate lists of positive integers.
+
+        Parameters
+        ----------
+        input_name : str
+            Name of the input argument.
+        input_value : list
+            Value of the input argument.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        if input_value is not None:
+            assert isinstance(input_value, list) and all(
+                isinstance(member, int) and member >= 0 for member in input_value
+            ), f"`{input_name}` must be a list of positive integers"
+
+    def _validate_airfoil(self, airfoil):
+        """
+        Validate airfoil input.
+
+        Parameters
+        ----------
+        airfoil : list[tuple]
+            List of tuples with two items.
+
+        Raises
+        ------
+        AssertionError
+            If the input is not in a valid format.
+        """
+        # TODO: The _validate_airfoil should be defined in a child class.
+        if airfoil is not None:
+            assert isinstance(airfoil, list) and all(
+                isinstance(member, tuple) for member in airfoil
+            ), "`airfoil` must be a list of tuples"
+            for member in airfoil:
+                assert len(member) == 2, "`airfoil` tuples must have length 2"
+                assert isinstance(
+                    member[1], str
+                ), "`airfoil` tuples must have a string as the second item"
+                if isinstance(member[0], list):
+                    if len(np.shape(member[0])) != 2 and np.shape(member[0])[1] != 2:
+                        raise AssertionError("`airfoil` tuples must have shape (n,2)")
+                elif not isinstance(member[0], str) and not callable(member[0]):
+                    raise AssertionError(
+                        "`airfoil` tuples must have a string or Function as "
+                        "the first item"
+                    )
+
+    def dict_generator(self):
+        """
+        Generate a dictionary with randomly generated input arguments.
+        The last generated dictionary is saved as a class attribute called
+        `last_rnd_dict`.
+
+        Yields
+        ------
+        dict
+            Dictionary with the randomly generated input arguments.
+
+        Notes
+        -----
+        1. The dictionary is generated by iterating over the class attributes and:
+            a. If the attribute is a tuple, the value is generated using the\
+                distribution function specified in the tuple.
+            b. If the attribute is a list, the value is randomly chosen from the list.
+        """
+        generated_dict = {}
+        for arg, value in self.__dict__.items():
+            if isinstance(value, tuple):
+                generated_dict[arg] = value[-1](value[0], value[1])
+            elif isinstance(value, list):
+                generated_dict[arg] = choice(value) if value else value
+        self.last_rnd_dict = generated_dict
+        yield generated_dict
+
+    def visualize_attributes(self):
+        """
+        This method prints a report of the attributes stored in the Stochastic
+        Model object. The report includes the variable name, the nominal value,
+        the standard deviation, and the distribution function used to generate
+        the random attributes.
+        """
+
+        def format_attribute(attr, value):
+            if isinstance(value, list):
+                return (
+                    f"\t{attr.ljust(max_str_length)} {value[0]}"
+                    if len(value) == 1
+                    else f"\t{attr} {value}"
+                )
+            elif isinstance(value, tuple):
+                nominal_value, std_dev, dist_func = value
+                return (
+                    f"\t{attr.ljust(max_str_length)} "
+                    f"{nominal_value:.5f} ± "
+                    f"{std_dev:.5f} ({dist_func.__name__})"
+                )
+            return None
+
+        attributes = {k: v for k, v in self.__dict__.items() if not k.startswith("_")}
+        max_str_length = max(len(var) for var in attributes) + 2
+
+        report = [
+            f"Reporting the attributes of the `{self.__class__.__name__}` object:"
+        ]
+
+        # Sorting alphabetically makes the report more readable
+        items = attributes.items()
+        items = sorted(items, key=lambda x: x[0])
+
+        to_exclude = ["object", "last_rnd_dict", "exception_list", "parachutes"]
+        items = [item for item in items if item[0] not in to_exclude]
+
+        constant_attributes = [
+            attr for attr, val in items if isinstance(val, list) and len(val) == 1
+        ]
+        tuple_attributes = [attr for attr, val in items if isinstance(val, tuple)]
+        list_attributes = [
+            attr for attr, val in items if isinstance(val, list) and len(val) > 1
+        ]
+
+        if constant_attributes:
+            report.append("\nConstant Attributes:")
+            report.extend(
+                format_attribute(attr, attributes[attr]) for attr in constant_attributes
+            )
+
+        if tuple_attributes:
+            report.append("\nStochastic Attributes:")
+            report.extend(
+                format_attribute(attr, attributes[attr]) for attr in tuple_attributes
+            )
+
+        if list_attributes:
+            report.append("\nStochastic Attributes with choice of values:")
+            report.extend(
+                format_attribute(attr, attributes[attr]) for attr in list_attributes
+            )
+
+        print("\n".join(filter(None, report)))
diff --git a/rocketpy/stochastic/stochastic_motor_model.py b/rocketpy/stochastic/stochastic_motor_model.py
new file mode 100644
index 000000000..a99368ab3
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_motor_model.py
@@ -0,0 +1,19 @@
+"""Defines the StochasticMotorModel class."""
+
+from .stochastic_model import StochasticModel
+
+
+class StochasticMotorModel(StochasticModel):
+    """Stochastic Motor Model class that inherits from StochasticModel. This
+    class makes a common ground for other stochastic motor classes.
+
+    See Also
+    --------
+    :ref:`stochastic_model`
+    """
+
+    def __init__(self, object, **kwargs):
+        self._validate_1d_array_like("thrust_source", kwargs.get("thrust_source"))
+        # TODO: never vary the grain_number
+        self._validate_positive_int_list("grain_number", kwargs.get("grain_number"))
+        super().__init__(object, **kwargs)
diff --git a/rocketpy/stochastic/stochastic_parachute.py b/rocketpy/stochastic/stochastic_parachute.py
new file mode 100644
index 000000000..4cf7746d7
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_parachute.py
@@ -0,0 +1,121 @@
+"""Defines the StochasticParachute class."""
+
+from rocketpy.rocket import Parachute
+
+from .stochastic_model import StochasticModel
+
+
+class StochasticParachute(StochasticModel):
+    """A Stochastic Parachute class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`Parachute <rocketpy.rocket.Parachute>`
+
+    Attributes
+    ----------
+    object : Parachute
+        Parachute object to be used for validation.
+    cd_s : tuple, list, int, float
+        Drag coefficient of the parachute.
+    trigger : list
+        List of callables, string "apogee" or ints/floats.
+    sampling_rate : tuple, list, int, float
+        Sampling rate of the parachute in seconds.
+    lag : tuple, list, int, float
+        Lag of the parachute in seconds.
+    noise : list[tuple]
+        List of tuples in the form of (mean, standard deviation,
+        time-correlation).
+    name : list[str]
+        List with the name of the parachute object. This cannot be randomized.
+    """
+
+    def __init__(
+        self,
+        parachute,
+        cd_s=None,
+        trigger=None,
+        sampling_rate=None,
+        lag=None,
+        noise=None,
+    ):
+        """Initializes the Stochastic Parachute class.
+
+        See Also
+        --------
+        :ref:`stochastic_model`
+
+        Parameters
+        ----------
+        parachute : Parachute
+            Parachute object to be used for validation.
+        cd_s : tuple, list, int, float
+            Drag coefficient of the parachute.
+        trigger : list
+            List of callables, string "apogee" or ints/floats.
+        sampling_rate : tuple, list, int, float
+            Sampling rate of the parachute in seconds.
+        lag : tuple, list, int, float
+            Lag of the parachute in seconds. Pay special attention to ensure
+            the lag will not assume negative values based on its mean and
+            standard deviation.
+        noise : list
+            List of tuples in the form of (mean, standard deviation,
+            time-correlation).
+        """
+        self.parachute = parachute
+        self.cd_s = cd_s
+        self.trigger = trigger
+        self.sampling_rate = sampling_rate
+        self.lag = lag
+        self.noise = noise
+
+        self._validate_trigger(trigger)
+        self._validate_noise(noise)
+        super().__init__(
+            parachute,
+            cd_s=cd_s,
+            trigger=trigger,
+            sampling_rate=sampling_rate,
+            lag=lag,
+            noise=noise,
+            name=None,
+        )
+
+    def _validate_trigger(self, trigger):
+        """Validates the trigger input. If the trigger input argument is not
+        None, it must be:
+        - a list of callables, string "apogee" or ints/floats
+        - a tuple that will be further validated in the StochasticModel class
+        """
+        if trigger is not None:
+            assert isinstance(trigger, list) and all(
+                isinstance(member, (str, int, float) or callable(member))
+                for member in trigger
+            ), "`trigger` must be a list of callables, string 'apogee' or ints/floats"
+
+    def _validate_noise(self, noise):
+        """Validates the noise input. If the noise input argument is not
+        None, it must be a list of tuples in the form of
+        (mean, standard deviation, time-correlation)
+        """
+        if noise is not None:
+            assert isinstance(noise, list) and all(
+                isinstance(member, tuple) for member in noise
+            ), (
+                "`noise` must be a list of tuples in the form of "
+                "(mean, standard deviation, time-correlation)"
+            )
+
+    def create_object(self):
+        """Creates and returns a Parachute object from the randomly generated
+        input arguments.
+
+        Returns
+        -------
+        parachute : Parachute
+            Parachute object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return Parachute(**generated_dict)
diff --git a/rocketpy/stochastic/stochastic_rocket.py b/rocketpy/stochastic/stochastic_rocket.py
new file mode 100644
index 000000000..19975a6db
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_rocket.py
@@ -0,0 +1,586 @@
+"""Defines the StochasticRocket class."""
+
+import warnings
+from random import choice
+
+from rocketpy.motors.motor import EmptyMotor, GenericMotor, Motor
+from rocketpy.motors.solid_motor import SolidMotor
+from rocketpy.rocket.aero_surface import (
+    EllipticalFins,
+    NoseCone,
+    RailButtons,
+    Tail,
+    TrapezoidalFins,
+)
+from rocketpy.rocket.components import Components
+from rocketpy.rocket.parachute import Parachute
+from rocketpy.rocket.rocket import Rocket
+from rocketpy.stochastic.stochastic_generic_motor import StochasticGenericMotor
+from rocketpy.stochastic.stochastic_motor_model import StochasticMotorModel
+
+from .stochastic_aero_surfaces import (
+    StochasticEllipticalFins,
+    StochasticNoseCone,
+    StochasticRailButtons,
+    StochasticTail,
+    StochasticTrapezoidalFins,
+)
+from .stochastic_model import StochasticModel
+from .stochastic_parachute import StochasticParachute
+from .stochastic_solid_motor import StochasticSolidMotor
+
+# TODO: Private methods of this class should be double underscored
+
+
+class StochasticRocket(StochasticModel):
+    """A Stochastic Rocket class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`Rocket <rocketpy.Rocket>`
+
+    Attributes
+    ----------
+    object : Rocket
+        The Rocket object to be used as a base for the Stochastic rocket.
+    motors : Components
+        A Components instance containing all the motors of the rocket.
+    aerodynamic_surfaces : Components
+        A Components instance containing all the aerodynamic surfaces of the
+        rocket.
+    rail_buttons : Components
+        A Components instance containing all the rail buttons of the rocket.
+    parachutes : list of StochasticParachute
+        A list of StochasticParachute instances containing all the parachutes of
+        the rocket.
+    radius : tuple, list, int, float
+        The radius of the rocket.
+    mass : tuple, list, int, float
+        The mass of the rocket.
+    inertia_11 : tuple, list, int, float
+        The inertia of the rocket around the x axis.
+    inertia_22 : tuple, list, int, float
+        The inertia of the rocket around the y axis.
+    inertia_33 : tuple, list, int, float
+        The inertia of the rocket around the z axis.
+    inertia_12 : tuple, list, int, float
+        The inertia of the rocket around the xy axis.
+    inertia_13 : tuple, list, int, float
+        The inertia of the rocket around the xz axis.
+    inertia_23 : tuple, list, int, float
+        The inertia of the rocket around the yz axis.
+    power_off_drag : list
+        The power off drag of the rocket.
+    power_on_drag : list
+        The power on drag of the rocket.
+    power_off_drag_factor : tuple, list, int, float
+        The power off drag factor of the rocket.
+    power_on_drag_factor : tuple, list, int, float
+        The power on drag factor of the rocket.
+    center_of_mass_without_motor : tuple, list, int, float
+        The center of mass of the rocket without the motor.
+    coordinate_system_orientation : list[str]
+        The orientation of the coordinate system of the rocket. This attribute
+        can not be a randomized.
+    """
+
+    def __init__(
+        self,
+        rocket,
+        radius=None,
+        mass=None,
+        inertia_11=None,
+        inertia_22=None,
+        inertia_33=None,
+        inertia_12=None,
+        inertia_13=None,
+        inertia_23=None,
+        power_off_drag=None,
+        power_on_drag=None,
+        power_off_drag_factor=(1, 0),
+        power_on_drag_factor=(1, 0),
+        center_of_mass_without_motor=None,
+    ):
+        """Initializes the Stochastic Rocket class.
+
+        See Also
+        --------
+        :ref:`stochastic_model`
+
+        Parameters
+        ----------
+        rocket : Rocket
+            The Rocket object to be used as a base for the Stochastic rocket.
+        radius : int, float, tuple, list, optional
+            The radius of the rocket.
+        mass : int, float, tuple, list, optional
+            The mass of the rocket.
+        inertia_11 : int, float, tuple, list, optional
+            The inertia of the rocket around the x axis.
+        inertia_22 : int, float, tuple, list, optional
+            The inertia of the rocket around the y axis.
+        inertia_33 : int, float, tuple, list, optional
+            The inertia of the rocket around the z axis.
+        inertia_12 : int, float, tuple, list, optional
+            The inertia of the rocket around the xy axis.
+        inertia_13 : int, float, tuple, list, optional
+            The inertia of the rocket around the xz axis.
+        inertia_23 : int, float, tuple, list, optional
+            The inertia of the rocket around the yz axis.
+        power_off_drag : list, optional
+            The power off drag of the rocket.
+        power_on_drag : list, optional
+            The power on drag of the rocket.
+        power_off_drag_factor : int, float, tuple, list, optional
+            The power off drag factor of the rocket. This represents a factor
+            that multiplies the power off drag curve.
+        power_on_drag_factor : int, float, tuple, list, optional
+            The power on drag factor of the rocket. This represents a factor
+            that multiplies the power on drag curve.
+        center_of_mass_without_motor : int, float, tuple, list, optional
+            The center of mass of the rocket without the motor.
+        """
+        # TODO: mention that these factors are validated differently
+        self._validate_1d_array_like("power_off_drag", power_off_drag)
+        self._validate_1d_array_like("power_on_drag", power_on_drag)
+        super().__init__(
+            object=rocket,
+            radius=radius,
+            mass=mass,
+            I_11_without_motor=inertia_11,
+            I_22_without_motor=inertia_22,
+            I_33_without_motor=inertia_33,
+            I_12_without_motor=inertia_12,
+            I_13_without_motor=inertia_13,
+            I_23_without_motor=inertia_23,
+            power_off_drag=power_off_drag,
+            power_on_drag=power_on_drag,
+            power_off_drag_factor=power_off_drag_factor,
+            power_on_drag_factor=power_on_drag_factor,
+            center_of_mass_without_motor=center_of_mass_without_motor,
+            coordinate_system_orientation=None,
+        )
+        self.motors = Components()
+        self.aerodynamic_surfaces = Components()
+        self.rail_buttons = Components()
+        self.parachutes = []
+
+    def add_motor(self, motor, position=None):
+        """Adds a stochastic motor to the stochastic rocket. If a motor is
+        already present, it will be replaced.
+
+        Parameters
+        ----------
+        motor : StochasticMotor or Motor
+            The motor to be added to the stochastic rocket.
+        position : tuple, list, int, float, optional
+            The position of the motor.
+        """
+        # checks if there is a motor already
+        if len(self.motors) > 0:
+            warnings.warn(
+                "Only one motor can be added to the stochastic rocket. "
+                "The previous motor will be replaced."
+            )
+            self.motors = Components()
+
+        # checks if input is a Motor
+        if not isinstance(motor, (Motor, StochasticMotorModel)):
+            raise TypeError("`motor` must be a StochasticMotor or Motor type")
+        if isinstance(motor, Motor):
+            # TODO implement HybridMotor and LiquidMotor stochastic models
+            if isinstance(motor, SolidMotor):
+                motor = StochasticSolidMotor(solid_motor=motor)
+            elif isinstance(motor, GenericMotor):
+                motor = StochasticGenericMotor(generic_motor=motor)
+        self.motors.add(motor, self._validate_position(motor, position))
+
+    def _add_surfaces(self, surfaces, positions, type, stochastic_type, error_message):
+        """Adds a stochastic aerodynamic surface to the stochastic rocket. If
+        an aerodynamic surface is already present, it will be replaced.
+
+        Parameters
+        ----------
+        surfaces : StochasticAeroSurface or AeroSurface
+            The aerodynamic surface to be added to the stochastic rocket.
+        positions : tuple, list, int, float, optional
+            The position of the aerodynamic surface.
+        type : type
+            The type of the aerodynamic surface to be added to the stochastic
+            rocket.
+        stochastic_type : type
+            The type of the stochastic aerodynamic surface to be added to the
+            stochastic rocket.
+        error_message : str
+            The error message to be raised if the input is not of the correct
+            type.
+        """
+        if not isinstance(surfaces, (type, stochastic_type)):
+            raise AssertionError(error_message)
+        if isinstance(surfaces, type):
+            surfaces = stochastic_type(component=surfaces)
+        self.aerodynamic_surfaces.add(
+            surfaces, self._validate_position(surfaces, positions)
+        )
+
+    def add_nose(self, nose, position=None):
+        """Adds a stochastic nose cone to the stochastic rocket.
+
+        Parameters
+        ----------
+        nose : StochasticNoseCone or NoseCone
+            The nose cone to be added to the stochastic rocket.
+        position : tuple, list, int, float, optional
+            The position of the nose cone.
+        """
+        self._add_surfaces(
+            surfaces=nose,
+            positions=position,
+            type=NoseCone,
+            stochastic_type=StochasticNoseCone,
+            error_message="`nose` must be of NoseCone or StochasticNoseCone type",
+        )
+
+    def add_trapezoidal_fins(self, fins, position=None):
+        """Adds a stochastic trapezoidal fins to the stochastic rocket.
+
+        Parameters
+        ----------
+        fins : StochasticTrapezoidalFins or TrapezoidalFins
+            The trapezoidal fins to be added to the stochastic rocket.
+        position : tuple, list, int, float, optional
+            The position of the trapezoidal fins.
+        """
+        self._add_surfaces(
+            fins,
+            position,
+            TrapezoidalFins,
+            StochasticTrapezoidalFins,
+            "`fins` must be of TrapezoidalFins or StochasticTrapezoidalFins type",
+        )
+
+    def add_elliptical_fins(self, fins, position=None):
+        """Adds a stochastic elliptical fins to the stochastic rocket.
+
+        Parameters
+        ----------
+        fins : StochasticEllipticalFins or EllipticalFins
+            The elliptical fins to be added to the stochastic rocket.
+        position : tuple, list, int, float, optional
+            The position of the elliptical fins.
+        """
+        self._add_surfaces(
+            fins,
+            position,
+            EllipticalFins,
+            StochasticEllipticalFins,
+            "`fins` must be of EllipticalFins or StochasticEllipticalFins type",
+        )
+
+    def add_tail(self, tail, position=None):
+        """Adds a stochastic tail to the stochastic rocket.
+
+        Parameters
+        ----------
+        tail : StochasticTail or Tail
+            The tail to be added to the stochastic rocket.
+        position : tuple, list, int, float, optional
+            The position of the tail.
+        """
+        self._add_surfaces(
+            tail,
+            position,
+            Tail,
+            StochasticTail,
+            "`tail` must be of Tail or StochasticTail type",
+        )
+
+    def add_parachute(self, parachute):
+        """Adds a stochastic parachute to the stochastic rocket.
+
+        Parameters
+        ----------
+        parachute : StochasticParachute or Parachute
+            The parachute to be added to the stochastic rocket.
+        """
+        # checks if input is a StochasticParachute type
+        if not isinstance(parachute, (Parachute, StochasticParachute)):
+            raise TypeError(
+                "`parachute` must be of Parachute or StochasticParachute type"
+            )
+        if isinstance(parachute, Parachute):
+            parachute = StochasticParachute(parachute=parachute)
+        self.parachutes.append(parachute)
+
+    def set_rail_buttons(
+        self,
+        rail_buttons,
+        lower_button_position=None,
+    ):
+        """Sets the rail buttons of the stochastic rocket.
+
+        Parameters
+        ----------
+        rail_buttons : StochasticRailButtons or RailButtons
+            The rail buttons to be added to the stochastic rocket.
+        lower_button_position : tuple, list, int, float, optional
+            The position of the lower button.
+        """
+        if not isinstance(rail_buttons, (StochasticRailButtons, RailButtons)):
+            raise AssertionError(
+                "`rail_buttons` must be of RailButtons or StochasticRailButtons type"
+            )
+        if isinstance(rail_buttons, RailButtons):
+            rail_buttons = StochasticRailButtons(rail_buttons=rail_buttons)
+        self.rail_buttons.add(
+            rail_buttons, self._validate_position(rail_buttons, lower_button_position)
+        )
+
+    def _validate_position(self, validated_object, position):
+        """Validate the position argument.
+
+        Parameters
+        ----------
+        validated_object : object
+            The object to which the position argument refers to.
+        position : tuple, list, int, float
+            The position argument to be validated.
+
+        Returns
+        -------
+        tuple or list
+            Validated position argument.
+
+        Raises
+        ------
+        ValueError
+            If the position argument does not conform to the specified formats.
+        """
+
+        if isinstance(position, tuple):
+            return self._validate_tuple(
+                "position",
+                position,
+                getattr=self._create_get_position(validated_object),
+            )
+        elif isinstance(position, (int, float)):
+            return self._validate_scalar(
+                "position",
+                position,
+                getattr=self._create_get_position(validated_object),
+            )
+        elif isinstance(position, list):
+            return self._validate_list(
+                "position",
+                position,
+                getattr=self._create_get_position(validated_object),
+            )
+        elif position is None:
+            position = []
+            return self._validate_list(
+                "position",
+                position,
+                getattr=self._create_get_position(validated_object),
+            )
+        else:
+            raise AssertionError("`position` must be a tuple, list, int, or float")
+
+    def _create_get_position(self, validated_object):
+        """Create a function to get the nominal position from an object.
+
+        Parameters
+        ----------
+        validated_object : object
+            The object to which the position argument refers to.
+
+        Returns
+        -------
+        function
+            Function to get the nominal position from an object. The function
+            must receive two arguments.
+        """
+
+        # try to get position from object
+        error_msg = (
+            "`position` standard deviation was provided but the rocket does "
+            f"not have the same {validated_object.object.__class__.__name__} "
+            "to get the nominal position value from."
+        )
+        # special case for motor stochastic model
+        if isinstance(validated_object, (StochasticMotorModel)):
+            if isinstance(self.object.motor, EmptyMotor):
+                raise AssertionError(error_msg)
+
+            def get_motor_position(self_object, _):
+                return self_object.motor_position
+
+            return get_motor_position
+        else:
+            if isinstance(validated_object, StochasticRailButtons):
+
+                def get_surface_position(self_object, _):
+                    surfaces = self_object.rail_buttons.get_tuple_by_type(
+                        validated_object.object.__class__
+                    )
+                    if len(surfaces) == 0:
+                        raise AssertionError(error_msg)
+                    for surface in surfaces:
+                        if surface.component == validated_object.object:
+                            return surface.position
+                        else:
+                            raise AssertionError(error_msg)
+
+            else:
+
+                def get_surface_position(self_object, _):
+                    surfaces = self_object.aerodynamic_surfaces.get_tuple_by_type(
+                        validated_object.object.__class__
+                    )
+                    if len(surfaces) == 0:
+                        raise AssertionError(error_msg)
+                    for surface in surfaces:
+                        if surface.component == validated_object.object:
+                            return surface.position
+                        else:
+                            raise AssertionError(error_msg)
+
+            return get_surface_position
+
+    def _randomize_position(self, position):
+        """Randomize a position provided as a tuple or list."""
+        if isinstance(position, tuple):
+            return position[-1](position[0], position[1])
+        elif isinstance(position, list):
+            return choice(position) if position else position
+
+    def dict_generator(self):
+        """Special generator for the rocket class that yields a dictionary with
+        the randomly generated input arguments. The dictionary is saved as an
+        attribute of the class. The dictionary is generated by looping through
+        all attributes of the class and generating a random value for each
+        attribute. The random values are generated according to the format of
+        each attribute. Tuples are generated using the distribution function
+        specified in the tuple. Lists are generated using the random.choice
+        function.
+
+        Parameters
+        ----------
+        None
+
+        Yields
+        -------
+        dict
+            Dictionary with the randomly generated input arguments.
+        """
+        generated_dict = next(super().dict_generator())
+        generated_dict["motors"] = []
+        generated_dict["aerodynamic_surfaces"] = []
+        generated_dict["rail_buttons"] = []
+        generated_dict["parachutes"] = []
+        self.last_rnd_dict = generated_dict
+        yield generated_dict
+
+    def _create_motor(self, component_stochastic_motor):
+        stochastic_motor = component_stochastic_motor.component
+        motor = stochastic_motor.create_object()
+        position_rnd = self._randomize_position(component_stochastic_motor.position)
+        self.last_rnd_dict["motors"].append(stochastic_motor.last_rnd_dict)
+        self.last_rnd_dict["motors"][-1]["position"] = position_rnd
+        return motor, position_rnd
+
+    def _create_surface(self, component_stochastic_surface):
+        stochastic_surface = component_stochastic_surface.component
+        surface = stochastic_surface.create_object()
+        position_rnd = self._randomize_position(component_stochastic_surface.position)
+        self.last_rnd_dict["aerodynamic_surfaces"].append(
+            stochastic_surface.last_rnd_dict
+        )
+        self.last_rnd_dict["aerodynamic_surfaces"][-1]["position"] = position_rnd
+        return surface, position_rnd
+
+    def _create_rail_buttons(self, component_stochastic_rail_buttons):
+        stochastic_rail_buttons = component_stochastic_rail_buttons.component
+        rail_buttons = stochastic_rail_buttons.create_object()
+        lower_button_position_rnd = self._randomize_position(
+            component_stochastic_rail_buttons.position
+        )
+        upper_button_position_rnd = (
+            rail_buttons.buttons_distance + lower_button_position_rnd
+        )
+        self.last_rnd_dict["rail_buttons"].append(stochastic_rail_buttons.last_rnd_dict)
+        self.last_rnd_dict["rail_buttons"][-1][
+            "lower_button_position"
+        ] = lower_button_position_rnd
+        self.last_rnd_dict["rail_buttons"][-1][
+            "upper_button_position"
+        ] = upper_button_position_rnd
+        return rail_buttons, lower_button_position_rnd, upper_button_position_rnd
+
+    def _create_parachute(self, stochastic_parachute):
+        parachute = stochastic_parachute.create_object()
+        self.last_rnd_dict["parachutes"].append(stochastic_parachute.last_rnd_dict)
+        return parachute
+
+    def create_object(self):
+        """Creates and returns a Rocket object from the randomly generated input
+        arguments.
+
+        Returns
+        -------
+        rocket : Rocket
+            Rocket object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        rocket = Rocket(
+            radius=generated_dict["radius"],
+            mass=generated_dict["mass"],
+            inertia=(
+                generated_dict["I_11_without_motor"],
+                generated_dict["I_22_without_motor"],
+                generated_dict["I_33_without_motor"],
+                generated_dict["I_12_without_motor"],
+                generated_dict["I_13_without_motor"],
+                generated_dict["I_23_without_motor"],
+            ),
+            power_off_drag=generated_dict["power_off_drag"],
+            power_on_drag=generated_dict["power_on_drag"],
+            center_of_mass_without_motor=generated_dict["center_of_mass_without_motor"],
+            coordinate_system_orientation=generated_dict[
+                "coordinate_system_orientation"
+            ],
+        )
+        rocket.power_off_drag *= generated_dict["power_off_drag_factor"]
+        rocket.power_on_drag *= generated_dict["power_on_drag_factor"]
+
+        for component_motor in self.motors:
+            motor, position_rnd = self._create_motor(component_motor)
+            rocket.add_motor(motor, position_rnd)
+
+        for component_surface in self.aerodynamic_surfaces:
+            surface, position_rnd = self._create_surface(component_surface)
+            rocket.add_surfaces(surface, position_rnd)
+
+        for component_rail_buttons in self.rail_buttons:
+            (
+                rail_buttons,
+                lower_button_position_rnd,
+                upper_button_position_rnd,
+            ) = self._create_rail_buttons(component_rail_buttons)
+            rocket.set_rail_buttons(
+                upper_button_position=upper_button_position_rnd,
+                lower_button_position=lower_button_position_rnd,
+                angular_position=rail_buttons.angular_position,
+            )
+
+        for parachute in self.parachutes:
+            parachute = self._create_parachute(parachute)
+            rocket.add_parachute(
+                name=parachute.name,
+                cd_s=parachute.cd_s,
+                trigger=parachute.trigger,
+                sampling_rate=parachute.sampling_rate,
+                lag=parachute.lag,
+                noise=parachute.noise,
+            )
+
+        return rocket
diff --git a/rocketpy/stochastic/stochastic_solid_motor.py b/rocketpy/stochastic/stochastic_solid_motor.py
new file mode 100644
index 000000000..8550c1e11
--- /dev/null
+++ b/rocketpy/stochastic/stochastic_solid_motor.py
@@ -0,0 +1,222 @@
+"""Defines the StochasticSolidMotor class."""
+
+from rocketpy.motors import SolidMotor
+
+from .stochastic_motor_model import StochasticMotorModel
+
+
+class StochasticSolidMotor(StochasticMotorModel):
+    """A Stochastic Solid Motor class that inherits from StochasticModel.
+
+    See Also
+    --------
+    :ref:`stochastic_model` and :class:`SolidMotor <rocketpy.motors.SolidMotor>`
+
+    Attributes
+    ----------
+    object : SolidMotor
+        SolidMotor object to be used for validation.
+    thrust_source : list
+        List of strings representing the thrust source to be selected.
+    total_impulse : int, float, tuple, list
+        Total impulse of the motor in newton seconds.
+    burn_start_time : int, float, tuple, list
+        Burn start time of the motor in seconds.
+    burn_out_time : int, float, tuple, list
+        Burn out time of the motor in seconds.
+    dry_mass : int, float, tuple, list
+        Dry mass of the motor in kilograms.
+    dry_I_11 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_22 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_33 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_12 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_13 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    dry_I_23 : int, float, tuple, list
+        Dry inertia of the motor in kilograms times meters squared.
+    nozzle_radius : int, float, tuple, list
+        Nozzle radius of the motor in meters.
+    grain_number : list[int]
+        Number of grains in the motor. This attribute can not be randomized.
+    grain_density : int, float, tuple, list
+        Density of the grains in the motor in kilograms per meters cubed.
+    grain_outer_radius : int, float, tuple, list
+        Outer radius of the grains in the motor in meters.
+    grain_initial_inner_radius : int, float, tuple, list
+        Initial inner radius of the grains in the motor in meters.
+    grain_initial_height : int, float, tuple, list
+        Initial height of the grains in the motor in meters.
+    grain_separation : int, float, tuple, list
+        Separation between grains in the motor in meters.
+    grains_center_of_mass_position : int, float, tuple, list
+        Position of the center of mass of the grains in the motor in
+        meters.
+    center_of_dry_mass_position : int, float, tuple, list
+        Position of the center of mass of the dry mass in the motor in
+        meters.
+    nozzle_position : int, float, tuple, list
+        Position of the nozzle in the motor in meters.
+    throat_radius : int, float, tuple, list
+        Radius of the throat in the motor in meters.
+    """
+
+    def __init__(
+        self,
+        solid_motor,
+        thrust_source=None,
+        total_impulse=None,
+        burn_start_time=None,
+        burn_out_time=None,
+        dry_mass=None,
+        dry_inertia_11=None,
+        dry_inertia_22=None,
+        dry_inertia_33=None,
+        dry_inertia_12=None,
+        dry_inertia_13=None,
+        dry_inertia_23=None,
+        nozzle_radius=None,
+        grain_number=None,  # TODO: can't vary the number of grains.
+        grain_density=None,
+        grain_outer_radius=None,
+        grain_initial_inner_radius=None,
+        grain_initial_height=None,
+        grain_separation=None,
+        grains_center_of_mass_position=None,
+        center_of_dry_mass_position=None,
+        nozzle_position=None,
+        throat_radius=None,
+    ):
+        """Initializes the Stochastic Solid Motor class.
+
+        See Also
+        --------
+        :ref:`stochastic_model` and :class:`SolidMotor <rocketpy.motors.SolidMotor>`
+
+        Parameters
+        ----------
+        solid_motor : SolidMotor
+            SolidMotor object to be used for validation.
+        thrust_source : list, optional
+            List of strings representing the thrust source to be selected.
+        total_impulse : int, float, tuple, list, optional
+            Total impulse of the motor in newton seconds.
+        burn_start_time : int, float, tuple, list, optional
+            Burn start time of the motor in seconds.
+        burn_out_time : int, float, tuple, list, optional
+            Burn out time of the motor in seconds.
+        dry_mass : int, float, tuple, list, optional
+            Dry mass of the motor in kilograms.
+        dry_I_11 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_22 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_33 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_12 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_13 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        dry_I_23 : int, float, tuple, list, optional
+            Dry inertia of the motor in kilograms times meters squared.
+        nozzle_radius : int, float, tuple, list, optional
+            Nozzle radius of the motor in meters.
+        grain_density : int, float, tuple, list, optional
+            Density of the grains in the motor in kilograms per meters cubed.
+        grain_outer_radius : int, float, tuple, list, optional
+            Outer radius of the grains in the motor in meters.
+        grain_initial_inner_radius : int, float, tuple, list, optional
+            Initial inner radius of the grains in the motor in meters.
+        grain_initial_height : int, float, tuple, list, optional
+            Initial height of the grains in the motor in meters.
+        grain_separation : int, float, tuple, list, optional
+            Separation between grains in the motor in meters.
+        grains_center_of_mass_position : int, float, tuple, list, optional
+            Position of the center of mass of the grains in the motor in
+            meters.
+        center_of_dry_mass_position : int, float, tuple, list, optional
+            Position of the center of mass of the dry mass in the motor in
+            meters.
+        nozzle_position : int, float, tuple, list, optional
+            Position of the nozzle in the motor in meters.
+        throat_radius : int, float, tuple, list, optional
+            Radius of the throat in the motor in meters.
+        """
+        super().__init__(
+            solid_motor,
+            thrust_source=thrust_source,
+            total_impulse=total_impulse,
+            burn_start_time=burn_start_time,
+            burn_out_time=burn_out_time,
+            dry_mass=dry_mass,
+            dry_I_11=dry_inertia_11,
+            dry_I_22=dry_inertia_22,
+            dry_I_33=dry_inertia_33,
+            dry_I_12=dry_inertia_12,
+            dry_I_13=dry_inertia_13,
+            dry_I_23=dry_inertia_23,
+            nozzle_radius=nozzle_radius,
+            grain_number=grain_number,
+            grain_density=grain_density,
+            grain_outer_radius=grain_outer_radius,
+            grain_initial_inner_radius=grain_initial_inner_radius,
+            grain_initial_height=grain_initial_height,
+            grain_separation=grain_separation,
+            grains_center_of_mass_position=grains_center_of_mass_position,
+            center_of_dry_mass_position=center_of_dry_mass_position,
+            nozzle_position=nozzle_position,
+            throat_radius=throat_radius,
+            interpolate=None,
+            coordinate_system_orientation=None,
+        )
+
+    def create_object(self):
+        """Creates and returns a SolidMotor object from the randomly generated
+        input arguments.
+
+        Returns
+        -------
+        SolidMotor
+            SolidMotor object with the randomly generated input arguments.
+        """
+        generated_dict = next(self.dict_generator())
+        return SolidMotor(
+            thrust_source=generated_dict["thrust_source"],
+            dry_mass=generated_dict["dry_mass"],
+            dry_inertia=(
+                generated_dict["dry_I_11"],
+                generated_dict["dry_I_22"],
+                generated_dict["dry_I_33"],
+                generated_dict["dry_I_12"],
+                generated_dict["dry_I_13"],
+                generated_dict["dry_I_23"],
+            ),
+            nozzle_radius=generated_dict["nozzle_radius"],
+            grain_number=generated_dict["grain_number"],
+            grain_density=generated_dict["grain_density"],
+            grain_outer_radius=generated_dict["grain_outer_radius"],
+            grain_initial_inner_radius=generated_dict["grain_initial_inner_radius"],
+            grain_initial_height=generated_dict["grain_initial_height"],
+            grain_separation=generated_dict["grain_separation"],
+            grains_center_of_mass_position=generated_dict[
+                "grains_center_of_mass_position"
+            ],
+            center_of_dry_mass_position=generated_dict["center_of_dry_mass_position"],
+            nozzle_position=generated_dict["nozzle_position"],
+            burn_time=(
+                generated_dict["burn_start_time"],
+                generated_dict["burn_out_time"],
+            ),
+            throat_radius=generated_dict["throat_radius"],
+            reshape_thrust_curve=(
+                (generated_dict["burn_start_time"], generated_dict["burn_out_time"]),
+                generated_dict["total_impulse"],
+            ),
+            coordinate_system_orientation=generated_dict[
+                "coordinate_system_orientation"
+            ],
+            interpolation_method=generated_dict["interpolate"],
+        )
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 0cbd16628..d27408dca 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -1,3 +1,11 @@
+"""The module rocketpy.tools contains a set of functions that are used
+throughout the rocketpy package. These functions are not specific to any
+particular class or module, and are used to perform general tasks that are
+required by multiple classes or modules. These functions can be modified or
+expanded to suit the needs of other modules and may present breaking changes
+between minor versions if necessary, although this will be always avoided.
+"""
+
 import functools
 import importlib
 import importlib.metadata
@@ -9,6 +17,7 @@
 import numpy as np
 import pytz
 from cftime import num2pydate
+from matplotlib.patches import Ellipse
 from packaging import version as packaging_version
 
 # Mapping of module name and the name of the package that should be installed
@@ -43,6 +52,139 @@ def tuple_handler(value):
             raise ValueError("value must be a list or tuple of length 1 or 2.")
 
 
+def calculate_cubic_hermite_coefficients(x0, x1, y0, yp0, y1, yp1):
+    """Calculate the coefficients of a cubic Hermite interpolation function.
+    The function is defined as ax**3 + bx**2 + cx + d.
+
+    Parameters
+    ----------
+    x0 : float
+        Position of the first point.
+    x1 : float
+        Position of the second point.
+    y0 : float
+        Value of the function evaluated at the first point.
+    yp0 : float
+        Value of the derivative of the function evaluated at the first
+        point.
+    y1 : float
+        Value of the function evaluated at the second point.
+    yp1 : float
+        Value of the derivative of the function evaluated at the second
+        point.
+
+    Returns
+    -------
+    tuple[float, float, float, float]
+        The coefficients of the cubic Hermite interpolation function.
+    """
+    dx = x1 - x0
+    d = float(y0)
+    c = float(yp0)
+    b = float((3 * y1 - yp1 * dx - 2 * c * dx - 3 * d) / (dx**2))
+    a = float(-(2 * y1 - yp1 * dx - c * dx - 2 * d) / (dx**3))
+    return a, b, c, d
+
+
+def find_roots_cubic_function(a, b, c, d):
+    """Calculate the roots of a cubic function using Cardano's method.
+
+    This method applies Cardano's method to find the roots of a cubic
+    function of the form ax^3 + bx^2 + cx + d. The roots may be complex
+    numbers.
+
+    Parameters
+    ----------
+    a : float
+        Coefficient of the cubic term (x^3).
+    b : float
+        Coefficient of the quadratic term (x^2).
+    c : float
+        Coefficient of the linear term (x).
+    d : float
+        Constant term.
+
+    Returns
+    -------
+    tuple[complex, complex, complex]
+        A tuple containing the real and complex roots of the cubic function.
+        Note that the roots may be complex numbers. The roots are ordered
+        in the tuple as x1, x2, x3.
+
+    References
+    ----------
+    - Cardano's method: https://en.wikipedia.org/wiki/Cubic_function#Cardano's_method
+
+    Examples
+    --------
+    >>> from rocketpy.tools import find_roots_cubic_function
+
+    First we define the coefficients of the function ax**3 + bx**2 + cx + d
+    >>> a, b, c, d = 1, -3, -1, 3
+    >>> x1, x2, x3 = find_roots_cubic_function(a, b, c, d)
+    >>> x1, x2, x3
+    ((-1+0j), (3+7.401486830834377e-17j), (1-1.4802973661668753e-16j))
+
+    To get the real part of the roots, use the real attribute of the complex
+    number.
+    >>> x1.real, x2.real, x3.real
+    (-1.0, 3.0, 1.0)
+    """
+    delta_0 = b**2 - 3 * a * c
+    delta_1 = 2 * b**3 - 9 * a * b * c + 27 * d * a**2
+    c1 = ((delta_1 + (delta_1**2 - 4 * delta_0**3) ** (0.5)) / 2) ** (1 / 3)
+
+    c2_0 = c1
+    x1 = -(1 / (3 * a)) * (b + c2_0 + delta_0 / c2_0)
+
+    c2_1 = c1 * (-1 / 2 + 1j * (3**0.5) / 2) ** 1
+    x2 = -(1 / (3 * a)) * (b + c2_1 + delta_0 / c2_1)
+
+    c2_2 = c1 * (-1 / 2 + 1j * (3**0.5) / 2) ** 2
+    x3 = -(1 / (3 * a)) * (b + c2_2 + delta_0 / c2_2)
+
+    return x1, x2, x3
+
+
+def find_root_linear_interpolation(x0, x1, y0, y1, y):
+    """Calculate the root of a linear interpolation function.
+
+    This method calculates the root of a linear interpolation function
+    given two points (x0, y0) and (x1, y1) and a value y. The function
+    is defined as y = m*x + c.
+
+    Parameters
+    ----------
+    x0 : float
+        Position of the first point.
+    x1 : float
+        Position of the second point.
+    y0 : float
+        Value of the function evaluated at the first point.
+    y1 : float
+        Value of the function evaluated at the second point.
+    y : float
+        Value of the function at the desired point.
+
+    Returns
+    -------
+    float
+        The root of the linear interpolation function. This represents the
+        value of x at which the function evaluates to y.
+
+    Examples
+    --------
+    >>> from rocketpy.tools import find_root_linear_interpolation
+    >>> x0, x1, y0, y1, y = 0, 1, 0, 1, 0.5
+    >>> x = find_root_linear_interpolation(x0, x1, y0, y1, y)
+    >>> x
+    0.5
+    """
+    m = (y1 - y0) / (x1 - x0)
+    c = y0 - m * x0
+    return (y - c) / m
+
+
 def bilinear_interpolation(x, y, x1, x2, y1, y2, z11, z12, z21, z22):
     """Bilinear interpolation. It considers the values of the four points
     around the point to be interpolated and returns the interpolated value.
@@ -90,6 +232,323 @@ def bilinear_interpolation(x, y, x1, x2, y1, y2, z11, z12, z21, z22):
     ) / ((x2 - x1) * (y2 - y1))
 
 
+def get_distribution(distribution_function_name):
+    """Sets the distribution function to be used in the monte carlo analysis.
+
+    Parameters
+    ----------
+    distribution_function_name : string
+        The type of distribution to be used in the analysis. It can be
+        'uniform', 'normal', 'lognormal', etc.
+
+    Returns
+    -------
+    np.random distribution function
+        The distribution function to be used in the analysis.
+    """
+    distributions = {
+        "normal": np.random.normal,
+        "binomial": np.random.binomial,
+        "chisquare": np.random.chisquare,
+        "exponential": np.random.exponential,
+        "gamma": np.random.gamma,
+        "gumbel": np.random.gumbel,
+        "laplace": np.random.laplace,
+        "logistic": np.random.logistic,
+        "poisson": np.random.poisson,
+        "uniform": np.random.uniform,
+        "wald": np.random.wald,
+    }
+    try:
+        return distributions[distribution_function_name]
+    except KeyError as e:
+        raise ValueError(
+            f"Distribution function '{distribution_function_name}' not found, "
+            + "please use one of the following np.random distribution function:"
+            + '\n\t"normal"'
+            + '\n\t"binomial"'
+            + '\n\t"chisquare"'
+            + '\n\t"exponential"'
+            + '\n\t"geometric"'
+            + '\n\t"gamma"'
+            + '\n\t"gumbel"'
+            + '\n\t"laplace"'
+            + '\n\t"logistic"'
+            + '\n\t"poisson"'
+            + '\n\t"uniform"'
+            + '\n\t"wald"\n'
+        ) from e
+
+
+def haversine(lat0, lon0, lat1, lon1, earth_radius=6.3781e6):
+    """Returns the distance between two points in meters.
+    The points are defined by their latitude and longitude coordinates.
+
+    Parameters
+    ----------
+    lat0 : float
+        Latitude of the first point, in degrees.
+    lon0 : float
+        Longitude of the first point, in degrees.
+    lat1 : float
+        Latitude of the second point, in degrees.
+    lon1 : float
+        Longitude of the second point, in degrees.
+    earth_radius : float, optional
+        Earth's radius in meters. Default value is 6.3781e6.
+
+    Returns
+    -------
+    float
+        Distance between the two points in meters.
+
+    """
+    lat0_rad = math.radians(lat0)
+    lat1_rad = math.radians(lat1)
+    delta_lat_rad = math.radians(lat1 - lat0)
+    delta_lon_rad = math.radians(lon1 - lon0)
+
+    a = (
+        math.sin(delta_lat_rad / 2) ** 2
+        + math.cos(lat0_rad) * math.cos(lat1_rad) * math.sin(delta_lon_rad / 2) ** 2
+    )
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
+
+    return earth_radius * c
+
+
+def inverted_haversine(lat0, lon0, distance, bearing, earth_radius=6.3781e6):
+    """Returns a tuple with new latitude and longitude coordinates considering
+    a displacement of a given distance in a given direction (bearing compass)
+    starting from a point defined by (lat0, lon0). This is the opposite of
+    Haversine function.
+
+    Parameters
+    ----------
+    lat0 : float
+        Origin latitude coordinate, in degrees.
+    lon0 : float
+        Origin longitude coordinate, in degrees.
+    distance : float
+        Distance from the origin point, in meters.
+    bearing : float
+        Azimuth (or bearing compass) from the origin point, in degrees.
+    earth_radius : float, optional
+        Earth radius, in meters. Default value is 6.3781e6.
+        See the Environment.calculateEarthRadius() function for more accuracy.
+
+    Returns
+    -------
+    lat1 : float
+        New latitude coordinate, in degrees.
+    lon1 : float
+        New longitude coordinate, in degrees.
+
+    """
+
+    # Convert coordinates to radians
+    lat0_rad = np.deg2rad(lat0)
+    lon0_rad = np.deg2rad(lon0)
+
+    # Apply inverted Haversine formula
+    lat1_rad = math.asin(
+        math.sin(lat0_rad) * math.cos(distance / earth_radius)
+        + math.cos(lat0_rad) * math.sin(distance / earth_radius) * math.cos(bearing)
+    )
+
+    lon1_rad = lon0_rad + math.atan2(
+        math.sin(bearing) * math.sin(distance / earth_radius) * math.cos(lat0_rad),
+        math.cos(distance / earth_radius) - math.sin(lat0_rad) * math.sin(lat1_rad),
+    )
+
+    # Convert back to degrees and then return
+    lat1_deg = np.rad2deg(lat1_rad)
+    lon1_deg = np.rad2deg(lon1_rad)
+
+    return lat1_deg, lon1_deg
+
+
+# Functions for monte carlo analysis
+def generate_monte_carlo_ellipses(results):
+    """A function to create apogee and impact ellipses from the monte carlo
+    analysis results.
+
+    Parameters
+    ----------
+    results : dict
+        A dictionary containing the results of the monte carlo analysis. It
+        should contain the following keys:
+            - apogeeX: an array containing the x coordinates of the apogee
+            - apogeeY: an array containing the y coordinates of the apogee
+            - xImpact: an array containing the x coordinates of the impact
+            - yImpact: an array containing the y coordinates of the impact
+
+    Returns
+    -------
+    apogee_ellipse : list[Ellipse]
+        A list of ellipse objects representing the apogee ellipses.
+    impact_ellipse : list[Ellipse]
+        A list of ellipse objects representing the impact ellipses.
+    apogeeX : np.array
+        An array containing the x coordinates of the apogee ellipse.
+    apogeeY : np.array
+        An array containing the y coordinates of the apogee ellipse.
+    impactX : np.array
+        An array containing the x coordinates of the impact ellipse.
+    impactY : np.array
+        An array containing the y coordinates of the impact ellipse.
+    """
+
+    # Retrieve monte carlo data por apogee and impact XY position
+    try:
+        apogee_x = np.array(results["apogee_x"])
+        apogee_y = np.array(results["apogee_y"])
+    except KeyError:
+        print("No apogee data found. Skipping apogee ellipses.")
+        apogee_x = np.array([])
+        apogee_y = np.array([])
+    try:
+        impact_x = np.array(results["x_impact"])
+        impact_y = np.array(results["y_impact"])
+    except KeyError:
+        print("No impact data found. Skipping impact ellipses.")
+        impact_x = np.array([])
+        impact_y = np.array([])
+
+    # Define function to calculate Eigenvalues
+    def eigsorted(cov):
+        # Calculate eigenvalues and eigenvectors
+        vals, vecs = np.linalg.eigh(cov)
+        # Order eigenvalues and eigenvectors in descending order
+        order = vals.argsort()[::-1]
+        return vals[order], vecs[:, order]
+
+    def calculate_ellipses(list_x, list_y):
+        # Calculate covariance matrix
+        cov = np.cov(list_x, list_y)
+        # Calculate eigenvalues and eigenvectors
+        vals, vecs = eigsorted(cov)
+        # Calculate ellipse angle and width/height
+        theta = np.degrees(np.arctan2(*vecs[:, 0][::-1]))
+        w, h = 2 * np.sqrt(vals)
+        return theta, w, h
+
+    def create_ellipse_objects(x, y, n, w, h, theta, rgb):
+        """Create a list of matplotlib.patches.Ellipse objects.
+
+        Parameters
+        ----------
+        x : list or np.array
+            List of x coordinates.
+        y : list or np.array
+            List of y coordinates.
+        n : int
+            Number of ellipses to create. It represents the number of confidence
+            intervals to be used. For example, n=3 will create 3 ellipses with
+            1, 2 and 3 standard deviations.
+        w : float
+            Width of the ellipse.
+        h : float
+            Height of the ellipse.
+        theta : float
+            Angle of the ellipse.
+        rgb : tuple
+            Tuple containing the color of the ellipse in RGB format. For example,
+            (0, 0, 1) will create a blue ellipse.
+
+        Returns
+        -------
+        list
+            List of matplotlib.patches.Ellipse objects.
+        """
+        ell_list = [None] * n
+        for j in range(n):
+            ell = Ellipse(
+                xy=(np.mean(x), np.mean(y)),
+                width=w,
+                height=h,
+                angle=theta,
+                color="black",
+            )
+            ell.set_facecolor(rgb)
+            ell_list[j] = ell
+        return ell_list
+
+    # Calculate error ellipses for impact and apogee
+    impactTheta, impactW, impactH = calculate_ellipses(impact_x, impact_y)
+    apogeeTheta, apogeeW, apogeeH = calculate_ellipses(apogee_x, apogee_y)
+
+    # Draw error ellipses for impact
+    impact_ellipses = create_ellipse_objects(
+        impact_x, impact_y, 3, impactW, impactH, impactTheta, (0, 0, 1, 0.2)
+    )
+
+    apogee_ellipses = create_ellipse_objects(
+        apogee_x, apogee_y, 3, apogeeW, apogeeH, apogeeTheta, (0, 1, 0, 0.2)
+    )
+
+    return impact_ellipses, apogee_ellipses, apogee_x, apogee_y, impact_x, impact_y
+
+
+def generate_monte_carlo_ellipses_coordinates(
+    ellipses, origin_lat, origin_lon, resolution=100
+):
+    """Generate a list of latitude and longitude points for each ellipse in
+    ellipses.
+
+    Parameters
+    ----------
+    ellipses : list
+        List of matplotlib.patches.Ellipse objects.
+    origin_lat : float
+        Latitude of the origin of the coordinate system.
+    origin_lon : float
+        Longitude of the origin of the coordinate system.
+    resolution : int, optional
+        Number of points to generate for each ellipse, by default 100
+
+    Returns
+    -------
+    list
+        List of lists of tuples containing the latitude and longitude of each
+        point in each ellipse.
+    """
+    outputs = [None] * len(ellipses)
+
+    for index, ell in enumerate(ellipses):
+        # Get ellipse path points
+        center = ell.get_center()
+        width = ell.get_width()
+        height = ell.get_height()
+        angle = np.deg2rad(ell.get_angle())
+        points = lat_lon_points = [None] * resolution
+
+        # Generate ellipse path points (in a Cartesian coordinate system)
+        for i in range(resolution):
+            x = width / 2 * math.cos(2 * np.pi * i / resolution)
+            y = height / 2 * math.sin(2 * np.pi * i / resolution)
+            x_rot = center[0] + x * math.cos(angle) - y * math.sin(angle)
+            y_rot = center[1] + x * math.sin(angle) + y * math.cos(angle)
+            points[i] = (x_rot, y_rot)
+        points = np.array(points)
+
+        # Convert path points to lat/lon
+        for point in points:
+            x, y = point
+            # Convert to distance and bearing
+            d = math.sqrt((x**2 + y**2))
+            bearing = math.atan2(
+                x, y
+            )  # math.atan2 returns the angle in the range [-pi, pi]
+
+            lat_lon_points[i] = inverted_haversine(
+                origin_lat, origin_lon, d, bearing, earth_radius=6.3781e6
+            )
+
+        outputs[index] = lat_lon_points
+    return outputs
+
+
 def find_two_closest_integers(number):
     """Find the two closest integer factors of a number.
 
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 96f21a8d3..000000000
--- a/setup.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import setuptools
-
-with open("README.md", "r") as fh:
-    long_description = fh.read()
-
-necessary_require = [
-    "numpy>=1.13",
-    "scipy>=1.0",
-    "matplotlib>=3.0",
-    "netCDF4>=1.6.4",
-    "requests",
-    "pytz",
-    "simplekml",
-]
-
-env_analysis_require = [
-    "timezonefinder",
-    "windrose>=1.6.8",
-    "IPython",
-    "ipywidgets>=7.6.3",
-    "jsonpickle",
-]
-
-setuptools.setup(
-    name="rocketpy",
-    version="1.2.2",
-    install_requires=necessary_require,
-    extras_require={
-        "env_analysis": env_analysis_require,
-        "all": necessary_require + env_analysis_require,
-    },
-    maintainer="RocketPy Developers",
-    author="Giovani Hidalgo Ceotto",
-    author_email="ghceotto@gmail.com",
-    description="Advanced 6-DOF trajectory simulation for High-Power Rocketry.",
-    long_description=long_description,
-    long_description_content_type="text/markdown",
-    url="https://github.com/RocketPy-Team/RocketPy",
-    packages=setuptools.find_packages(),
-    classifiers=[
-        "Programming Language :: Python :: 3",
-        "License :: OSI Approved :: MIT License",
-        "Operating System :: OS Independent",
-    ],
-    python_requires=">=3.8",
-)
diff --git a/tests/acceptance/test_bella_lui_rocket.py b/tests/acceptance/test_bella_lui_rocket.py
index a1297e1fb..0041074a8 100644
--- a/tests/acceptance/test_bella_lui_rocket.py
+++ b/tests/acceptance/test_bella_lui_rocket.py
@@ -228,10 +228,14 @@ def drogue_trigger(p, h, y):
     apogee_time_measured = time_kalt[np.argmax(altitude_kalt)]
     apogee_time_simulated = test_flight.apogee_time
 
-    assert (
-        abs(max(altitude_kalt) - test_flight.apogee + test_flight.env.elevation)
-        / max(altitude_kalt)
-        < 0.015
+    apogee_error_threshold = 0.015
+    apogee_error = abs(
+        max(altitude_kalt) - test_flight.apogee + test_flight.env.elevation
+    ) / max(altitude_kalt)
+    assert apogee_error < apogee_error_threshold, (
+        f"Apogee altitude error exceeded the threshold. "
+        f"Expected the error to be less than {apogee_error_threshold * 100}%, "
+        f"but got an error of {apogee_error * 100:.1f}%."
     )
     assert abs(max(velocity_rcp) - max(vert_vel_kalt)) / max(vert_vel_kalt) < 0.06
     assert (
diff --git a/tests/acceptance/test_prometheus_rocket.py b/tests/acceptance/test_prometheus_rocket.py
new file mode 100644
index 000000000..cc7c64141
--- /dev/null
+++ b/tests/acceptance/test_prometheus_rocket.py
@@ -0,0 +1,70 @@
+from rocketpy import Flight
+from rocketpy.simulation.flight_data_importer import FlightDataImporter
+
+
+def test_prometheus_rocket_data_asserts_acceptance(
+    environment_spaceport_america_2023, prometheus_rocket
+):
+    """Tests the Prometheus rocket flight data against acceptance criteria.
+
+    This function simulates a rocket flight using the given environment and
+    rocket parameters, then compares the simulated apogee with real flight data
+    to ensure the relative error is within acceptable thresholds.
+
+    Parameters
+    ----------
+    environment_spaceport_america_2023 : Environment
+        An environment configuration for Spaceport America in 2023.
+    prometheus_rocket : Rocket
+        The Prometheus rocket configuration.
+
+    Raises
+    ------
+    AssertionError
+        If the relative error between the simulated apogee and the real apogee
+        exceeds the threshold.
+    """
+    # Define relative error threshold (defined manually based on data)
+    apogee_threshold = 7.5 / 100
+
+    # Simulate the flight
+    test_flight = Flight(
+        rocket=prometheus_rocket,
+        environment=environment_spaceport_america_2023,
+        inclination=80,
+        heading=75,
+        rail_length=5.18,
+    )
+
+    # Read the flight data
+    columns_map = {
+        "time": "time",
+        "altitude": "z",
+        "height": "altitude",
+        "acceleration": "acceleration",
+        "pressure": "pressure",
+        "accel_x": "ax",
+        "accel_y": "ay",
+        "accel_z": "az",
+        "latitude": "latitude",
+        "longitude": "longitude",
+    }
+
+    altimeter_data = FlightDataImporter(
+        name="Telemetry Mega",
+        paths="data/prometheus/2022-06-24-serial-5115-flight-0001-TeleMetrum.csv",
+        columns_map=columns_map,
+        units=None,
+        interpolation="linear",
+        extrapolation="zero",
+        delimiter=",",
+        encoding="utf-8",
+    )
+
+    # Calculate errors and assert values
+    real_apogee = altimeter_data.altitude.max
+    rocketpy_apogee = test_flight.apogee - test_flight.env.elevation
+    a_error = abs(real_apogee - rocketpy_apogee)
+    r_error = a_error / real_apogee
+
+    assert r_error < apogee_threshold, f"Apogee relative error is {r_error*100:.2f}%"
diff --git a/tests/conftest.py b/tests/conftest.py
index e8eda67ce..6c4171b66 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,5 +1,6 @@
 import pytest
 
+# Pytest configuration
 pytest_plugins = [
     "tests.fixtures.environment.environment_fixtures",
     "tests.fixtures.flight.flight_fixtures",
@@ -13,6 +14,9 @@
     "tests.fixtures.rockets.rocket_fixtures",
     "tests.fixtures.surfaces.surface_fixtures",
     "tests.fixtures.units.numerical_fixtures",
+    "tests.fixtures.monte_carlo.monte_carlo_fixtures",
+    "tests.fixtures.monte_carlo.stochastic_fixtures",
+    "tests.fixtures.monte_carlo.stochastic_motors_fixtures",
     "tests.fixtures.sensors.sensors_fixtures",
 ]
 
diff --git a/tests/fixtures/environment/environment_fixtures.py b/tests/fixtures/environment/environment_fixtures.py
index 851be3203..312401d6c 100644
--- a/tests/fixtures/environment/environment_fixtures.py
+++ b/tests/fixtures/environment/environment_fixtures.py
@@ -71,3 +71,30 @@ def env_analysis():
     )
 
     return env_analysis
+
+
+@pytest.fixture
+def environment_spaceport_america_2023():
+    """Creates an Environment object for Spaceport America with a 2023 launch
+    conditions.
+
+    Returns
+    -------
+    rocketpy.Environment
+        Environment object configured for Spaceport America in 2023.
+    """
+    env = Environment(
+        latitude=32.939377,
+        longitude=-106.911986,
+        elevation=1401,
+    )
+    env.set_date(date=(2023, 6, 24, 9), timezone="America/Denver")
+
+    env.set_atmospheric_model(
+        type="Reanalysis",
+        file="data/weather/spaceport_america_pressure_levels_2023_hourly.nc",
+        dictionary="ECMWF",
+    )
+
+    env.max_expected_height = 6000
+    return env
diff --git a/tests/fixtures/dispersion/Valetudo_inputs.csv b/tests/fixtures/monte_carlo/Valetudo_inputs.csv
similarity index 100%
rename from tests/fixtures/dispersion/Valetudo_inputs.csv
rename to tests/fixtures/monte_carlo/Valetudo_inputs.csv
diff --git a/tests/fixtures/monte_carlo/__init__.py b/tests/fixtures/monte_carlo/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/tests/fixtures/monte_carlo/example.inputs.txt b/tests/fixtures/monte_carlo/example.inputs.txt
new file mode 100644
index 000000000..d82cae696
--- /dev/null
+++ b/tests/fixtures/monte_carlo/example.inputs.txt
@@ -0,0 +1,10 @@
+{"elevation": 1401.4956352929128, "gravity": "'Function from R1 to R1 : (height (m)) \u2192 (gravity (m/s\u00b2))'", "latitude": 32.990254, "longitude": -106.974998, "wind_velocity_x_factor": 0.9450816780482028, "wind_velocity_y_factor": 0.9781441848266635, "datum": "WGS84", "timezone": "UTC", "radius": 0.0635062964327075, "mass": 15.908580991806707, "I_11_without_motor": 6.321, "I_22_without_motor": 6.322114874292384, "I_33_without_motor": 0.012957242330574877, "I_12_without_motor": 0, "I_13_without_motor": 0, "I_23_without_motor": 0, "power_off_drag": "'Function from R1 to R1 : (Mach Number) \u2192 (Drag Coefficient with Power Off)'", "power_on_drag": "'Function from R1 to R1 : (Mach Number) \u2192 (Drag Coefficient with Power On)'", "power_off_drag_factor": 1.0, "power_on_drag_factor": 1.0, "center_of_mass_without_motor": 0.0, "coordinate_system_orientation": "tail_to_nose", "parachutes": [{"cd_s": 10.116998067339784, "trigger": "<function calisto_main_parachute_trigger.<locals>.main_trigger at 0x7814fd01cfe0>", "sampling_rate": 105, "lag": 1.6280833219672366, "noise": [0, 8.3, 0.5], "name": "calisto_main_chute"}, {"cd_s": 1.0177025917838693, "trigger": "<function calisto_drogue_parachute_trigger.<locals>.drogue_trigger at 0x7814fd01c540>", "sampling_rate": 105, "lag": 1.0967003213742696, "noise": [0, 8.3, 0.5], "name": "calisto_drogue_chute"}], "motors": [{"thrust_source": "'Function from R1 to R1 : (Scalar) \u2192 (Scalar)'", "total_impulse": 8008.347921291322, "burn_start_time": 0, "burn_out_time": 3.906214754528265, "dry_mass": 1.815, "dry_I_11": 0.125, "dry_I_22": 0.125, "dry_I_33": 0.002, "dry_I_12": 0, "dry_I_13": 0, "dry_I_23": 0, "nozzle_radius": 0.03293120513502925, "grain_number": 5, "grain_density": 1854.2340720665204, "grain_outer_radius": 0.032985640020247765, "grain_initial_inner_radius": 0.015310123275236702, "grain_initial_height": 0.11811825300572186, "grain_separation": 0.006711096958736968, "grains_center_of_mass_position": 0.39647964588403434, "center_of_dry_mass_position": 0.317, "nozzle_position": 0.0013349636505807958, "throat_radius": 0.010921423639193314, "interpolate": "linear", "coordinate_system_orientation": "nozzle_to_combustion_chamber", "position": -1.3720479424144372}], "aerodynamic_surfaces": [{"length": 0.5578974370049176, "kind": "vonkarman", "base_radius": 0.0635, "bluffness": null, "rocket_radius": 0.0635, "name": "calisto_nose_cone", "position": 1.1358373309953151}, {"n": 4, "root_chord": 0.11974359643195065, "tip_chord": 0.03940879564813866, "span": 0.10000563733372181, "rocket_radius": 0.0635, "cant_angle": 0, "sweep_length": 0.07999999999999999, "sweep_angle": null, "airfoil": null, "name": "calisto_trapezoidal_fins", "position": -1.1674848464453782}, {"top_radius": 0.0629442823276734, "bottom_radius": 0.044000809597868056, "length": 0.060919598903432425, "rocket_radius": 0.0635, "name": "calisto_tail", "position": -1.313}], "rail_buttons": [{"buttons_distance": 0.6979653598166442, "angular_position": 45, "name": "Rail Buttons", "lower_button_position": -0.6191976129185146, "upper_button_position": 0.0787677468981296}], "rail_length": 5.2, "inclination": 85.41806990321825, "heading": 54.18109302296489}
+{"elevation": 1406.5350756913592, "gravity": "'Function from R1 to R1 : (height (m)) \u2192 (gravity (m/s\u00b2))'", "latitude": 32.990254, "longitude": -106.974998, "wind_velocity_x_factor": 0.9516662861966597, "wind_velocity_y_factor": 1.0064048593297057, "datum": "WGS84", "timezone": "UTC", "radius": 0.06350349167738431, "mass": 15.768610173003173, "I_11_without_motor": 6.321, "I_22_without_motor": 6.315825792646666, "I_33_without_motor": 0.028629613565978755, "I_12_without_motor": 0, "I_13_without_motor": 0, "I_23_without_motor": 0, "power_off_drag": "'Function from R1 to R1 : (Mach Number) \u2192 (Drag Coefficient with Power Off)'", "power_on_drag": "'Function from R1 to R1 : (Mach Number) \u2192 (Drag Coefficient with Power On)'", "power_off_drag_factor": 1.0, "power_on_drag_factor": 1.0, "center_of_mass_without_motor": 0.0, "coordinate_system_orientation": "tail_to_nose", "parachutes": [{"cd_s": 9.89730766328184, "trigger": "<function calisto_main_parachute_trigger.<locals>.main_trigger at 0x7814fd01cfe0>", "sampling_rate": 105, "lag": 1.4899191353962622, "noise": [0, 8.3, 0.5], "name": "calisto_main_chute"}, {"cd_s": 0.9607265553248231, "trigger": "<function calisto_drogue_parachute_trigger.<locals>.drogue_trigger at 0x7814fd01c540>", "sampling_rate": 105, "lag": 1.4523711630490321, "noise": [0, 8.3, 0.5], "name": "calisto_drogue_chute"}], "motors": [{"thrust_source": "'Function from R1 to R1 : (Scalar) \u2192 (Scalar)'", "total_impulse": 6446.57135198394, "burn_start_time": 0, "burn_out_time": 3.9894949335022, "dry_mass": 1.815, "dry_I_11": 0.125, "dry_I_22": 0.125, "dry_I_33": 0.002, "dry_I_12": 0, "dry_I_13": 0, "dry_I_23": 0, "nozzle_radius": 0.03320688298961293, "grain_number": 5, "grain_density": 1909.5604610821972, "grain_outer_radius": 0.0324705584521942, "grain_initial_inner_radius": 0.014811951142584205, "grain_initial_height": 0.11731380337585026, "grain_separation": 0.00491393364215582, "grains_center_of_mass_position": 0.39628551738684287, "center_of_dry_mass_position": 0.317, "nozzle_position": 0.0007868629707592146, "throat_radius": 0.01060574995942289, "interpolate": "linear", "coordinate_system_orientation": "nozzle_to_combustion_chamber", "position": -1.3735008381135014}], "aerodynamic_surfaces": [{"length": 0.5585570098911449, "kind": "vonkarman", "base_radius": 0.0635, "bluffness": null, "rocket_radius": 0.0635, "name": "calisto_nose_cone", "position": 1.132236295583569}, {"n": 4, "root_chord": 0.11988524950598159, "tip_chord": 0.039971120565612084, "span": 0.09991375118669615, "rocket_radius": 0.0635, "cant_angle": 0, "sweep_length": 0.07999999999999999, "sweep_angle": null, "airfoil": null, "name": "calisto_trapezoidal_fins", "position": -1.168340642420532}, {"top_radius": 0.06366749282692026, "bottom_radius": 0.04247035278896944, "length": 0.05982474727356781, "rocket_radius": 0.0635, "name": "calisto_tail", "position": -1.313}], "rail_buttons": [{"buttons_distance": 0.6981342606544769, "angular_position": 45, "name": "Rail Buttons", "lower_button_position": -0.6165145493073986, "upper_button_position": 0.08161971134707835}], "rail_length": 5.2, "inclination": 86.94780910509066, "heading": 53.98156443958248}
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diff --git a/tests/fixtures/monte_carlo/example.outputs.txt b/tests/fixtures/monte_carlo/example.outputs.txt
new file mode 100644
index 000000000..ffc0f5548
--- /dev/null
+++ b/tests/fixtures/monte_carlo/example.outputs.txt
@@ -0,0 +1,10 @@
+{"lateral_surface_wind": 0.0, "apogee_x": 418.0900192341263, "apogee_time": 29.227877417373804, "max_mach_number": 1.0597636981635778, "apogee": 5690.287437226489, "x_impact": 480.48559284729896, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.28886753090850337, "out_of_rail_velocity": 25.983654528478493, "y_impact": 346.7826493888511, "apogee_y": 301.74630214056145, "impact_velocity": -5.371608743357084, "t_final": 353.87686346458946}
+{"lateral_surface_wind": 0.0, "apogee_x": 664.8205729246815, "apogee_time": 26.40800619077295, "max_mach_number": 0.8577562337266057, "apogee": 4715.816960792063, "x_impact": 774.0891149671631, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.3285641180798137, "out_of_rail_velocity": 22.82061718874699, "y_impact": 562.7937790273377, "apogee_y": 483.3484727242321, "impact_velocity": -5.408315380727355, "t_final": 299.60847406715055}
+{"lateral_surface_wind": 0.0, "apogee_x": 766.3125531509313, "apogee_time": 27.926605808862806, "max_mach_number": 0.9775271452143771, "apogee": 5333.672919610753, "x_impact": 884.994696596615, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.3436250275216524, "out_of_rail_velocity": 27.626343866105426, "y_impact": 559.8829519991676, "apogee_y": 484.798733226189, "impact_velocity": -5.497690913213444, "t_final": 327.7157423960461}
+{"lateral_surface_wind": 0.0, "apogee_x": 587.5317254837414, "apogee_time": 28.782471451734626, "max_mach_number": 1.0199401850539194, "apogee": 5506.343181861931, "x_impact": 686.5316364540121, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.29597291668803427, "out_of_rail_velocity": 25.323284778536475, "y_impact": 488.7776245777793, "apogee_y": 418.2923812342386, "impact_velocity": -5.411864875130086, "t_final": 333.08817486926347}
+{"lateral_surface_wind": 0.0, "apogee_x": 574.3435227488437, "apogee_time": 27.657740448471746, "max_mach_number": 0.9499674698056779, "apogee": 5222.770164417492, "x_impact": 669.7873944157898, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.35454649267427035, "out_of_rail_velocity": 26.79571219168167, "y_impact": 547.7994529511036, "apogee_y": 469.7336805974083, "impact_velocity": -5.3642688614023, "t_final": 325.6947684429422}
+{"lateral_surface_wind": 0.0, "apogee_x": 617.4055133432199, "apogee_time": 27.860776577624453, "max_mach_number": 0.9391624608249222, "apogee": 5165.427839134199, "x_impact": 715.9015528056536, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.31178728761821195, "out_of_rail_velocity": 24.067906801593168, "y_impact": 527.6424058896348, "apogee_y": 455.044172305862, "impact_velocity": -5.467639886548914, "t_final": 314.140756080289}
+{"lateral_surface_wind": 0.0, "apogee_x": 463.7203499996117, "apogee_time": 27.173024195105338, "max_mach_number": 0.8879882772048172, "apogee": 4936.646625623801, "x_impact": 543.9667463996028, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.3262013366369224, "out_of_rail_velocity": 22.993879265630007, "y_impact": 423.8593982789621, "apogee_y": 361.32615557055516, "impact_velocity": -5.431124330631135, "t_final": 307.92373590017286}
+{"lateral_surface_wind": 0.0, "apogee_x": 415.0946170176034, "apogee_time": 26.158939945211348, "max_mach_number": 0.8302455031820458, "apogee": 4621.646237220374, "x_impact": 489.5625692055425, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.3353263159726264, "out_of_rail_velocity": 22.35481535832323, "y_impact": 374.56318197644185, "apogee_y": 317.5838766916845, "impact_velocity": -5.3972844384921, "t_final": 291.01036623249445}
+{"lateral_surface_wind": 0.0, "apogee_x": 466.8917957287704, "apogee_time": 26.612259607079338, "max_mach_number": 0.862939429135814, "apogee": 4750.199442755109, "x_impact": 552.5208903404148, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.3298597000284287, "out_of_rail_velocity": 22.740120701870772, "y_impact": 389.6042530941056, "apogee_y": 329.218827701524, "impact_velocity": -5.2978952420899, "t_final": 302.0154671206384}
+{"lateral_surface_wind": 0.0, "apogee_x": 230.54329163654137, "apogee_time": 21.045450434487567, "max_mach_number": 0.5800585300053369, "apogee": 3303.1748009382363, "x_impact": 284.76193579684883, "frontal_surface_wind": 0.0, "out_of_rail_time": 0.4028036449544367, "out_of_rail_velocity": 18.60552705484144, "y_impact": 217.08948166662054, "apogee_y": 175.75266710831295, "impact_velocity": -5.2650912092579425, "t_final": 226.12896807596684}
diff --git a/tests/fixtures/monte_carlo/monte_carlo_fixtures.py b/tests/fixtures/monte_carlo/monte_carlo_fixtures.py
new file mode 100644
index 000000000..c25a95188
--- /dev/null
+++ b/tests/fixtures/monte_carlo/monte_carlo_fixtures.py
@@ -0,0 +1,34 @@
+"""Defines the fixtures for the Monte Carlo tests. The fixtures should be
+instances of the MonteCarlo class, ideally."""
+
+import pytest
+
+from rocketpy.simulation import MonteCarlo
+
+
+@pytest.fixture
+def monte_carlo_calisto(stochastic_environment, stochastic_calisto, stochastic_flight):
+    """Creates a MonteCarlo object with the stochastic environment, stochastic
+    calisto and stochastic flight.
+
+    Parameters
+    ----------
+    stochastic_environment : StochasticEnvironment
+        The stochastic environment object, this is a pytest fixture.
+    stochastic_calisto : StochasticRocket
+        The stochastic rocket object, this is a pytest fixture.
+    stochastic_flight : StochasticFlight
+        The stochastic flight object, this is a pytest fixture.
+
+    Returns
+    -------
+    MonteCarlo
+        The MonteCarlo object with the stochastic environment, stochastic
+        calisto and stochastic flight.
+    """
+    return MonteCarlo(
+        filename="monte_carlo_test",
+        environment=stochastic_environment,
+        rocket=stochastic_calisto,
+        flight=stochastic_flight,
+    )
diff --git a/tests/fixtures/monte_carlo/stochastic_fixtures.py b/tests/fixtures/monte_carlo/stochastic_fixtures.py
new file mode 100644
index 000000000..bf576e5ed
--- /dev/null
+++ b/tests/fixtures/monte_carlo/stochastic_fixtures.py
@@ -0,0 +1,236 @@
+"""This module contains fixtures for the stochastic module. The fixtures are
+used to test the stochastic objects that will be used in the Monte Carlo
+simulations. It is a team effort to keep it as documented as possible."""
+
+import pytest
+
+from rocketpy.stochastic import (
+    StochasticEnvironment,
+    StochasticFlight,
+    StochasticNoseCone,
+    StochasticParachute,
+    StochasticRailButtons,
+    StochasticRocket,
+    StochasticTail,
+    StochasticTrapezoidalFins,
+)
+
+
+@pytest.fixture
+def stochastic_environment(example_spaceport_env):
+    """This fixture is used to create a stochastic environment object for the
+    Calisto flight.
+
+    Parameters
+    ----------
+    example_spaceport_env : Environment
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticEnvironment
+        The stochastic environment object
+    """
+    return StochasticEnvironment(
+        environment=example_spaceport_env,
+        elevation=(1400, 10, "normal"),
+        gravity=None,
+        latitude=None,
+        longitude=None,
+        ensemble_member=None,
+        wind_velocity_x_factor=(1.0, 0.033, "normal"),
+        wind_velocity_y_factor=(1.0, 0.033, "normal"),
+    )
+
+
+@pytest.fixture
+def stochastic_nose_cone(calisto_nose_cone):
+    """This fixture is used to create a StochasticNoseCone object for the
+    Calisto rocket.
+
+    Parameters
+    ----------
+    calisto_nose_cone : NoseCone
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticNoseCone
+        The stochastic nose cone object
+    """
+    return StochasticNoseCone(
+        nosecone=calisto_nose_cone,
+        length=0.001,
+    )
+
+
+@pytest.fixture
+def stochastic_trapezoidal_fins(calisto_trapezoidal_fins):
+    """This fixture is used to create a StochasticTrapezoidalFins object for the
+    Calisto rocket.
+
+    Parameters
+    ----------
+    calisto_trapezoidal_fins : TrapezoidalFins
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticTrapezoidalFins
+        The stochastic trapezoidal fins object
+    """
+    return StochasticTrapezoidalFins(
+        trapezoidal_fins=calisto_trapezoidal_fins,
+        root_chord=0.0005,
+        tip_chord=0.0005,
+        span=0.0005,
+    )
+
+
+@pytest.fixture
+def stochastic_tail(calisto_tail):
+    """This fixture is used to create a StochasticTail object for the
+    Calisto rocket.
+
+    Parameters
+    ----------
+    calisto_tail : Tail
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticTail
+        The stochastic tail object
+    """
+    return StochasticTail(
+        tail=calisto_tail,
+        top_radius=0.001,
+        bottom_radius=0.001,
+        length=0.001,
+    )
+
+
+@pytest.fixture
+def stochastic_rail_buttons(calisto_rail_buttons):
+    """This fixture is used to create a StochasticRailButtons object for the
+    Calisto rocket.
+
+    Parameters
+    ----------
+    calisto_rail_buttons : RailButtons
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticRailButtons
+        The stochastic rail buttons object
+    """
+    return StochasticRailButtons(
+        rail_buttons=calisto_rail_buttons, buttons_distance=0.001
+    )
+
+
+@pytest.fixture
+def stochastic_main_parachute(calisto_main_chute):
+    """This fixture is used to create a StochasticParachute object for the
+    Calisto rocket.
+
+    Parameters
+    ----------
+    calisto_main_chute : Parachute
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticParachute
+        The stochastic parachute object
+    """
+    return StochasticParachute(
+        parachute=calisto_main_chute,
+        cd_s=0.1,
+        lag=0.1,
+    )
+
+
+@pytest.fixture
+def stochastic_drogue_parachute(calisto_drogue_chute):
+    """This fixture is used to create a StochasticParachute object for the
+    Calisto rocket. This time, the drogue parachute is created.
+
+    Parameters
+    ----------
+    calisto_drogue_chute : Parachute
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticParachute
+        The stochastic parachute object
+    """
+    return StochasticParachute(
+        parachute=calisto_drogue_chute,
+        cd_s=0.07,
+        lag=0.2,
+    )
+
+
+@pytest.fixture
+def stochastic_calisto(
+    calisto_robust,
+    stochastic_nose_cone,
+    stochastic_trapezoidal_fins,
+    stochastic_tail,
+    stochastic_solid_motor,
+    stochastic_rail_buttons,
+    stochastic_main_parachute,
+    stochastic_drogue_parachute,
+):
+    """This fixture creates a StochasticRocket object for the Calisto rocket.
+    The fixture will already have the stochastic nose cone, trapezoidal fins,
+    tail, solid motor, rail buttons, main parachute, and drogue parachute.
+
+    Returns
+    -------
+    StochasticRocket
+        The stochastic rocket object
+    """
+    rocket = StochasticRocket(
+        rocket=calisto_robust,
+        radius=0.0127 / 2000,
+        mass=(15.426, 0.5, "normal"),
+        inertia_11=(6.321, 0),
+        inertia_22=0.01,
+        inertia_33=0.01,
+        center_of_mass_without_motor=0,
+    )
+    rocket.add_motor(stochastic_solid_motor, position=0.001)
+    rocket.add_nose(stochastic_nose_cone, position=(1.134, 0.001))
+    rocket.add_trapezoidal_fins(stochastic_trapezoidal_fins, position=(0.001, "normal"))
+    rocket.add_tail(stochastic_tail)
+    rocket.set_rail_buttons(
+        stochastic_rail_buttons, lower_button_position=(-0.618, 0.001, "normal")
+    )
+    rocket.add_parachute(stochastic_main_parachute)
+    rocket.add_parachute(stochastic_drogue_parachute)
+    return rocket
+
+
+@pytest.fixture
+def stochastic_flight(flight_calisto_robust):
+    """This fixture creates a StochasticFlight object for the Calisto flight.
+
+    Parameters
+    ----------
+    flight_calisto_robust : Flight
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticFlight
+        The stochastic flight object
+    """
+    return StochasticFlight(
+        flight=flight_calisto_robust,
+        inclination=(84.7, 1),
+        heading=(53, 2),
+    )
diff --git a/tests/fixtures/monte_carlo/stochastic_motors_fixtures.py b/tests/fixtures/monte_carlo/stochastic_motors_fixtures.py
new file mode 100644
index 000000000..9bc46de16
--- /dev/null
+++ b/tests/fixtures/monte_carlo/stochastic_motors_fixtures.py
@@ -0,0 +1,78 @@
+"""This module contains fixtures for the stochastic motors tests."""
+
+import pytest
+
+from rocketpy.mathutils.function import Function
+from rocketpy.stochastic import StochasticGenericMotor, StochasticSolidMotor
+
+
+@pytest.fixture
+def stochastic_solid_motor(cesaroni_m1670):
+    """A Stochastic Solid Motor fixture for the Cesaroni M1670 motor.
+
+    Parameters
+    ----------
+    cesaroni_m1670 : SolidMotor
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticSolidMotor
+        The stochastic solid motor object.
+    """
+    return StochasticSolidMotor(
+        solid_motor=cesaroni_m1670,
+        thrust_source=[
+            "data/motors/Cesaroni_M1670.eng",
+            [[0, 6000], [1, 6000], [2, 6000], [3, 6000], [4, 6000]],
+            Function([[0, 6000], [1, 6000], [2, 6000], [3, 6000], [4, 6000]]),
+        ],
+        burn_out_time=(4, 0.1),
+        grains_center_of_mass_position=0.001,
+        grain_density=50,
+        grain_separation=1 / 1000,
+        grain_initial_height=1 / 1000,
+        grain_initial_inner_radius=0.375 / 1000,
+        grain_outer_radius=0.375 / 1000,
+        total_impulse=(6500, 1000),
+        throat_radius=0.5 / 1000,
+        nozzle_radius=0.5 / 1000,
+        nozzle_position=0.001,
+    )
+
+
+@pytest.fixture
+def stochastic_generic_motor(generic_motor):
+    """A Stochastic Generic Motor fixture
+
+    Parameters
+    ----------
+    generic_motor : GenericMotor
+        This is another fixture.
+
+    Returns
+    -------
+    StochasticGenericMotor
+        The stochastic generic motor object.
+    """
+    return StochasticGenericMotor(
+        generic_motor,
+        thrust_source=None,
+        total_impulse=None,
+        burn_start_time=None,
+        burn_out_time=None,
+        propellant_initial_mass=None,
+        dry_mass=None,
+        dry_inertia_11=None,
+        dry_inertia_22=None,
+        dry_inertia_33=None,
+        dry_inertia_12=None,
+        dry_inertia_13=None,
+        dry_inertia_23=None,
+        chamber_radius=None,
+        chamber_height=(0.5, 0.005),
+        chamber_position=None,
+        nozzle_radius=None,
+        nozzle_position=None,
+        center_of_dry_mass_position=None,
+    )
diff --git a/tests/fixtures/motor/generic_motor_fixtures.py b/tests/fixtures/motor/generic_motor_fixtures.py
index 925716cb5..24a484bd1 100644
--- a/tests/fixtures/motor/generic_motor_fixtures.py
+++ b/tests/fixtures/motor/generic_motor_fixtures.py
@@ -28,3 +28,27 @@ def generic_motor():
     )
 
     return motor
+
+
+@pytest.fixture
+def generic_motor_cesaroni_M1520():
+    """Defines a Cesaroni M1520 motor for the Prometheus rocket using the
+    GenericMotor class.
+
+    Returns
+    -------
+    GenericMotor
+        The Cesaroni M1520 motor for the Prometheus rocket.
+    """
+    return GenericMotor(
+        # burn specs: https://www.thrustcurve.org/simfiles/5f4294d20002e900000006b1/
+        thrust_source="data/motors/cesaroni/Cesaroni_7579M1520-P.eng",
+        burn_time=4.897,
+        propellant_initial_mass=3.737,
+        dry_mass=2.981,
+        # casing specs: Pro98 3G Gen2 casing
+        chamber_radius=0.064,
+        chamber_height=0.548,
+        chamber_position=0.274,
+        nozzle_radius=0.027,
+    )
diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index a973e433b..34fd93137 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -1,3 +1,4 @@
+import numpy as np
 import pytest
 
 from rocketpy import Rocket
@@ -307,3 +308,81 @@ def dimensionless_calisto(kg, m, dimensionless_cesaroni_m1670):
     )
     example_rocket.add_motor(dimensionless_cesaroni_m1670, position=(-1.373) * m)
     return example_rocket
+
+
+@pytest.fixture
+def prometheus_rocket(generic_motor_cesaroni_M1520):
+    """Create a simple object of the Rocket class to be used in the tests. This
+    is the Prometheus rocket, a rocket documented in the Flight Examples section
+    of the RocketPy documentation.
+
+    Parameters
+    ----------
+    generic_motor_cesaroni_M1520 : GenericMotor
+        An object of the GenericMotor class. This is a pytest fixture too.
+    """
+
+    def prometheus_cd_at_ma(mach):
+        """Gives the drag coefficient of the rocket at a given mach number."""
+        if mach <= 0.15:
+            return 0.422
+        elif mach <= 0.45:
+            return 0.422 + (mach - 0.15) * (0.38 - 0.422) / (0.45 - 0.15)
+        elif mach <= 0.77:
+            return 0.38 + (mach - 0.45) * (0.32 - 0.38) / (0.77 - 0.45)
+        elif mach <= 0.82:
+            return 0.32 + (mach - 0.77) * (0.3 - 0.32) / (0.82 - 0.77)
+        elif mach <= 0.88:
+            return 0.3 + (mach - 0.82) * (0.3 - 0.3) / (0.88 - 0.82)
+        elif mach <= 0.94:
+            return 0.3 + (mach - 0.88) * (0.32 - 0.3) / (0.94 - 0.88)
+        elif mach <= 0.99:
+            return 0.32 + (mach - 0.94) * (0.37 - 0.32) / (0.99 - 0.94)
+        elif mach <= 1.04:
+            return 0.37 + (mach - 0.99) * (0.44 - 0.37) / (1.04 - 0.99)
+        elif mach <= 1.24:
+            return 0.44 + (mach - 1.04) * (0.43 - 0.44) / (1.24 - 1.04)
+        elif mach <= 1.33:
+            return 0.43 + (mach - 1.24) * (0.42 - 0.43) / (1.33 - 1.24)
+        elif mach <= 1.49:
+            return 0.42 + (mach - 1.33) * (0.39 - 0.42) / (1.49 - 1.33)
+        else:
+            return 0.39
+
+    prometheus = Rocket(
+        radius=0.06985,  # 5.5" diameter circle
+        mass=13.93,
+        inertia=(
+            4.87,
+            4.87,
+            0.05,
+        ),
+        power_off_drag=prometheus_cd_at_ma,
+        power_on_drag=lambda x: prometheus_cd_at_ma(x) * 1.02,  # 5% increase in drag
+        center_of_mass_without_motor=0.9549,
+        coordinate_system_orientation="tail_to_nose",
+    )
+
+    prometheus.set_rail_buttons(0.69, 0.21, 60)
+
+    prometheus.add_motor(motor=generic_motor_cesaroni_M1520, position=0)
+    nose_cone = prometheus.add_nose(length=0.742, kind="Von Karman", position=2.229)
+    fin_set = prometheus.add_trapezoidal_fins(
+        n=3,
+        span=0.13,
+        root_chord=0.268,
+        tip_chord=0.136,
+        position=0.273,
+        sweep_length=0.066,
+    )
+    drogue_chute = prometheus.add_parachute(
+        "Drogue",
+        cd_s=1.6 * np.pi * 0.3048**2,  # Cd = 1.6, D_chute = 24 in
+        trigger="apogee",
+    )
+    main_chute = prometheus.add_parachute(
+        "Main",
+        cd_s=2.2 * np.pi * 0.9144**2,  # Cd = 2.2, D_chute = 72 in
+        trigger=457.2,  # 1500 ft
+    )
+    return prometheus
diff --git a/tests/test_flight.py b/tests/test_flight.py
index 4fb4036eb..fb203b3af 100644
--- a/tests/test_flight.py
+++ b/tests/test_flight.py
@@ -618,11 +618,11 @@ def test_max_values(flight_calisto_robust):
         regarding this pytest fixture.
     """
     test = flight_calisto_robust
-    atol = 1e-2
-    assert pytest.approx(105.2774, abs=atol) == test.max_acceleration_power_on
-    assert pytest.approx(105.2774, abs=atol) == test.max_acceleration
-    assert pytest.approx(0.85999, abs=atol) == test.max_mach_number
-    assert pytest.approx(285.94948, abs=atol) == test.max_speed
+    rtol = 5e-3
+    assert pytest.approx(105.1599, rel=rtol) == test.max_acceleration_power_on
+    assert pytest.approx(105.1599, rel=rtol) == test.max_acceleration
+    assert pytest.approx(0.85999, rel=rtol) == test.max_mach_number
+    assert pytest.approx(285.94948, rel=rtol) == test.max_speed
 
 
 def test_rail_buttons_forces(flight_calisto_custom_wind):
@@ -640,10 +640,10 @@ def test_rail_buttons_forces(flight_calisto_custom_wind):
     """
     test = flight_calisto_custom_wind
     atol = 5e-3
-    assert pytest.approx(3.80358, abs=atol) == test.max_rail_button1_normal_force
-    assert pytest.approx(1.63602, abs=atol) == test.max_rail_button1_shear_force
-    assert pytest.approx(1.19353, abs=atol) == test.max_rail_button2_normal_force
-    assert pytest.approx(0.51337, abs=atol) == test.max_rail_button2_shear_force
+    assert pytest.approx(3.833613, abs=atol) == test.max_rail_button1_normal_force
+    assert pytest.approx(1.648938, abs=atol) == test.max_rail_button1_shear_force
+    assert pytest.approx(1.165307, abs=atol) == test.max_rail_button2_normal_force
+    assert pytest.approx(0.501229, abs=atol) == test.max_rail_button2_shear_force
 
 
 @pytest.mark.parametrize(
@@ -690,7 +690,7 @@ def test_accelerations(flight_calisto_custom_wind, flight_time, expected_values)
     [
         ("t_initial", (0, 0, 0)),
         ("out_of_rail_time", (0, 2.248727, 25.703072)),
-        ("apogee_time", (-13.209436, 16.05115, -0.000257)),
+        ("apogee_time", (-13.204789, 15.990903, -0.000138)),
         ("t_final", (5, 2, -5.65998)),
     ],
 )
@@ -728,7 +728,7 @@ def test_velocities(flight_calisto_custom_wind, flight_time, expected_values):
     [
         ("t_initial", (1.6542528, 0.65918, -0.067107)),
         ("out_of_rail_time", (5.05334, 2.01364, -1.7541)),
-        ("apogee_time", (2.35291, -1.8275, -0.87851)),
+        ("apogee_time", (2.366258, -1.830744, -0.875342)),
         ("t_final", (0, 0, 159.2212)),
     ],
 )
@@ -766,7 +766,7 @@ def test_aerodynamic_forces(flight_calisto_custom_wind, flight_time, expected_va
     "flight_time, expected_values",
     [
         ("t_initial", (0.17179073815516033, -0.431117, 0)),
-        ("out_of_rail_time", (0.547026, -1.3727895, 0)),
+        ("out_of_rail_time", (0.543760, -1.364593, 0)),
         ("apogee_time", (-0.5874848151271623, -0.7563596, 0)),
         ("t_final", (0, 0, 0)),
     ],
diff --git a/tests/test_function.py b/tests/test_function.py
index 2ce94f691..6f4122e47 100644
--- a/tests/test_function.py
+++ b/tests/test_function.py
@@ -102,7 +102,8 @@ def test_setters(func_from_csv, func_2d_from_csv):
     func_2d_from_csv.set_interpolation("shepard")
     assert func_2d_from_csv.get_interpolation_method() == "shepard"
     func_2d_from_csv.set_extrapolation("zero")
-    assert func_2d_from_csv.get_extrapolation_method() == "zero"
+    # 2d functions do not support zero extrapolation, must change to natural
+    assert func_2d_from_csv.get_extrapolation_method() == "natural"
 
 
 @patch("matplotlib.pyplot.show")
@@ -181,7 +182,32 @@ def test_extrapolation_methods(linear_func):
     assert linear_func.get_extrapolation_method() == "constant"
     assert np.isclose(linear_func.get_value(-1), 0, atol=1e-6)
 
-    # Test natural
+    # Test natural for linear interpolation
+    linear_func.set_interpolation("linear")
+    assert isinstance(linear_func.set_extrapolation("natural"), Function)
+    linear_func.set_extrapolation("natural")
+    assert isinstance(linear_func.get_extrapolation_method(), str)
+    assert linear_func.get_extrapolation_method() == "natural"
+    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
+
+    # Test natural for spline interpolation
+    linear_func.set_interpolation("spline")
+    assert isinstance(linear_func.set_extrapolation("natural"), Function)
+    linear_func.set_extrapolation("natural")
+    assert isinstance(linear_func.get_extrapolation_method(), str)
+    assert linear_func.get_extrapolation_method() == "natural"
+    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
+
+    # Test natural for akima interpolation
+    linear_func.set_interpolation("akima")
+    assert isinstance(linear_func.set_extrapolation("natural"), Function)
+    linear_func.set_extrapolation("natural")
+    assert isinstance(linear_func.get_extrapolation_method(), str)
+    assert linear_func.get_extrapolation_method() == "natural"
+    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
+
+    # Test natural for polynomial interpolation
+    linear_func.set_interpolation("polynomial")
     assert isinstance(linear_func.set_extrapolation("natural"), Function)
     linear_func.set_extrapolation("natural")
     assert isinstance(linear_func.get_extrapolation_method(), str)
diff --git a/tests/test_monte_carlo.py b/tests/test_monte_carlo.py
new file mode 100644
index 000000000..8142f91dd
--- /dev/null
+++ b/tests/test_monte_carlo.py
@@ -0,0 +1,171 @@
+import os
+from unittest.mock import patch
+
+import matplotlib as plt
+import numpy as np
+import pytest
+
+plt.rcParams.update({"figure.max_open_warning": 0})
+
+
+def test_stochastic_environment_create_object_with_wind_x(stochastic_environment):
+    """Tests the stochastic environment object by checking if the wind velocity
+    can be generated properly. The goal is to check if the create_object()
+    method is being called without any problems.
+
+    Parameters
+    ----------
+    stochastic_environment : StochasticEnvironment
+        The stochastic environment object, this is a pytest fixture.
+    """
+    wind_x_at_1000m = []
+    for _ in range(10):
+        random_env = stochastic_environment.create_object()
+        wind_x_at_1000m.append(random_env.wind_velocity_x(1000))
+
+    assert np.isclose(np.mean(wind_x_at_1000m), 0, atol=0.1)
+    assert np.isclose(np.std(wind_x_at_1000m), 0, atol=0.1)
+    # TODO: add a new test for the special case of ensemble member
+
+
+def test_stochastic_solid_motor_create_object_with_impulse(stochastic_solid_motor):
+    """Tests the stochastic solid motor object by checking if the total impulse
+    can be generated properly. The goal is to check if the create_object()
+    method is being called without any problems.
+
+    Parameters
+    ----------
+    stochastic_solid_motor : StochasticSolidMotor
+        The stochastic solid motor object, this is a pytest fixture.
+    """
+    total_impulse = []
+    for _ in range(20):
+        random_motor = stochastic_solid_motor.create_object()
+        total_impulse.append(random_motor.total_impulse)
+
+    assert np.isclose(np.mean(total_impulse), 6500, rtol=0.3)
+    assert np.isclose(np.std(total_impulse), 1000, rtol=0.3)
+
+
+def test_stochastic_calisto_create_object_with_static_margin(stochastic_calisto):
+    """Tests the stochastic calisto object by checking if the static margin
+    can be generated properly. The goal is to check if the create_object()
+    method is being called without any problems.
+
+    Parameters
+    ----------
+    stochastic_calisto : StochasticCalisto
+        The stochastic calisto object, this is a pytest fixture.
+    """
+
+    all_margins = []
+    for _ in range(10):
+        random_rocket = stochastic_calisto.create_object()
+        all_margins.append(random_rocket.static_margin(0))
+
+    assert np.isclose(np.mean(all_margins), 2.2625350013000434, rtol=0.15)
+    assert np.isclose(np.std(all_margins), 0.1, atol=0.2)
+
+
+@pytest.mark.slow
+def test_monte_carlo_simulate(monte_carlo_calisto):
+    """Tests the simulate method of the MonteCarlo class.
+
+    Parameters
+    ----------
+    monte_carlo_calisto : MonteCarlo
+        The MonteCarlo object, this is a pytest fixture.
+    """
+    # NOTE: this is really slow, it runs 10 flight simulations
+    monte_carlo_calisto.simulate(number_of_simulations=10, append=False)
+
+    assert monte_carlo_calisto.num_of_loaded_sims == 10
+    assert monte_carlo_calisto.number_of_simulations == 10
+    assert monte_carlo_calisto.filename == "monte_carlo_test"
+    assert monte_carlo_calisto.error_file == "monte_carlo_test.errors.txt"
+    assert monte_carlo_calisto.output_file == "monte_carlo_test.outputs.txt"
+    assert np.isclose(
+        monte_carlo_calisto.processed_results["apogee"][0], 4711, rtol=0.15
+    )
+    assert np.isclose(
+        monte_carlo_calisto.processed_results["impact_velocity"][0],
+        -5.234,
+        rtol=0.15,
+    )
+    os.remove("monte_carlo_test.errors.txt")
+    os.remove("monte_carlo_test.outputs.txt")
+    os.remove("monte_carlo_test.inputs.txt")
+
+
+def test_monte_carlo_set_inputs_log(monte_carlo_calisto):
+    """Tests the set_inputs_log method of the MonteCarlo class.
+
+    Parameters
+    ----------
+    monte_carlo_calisto : MonteCarlo
+        The MonteCarlo object, this is a pytest fixture.
+    """
+    monte_carlo_calisto.input_file = "tests/fixtures/monte_carlo/example.inputs.txt"
+    monte_carlo_calisto.set_inputs_log()
+    assert len(monte_carlo_calisto.inputs_log) == 10
+    assert all(isinstance(item, dict) for item in monte_carlo_calisto.inputs_log)
+    assert all(
+        "gravity" in item and "elevation" in item
+        for item in monte_carlo_calisto.inputs_log
+    )
+
+
+def test_monte_carlo_set_outputs_log(monte_carlo_calisto):
+    """Tests the set_outputs_log method of the MonteCarlo class.
+
+    Parameters
+    ----------
+    monte_carlo_calisto : MonteCarlo
+        The MonteCarlo object, this is a pytest fixture.
+    """
+    monte_carlo_calisto.output_file = "tests/fixtures/monte_carlo/example.outputs.txt"
+    monte_carlo_calisto.set_outputs_log()
+    assert len(monte_carlo_calisto.outputs_log) == 10
+    assert all(isinstance(item, dict) for item in monte_carlo_calisto.outputs_log)
+    assert all(
+        "apogee" in item and "impact_velocity" in item
+        for item in monte_carlo_calisto.outputs_log
+    )
+
+
+# def test_monte_carlo_set_errors_log(monte_carlo_calisto):
+#     monte_carlo_calisto.error_file = "tests/fixtures/monte_carlo/example.errors.txt"
+#     monte_carlo_calisto.set_errors_log()
+#     assert
+
+
+def test_monte_carlo_prints(monte_carlo_calisto):
+    """Tests the prints methods of the MonteCarlo class."""
+    monte_carlo_calisto.info()
+
+
+@patch("matplotlib.pyplot.show")
+def test_monte_carlo_plots(mock_show, monte_carlo_calisto):
+    """Tests the plots methods of the MonteCarlo class."""
+    assert monte_carlo_calisto.all_info() is None
+
+
+def test_monte_carlo_export_ellipses_to_kml(monte_carlo_calisto):
+    """Tests the export_ellipses_to_kml method of the MonteCarlo class.
+
+    Parameters
+    ----------
+    monte_carlo_calisto : MonteCarlo
+        The MonteCarlo object, this is a pytest fixture.
+    """
+    assert (
+        monte_carlo_calisto.export_ellipses_to_kml(
+            filename="monte_carlo_class_example.kml",
+            origin_lat=32,
+            origin_lon=-104,
+            type="impact",
+        )
+        is None
+    )
+
+    os.remove("monte_carlo_class_example.kml")
diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/tests/unit/stochastic/__init__.py b/tests/unit/stochastic/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/tests/unit/stochastic/test_stochastic_aero_surfaces.py b/tests/unit/stochastic/test_stochastic_aero_surfaces.py
new file mode 100644
index 000000000..d63feb76c
--- /dev/null
+++ b/tests/unit/stochastic/test_stochastic_aero_surfaces.py
@@ -0,0 +1,92 @@
+from rocketpy.rocket.aero_surface import NoseCone, RailButtons, Tail, TrapezoidalFins
+
+## NOSE CONE
+
+
+def test_stochastic_nose_cone_create_object(stochastic_nose_cone):
+    """Test create object method of StochasticNoseCone class.
+
+    This test checks if the create_object method of the StochasticNoseCone
+    class creates a StochasticNoseCone object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_nose_cone : StochasticNoseCone
+        StochasticNoseCone object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_nose_cone.create_object()
+    assert isinstance(obj, NoseCone)
+
+
+## TRAPEZOIDAL FINS
+
+
+def test_stochastic_trapezoidal_fins_create_object(stochastic_trapezoidal_fins):
+    """Test create object method of StochasticTrapezoidalFins class.
+
+    This test checks if the create_object method of the StochasticTrapezoidalFins
+    class creates a StochasticTrapezoidalFins object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_trapezoidal_fins : StochasticTrapezoidalFins
+        StochasticTrapezoidalFins object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_trapezoidal_fins.create_object()
+    assert isinstance(obj, TrapezoidalFins)
+
+
+## TAIL
+
+
+def test_stochastic_tail_create_object(stochastic_tail):
+    """Test create object method of StochasticTail class.
+
+    This test checks if the create_object method of the StochasticTail
+    class creates a StochasticTail object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_tail : StochasticTail
+        StochasticTail object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_tail.create_object()
+    assert isinstance(obj, Tail)
+
+
+## RAIL BUTTONS
+
+
+def test_stochastic_rail_buttons_create_object(stochastic_rail_buttons):
+    """Test create object method of StochasticRailButtons class.
+
+    This test checks if the create_object method of the StochasticRailButtons
+    class creates a StochasticRailButtons object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_rail_buttons : StochasticRailButtons
+        StochasticRailButtons object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_rail_buttons.create_object()
+    assert isinstance(obj, RailButtons)
diff --git a/tests/unit/stochastic/test_stochastic_environment.py b/tests/unit/stochastic/test_stochastic_environment.py
new file mode 100644
index 000000000..ce115fe05
--- /dev/null
+++ b/tests/unit/stochastic/test_stochastic_environment.py
@@ -0,0 +1,43 @@
+from rocketpy.environment.environment import Environment
+
+
+def test_str(stochastic_environment):
+    """Test __str__ method of StochasticEnvironment class.
+
+    This test checks if the __str__ method of the StochasticEnvironment class
+    returns a string without raising any exceptions.
+
+    Parameters
+    ----------
+    stochastic_environment : StochasticEnvironment
+        StochasticEnvironment object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    assert isinstance(str(stochastic_environment), str)
+
+
+# def test_validate_ensemble(stochastic_environment):
+#     print("Implement this later")
+
+
+def test_create_object(stochastic_environment):
+    """Test create object method of StochasticEnvironment class.
+
+    This test checks if the create_object method of the StochasticEnvironment
+    class creates a StochasticEnvironment object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_environment : StochasticEnvironment
+        StochasticEnvironment object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_environment.create_object()
+    assert isinstance(obj, Environment)
diff --git a/tests/unit/stochastic/test_stochastic_flight.py b/tests/unit/stochastic/test_stochastic_flight.py
new file mode 100644
index 000000000..aeb71b906
--- /dev/null
+++ b/tests/unit/stochastic/test_stochastic_flight.py
@@ -0,0 +1,6 @@
+from rocketpy.simulation.flight import Flight
+
+
+def test_stochastic_flight_create_object(stochastic_flight):
+    obj = stochastic_flight.create_object()
+    assert isinstance(obj, Flight)
diff --git a/tests/unit/stochastic/test_stochastic_motors.py b/tests/unit/stochastic/test_stochastic_motors.py
new file mode 100644
index 000000000..214772743
--- /dev/null
+++ b/tests/unit/stochastic/test_stochastic_motors.py
@@ -0,0 +1,6 @@
+from rocketpy.motors import GenericMotor
+
+
+def test_stochastic_generic_motor_create_object(stochastic_generic_motor):
+    obj = stochastic_generic_motor.create_object()
+    assert isinstance(obj, GenericMotor)
diff --git a/tests/unit/stochastic/test_stochastic_parachute.py b/tests/unit/stochastic/test_stochastic_parachute.py
new file mode 100644
index 000000000..09a1497f7
--- /dev/null
+++ b/tests/unit/stochastic/test_stochastic_parachute.py
@@ -0,0 +1,21 @@
+from rocketpy.rocket.parachute import Parachute
+
+
+def test_stochastic_parachute_create_object(stochastic_main_parachute):
+    """Test create object method of StochasticParachute class.
+
+    This test checks if the create_object method of the StochasticParachute
+    class creates a StochasticParachute object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_main_parachute : StochasticParachute
+        StochasticParachute object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_main_parachute.create_object()
+    assert isinstance(obj, Parachute)
diff --git a/tests/unit/stochastic/test_stochastic_rocket.py b/tests/unit/stochastic/test_stochastic_rocket.py
new file mode 100644
index 000000000..8306b6039
--- /dev/null
+++ b/tests/unit/stochastic/test_stochastic_rocket.py
@@ -0,0 +1,25 @@
+from rocketpy.rocket.rocket import Rocket
+
+
+def test_str(stochastic_calisto):
+    assert isinstance(str(stochastic_calisto), str)
+
+
+def test_create_object(stochastic_calisto):
+    """Test create object method of StochasticRocket class.
+
+    This test checks if the create_object method of the StochasticCalisto
+    class creates a StochasticCalisto object from the randomly generated
+    input arguments.
+
+    Parameters
+    ----------
+    stochastic_calisto : StochasticCalisto
+        StochasticCalisto object to be tested.
+
+    Returns
+    -------
+    None
+    """
+    obj = stochastic_calisto.create_object()
+    assert isinstance(obj, Rocket)
diff --git a/tests/unit/test_flight_time_nodes.py b/tests/unit/test_flight_time_nodes.py
new file mode 100644
index 000000000..10f6b6c30
--- /dev/null
+++ b/tests/unit/test_flight_time_nodes.py
@@ -0,0 +1,103 @@
+"""Module to test everything related to the TimeNodes class and it's subclass
+TimeNode.
+"""
+
+import pytest
+
+from rocketpy.rocket import Parachute, _Controller
+
+
+def test_time_nodes_init(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    assert len(time_nodes) == 0
+
+
+def test_time_nodes_getitem(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    time_nodes.add_node(1.0, [], [])
+    assert isinstance(time_nodes[0], flight_calisto.TimeNodes.TimeNode)
+    assert time_nodes[0].t == 1.0
+
+
+def test_time_nodes_len(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    assert len(time_nodes) == 0
+
+
+def test_time_nodes_add(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    example_node = flight_calisto.TimeNodes.TimeNode(1.0, [], [])
+    time_nodes.add(example_node)
+    assert len(time_nodes) == 1
+    assert isinstance(time_nodes[0], flight_calisto.TimeNodes.TimeNode)
+    assert time_nodes[0].t == 1.0
+
+
+def test_time_nodes_add_node(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    time_nodes.add_node(2.0, [], [])
+    assert len(time_nodes) == 1
+    assert time_nodes[0].t == 2.0
+    assert len(time_nodes[0].parachutes) == 0
+    assert len(time_nodes[0].callbacks) == 0
+
+
+# def test_time_nodes_add_parachutes(
+#     flight_calisto, calisto_drogue_chute, calisto_main_chute
+# ): # TODO: implement this test
+
+
+# def test_time_nodes_add_controllers(flight_calisto):
+# TODO: implement this test
+
+
+def test_time_nodes_sort(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    time_nodes.add_node(3.0, [], [])
+    time_nodes.add_node(1.0, [], [])
+    time_nodes.add_node(2.0, [], [])
+    time_nodes.sort()
+    assert len(time_nodes) == 3
+    assert time_nodes[0].t == 1.0
+    assert time_nodes[1].t == 2.0
+    assert time_nodes[2].t == 3.0
+
+
+def test_time_nodes_merge(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    time_nodes.add_node(1.0, [], [])
+    time_nodes.add_node(1.0, [], [])
+    time_nodes.add_node(2.0, [], [])
+    time_nodes.merge()
+    assert len(time_nodes) == 2
+    assert time_nodes[0].t == 1.0
+    assert len(time_nodes[0].parachutes) == 0
+    assert len(time_nodes[0].callbacks) == 0
+    assert time_nodes[1].t == 2.0
+    assert len(time_nodes[1].parachutes) == 0
+    assert len(time_nodes[1].callbacks) == 0
+
+
+def test_time_nodes_flush_after(flight_calisto):
+    time_nodes = flight_calisto.TimeNodes()
+    time_nodes.add_node(1.0, [], [])
+    time_nodes.add_node(2.0, [], [])
+    time_nodes.add_node(3.0, [], [])
+    time_nodes.flush_after(1)
+    assert len(time_nodes) == 2
+    assert time_nodes[0].t == 1.0
+    assert time_nodes[1].t == 2.0
+
+
+def test_time_node_init(flight_calisto):
+    node = flight_calisto.TimeNodes.TimeNode(1.0, [], [])
+    assert node.t == 1.0
+    assert len(node.parachutes) == 0
+    assert len(node.callbacks) == 0
+
+
+def test_time_node_lt(flight_calisto):
+    node1 = flight_calisto.TimeNodes.TimeNode(1.0, [], [])
+    node2 = flight_calisto.TimeNodes.TimeNode(2.0, [], [])
+    assert node1 < node2
+    assert not node2 < node1
diff --git a/tests/unit/test_function.py b/tests/unit/test_function.py
index 8bcefb818..9a8a1a834 100644
--- a/tests/unit/test_function.py
+++ b/tests/unit/test_function.py
@@ -79,6 +79,37 @@ def test_differentiate(func_input, derivative_input, expected_derivative):
     assert np.isclose(func.differentiate(derivative_input), expected_derivative)
 
 
+@pytest.mark.parametrize(
+    "func_input, derivative_input, expected_first_derivative",
+    [
+        (1, 0, 0),  # Test case 1: Function(1)
+        (lambda x: x, 0, 1),  # Test case 2: Function(lambda x: x)
+        (lambda x: x**2, 1, 2),  # Test case 3: Function(lambda x: x**2)
+        (lambda x: -(x**3), 2, -12),  # Test case 4: Function(lambda x: -x**3)
+    ],
+)
+def test_differentiate_complex_step(
+    func_input, derivative_input, expected_first_derivative
+):
+    """Test the differentiate_complex_step method of the Function class.
+
+    Parameters
+    ----------
+    func_input : function
+        A function object created from a list of values.
+    derivative_input : int
+        Point at which to differentiate.
+    expected_derivative : float
+        Expected value of the derivative.
+    """
+    func = Function(func_input)
+    assert isinstance(func.differentiate_complex_step(x=derivative_input), float)
+    assert np.isclose(
+        func.differentiate_complex_step(x=derivative_input, order=1),
+        expected_first_derivative,
+    )
+
+
 def test_get_value():
     """Tests the get_value method of the Function class.
     Both with respect to return instances and expected behaviour.
@@ -306,3 +337,31 @@ def test_remove_outliers_iqr(x, y, expected_x, expected_y):
     assert filtered_func.__interpolation__ == func.__interpolation__
     assert filtered_func.__extrapolation__ == func.__extrapolation__
     assert filtered_func.title == func.title
+
+
+def test_set_get_value_opt():
+    """Test the set_value_opt and get_value_opt methods of the Function class."""
+    func = Function(lambda x: x**2)
+    func.source = np.array([[1, 1], [2, 4], [3, 9], [4, 16], [5, 25]])
+    func.x_array = np.array([1, 2, 3, 4, 5])
+    func.y_array = np.array([1, 4, 9, 16, 25])
+    func.x_initial = 1
+    func.x_final = 5
+    func.set_interpolation("linear")
+    func.set_get_value_opt()
+    assert func.get_value_opt(2.5) == 6.5
+
+
+def test_get_image_dim(linear_func):
+    """Test the get_img_dim method of the Function class."""
+    assert linear_func.get_image_dim() == 1
+
+
+def test_get_domain_dim(linear_func):
+    """Test the get_domain_dim method of the Function class."""
+    assert linear_func.get_domain_dim() == 1
+
+
+def test_bool(linear_func):
+    """Test the __bool__ method of the Function class."""
+    assert bool(linear_func) == True
diff --git a/tests/unit/test_rocket.py b/tests/unit/test_rocket.py
index 7d942ee60..4d934efef 100644
--- a/tests/unit/test_rocket.py
+++ b/tests/unit/test_rocket.py
@@ -413,3 +413,86 @@ def test_evaluate_center_of_mass(calisto):
         A predefined instance of the calisto Rocket with a motor, used as a base for testing.
     """
     assert isinstance(calisto.evaluate_center_of_mass(), Function)
+
+
+def test_evaluate_nozzle_to_cdm(calisto):
+    expected_distance = 1.255
+    atol = 1e-3  # Equivalent to 1mm
+    assert pytest.approx(expected_distance, atol) == calisto.nozzle_to_cdm
+    # Test if calling the function returns the same result
+    res = calisto.evaluate_nozzle_to_cdm()
+    assert pytest.approx(expected_distance, atol) == res
+
+
+def test_evaluate_nozzle_gyration_tensor(calisto):
+    expected_gyration_tensor = np.array(
+        [[0.3940207, 0, 0], [0, 0.3940207, 0], [0, 0, 0.0005445]]
+    )
+    atol = 1e-3 * 1e-2 * 1e-2  # Equivalent to 1g * 1cm^2
+    assert np.allclose(
+        expected_gyration_tensor, np.array(calisto.nozzle_gyration_tensor), atol=atol
+    )
+    # Test if calling the function returns the same result
+    res = calisto.evaluate_nozzle_gyration_tensor()
+    assert np.allclose(expected_gyration_tensor, np.array(res), atol=atol)
+
+
+def test_evaluate_com_to_cdm_function(calisto):
+    atol = 1e-3  # Equivalent to 1mm
+    assert np.allclose(
+        (calisto.center_of_dry_mass_position - calisto.center_of_mass).source,
+        calisto.com_to_cdm_function.source,
+        atol=atol,
+    )
+
+
+def test_get_inertia_tensor_at_time(calisto):
+    # Expected values (for t = 0)
+    # TODO: compute these values by hand or using CAD.
+    Ixx = 10.31379
+    Iyy = 10.31379
+    Izz = 0.039942
+
+    # Set tolerance threshold
+    atol = 1e-5
+
+    # Get inertia tensor at t = 0
+    inertia_tensor = calisto.get_inertia_tensor_at_time(0)
+
+    # Check if the values are close to the expected ones
+    assert pytest.approx(Ixx, atol) == inertia_tensor.x[0]
+    assert pytest.approx(Iyy, atol) == inertia_tensor.y[1]
+    assert pytest.approx(Izz, atol) == inertia_tensor.z[2]
+    # Check if products of inertia are zero
+    assert pytest.approx(0, atol) == inertia_tensor.x[1]
+    assert pytest.approx(0, atol) == inertia_tensor.x[2]
+    assert pytest.approx(0, atol) == inertia_tensor.y[0]
+    assert pytest.approx(0, atol) == inertia_tensor.y[2]
+    assert pytest.approx(0, atol) == inertia_tensor.z[0]
+    assert pytest.approx(0, atol) == inertia_tensor.z[1]
+
+
+def test_get_inertia_tensor_derivative_at_time(calisto):
+    # Expected values (for t = 2s)
+    # TODO: compute these values by hand or using CAD.
+    Ixx_dot = -0.634805230901143
+    Iyy_dot = -0.634805230901143
+    Izz_dot = -0.000671493662305
+
+    # Set tolerance threshold
+    atol = 1e-3
+
+    # Get inertia tensor at t = 2s
+    inertia_tensor = calisto.get_inertia_tensor_derivative_at_time(2)
+
+    # Check if the values are close to the expected ones
+    assert pytest.approx(Ixx_dot, atol) == inertia_tensor.x[0]
+    assert pytest.approx(Iyy_dot, atol) == inertia_tensor.y[1]
+    assert pytest.approx(Izz_dot, atol) == inertia_tensor.z[2]
+    # Check if products of inertia are zero
+    assert pytest.approx(0, atol) == inertia_tensor.x[1]
+    assert pytest.approx(0, atol) == inertia_tensor.x[2]
+    assert pytest.approx(0, atol) == inertia_tensor.y[0]
+    assert pytest.approx(0, atol) == inertia_tensor.y[2]
+    assert pytest.approx(0, atol) == inertia_tensor.z[0]
+    assert pytest.approx(0, atol) == inertia_tensor.z[1]
diff --git a/tests/unit/test_stochastic_model.py b/tests/unit/test_stochastic_model.py
new file mode 100644
index 000000000..77c94fb40
--- /dev/null
+++ b/tests/unit/test_stochastic_model.py
@@ -0,0 +1,20 @@
+import pytest
+
+
+@pytest.mark.parametrize(
+    "fixture_name",
+    [
+        "stochastic_rail_buttons",
+        "stochastic_main_parachute",
+        "stochastic_environment",
+        "stochastic_tail",
+        "stochastic_calisto",
+    ],
+)
+def test_visualize_attributes(request, fixture_name):
+    """Tests the visualize_attributes method of the StochasticModel class. This
+    test verifies if the method returns None, which means that the method is
+    running without breaking.
+    """
+    fixture = request.getfixturevalue(fixture_name)
+    assert fixture.visualize_attributes() is None
diff --git a/tests/unit/test_tools.py b/tests/unit/test_tools.py
index 476451c85..e3684199f 100644
--- a/tests/unit/test_tools.py
+++ b/tests/unit/test_tools.py
@@ -14,3 +14,51 @@ def test_euler_to_quaternions(angles, expected_quaternions):
     assert round(q1, 7) == expected_quaternions[1]
     assert round(q2, 7) == expected_quaternions[2]
     assert round(q3, 7) == expected_quaternions[3]
+
+
+import numpy as np
+
+from rocketpy.tools import (
+    calculate_cubic_hermite_coefficients,
+    find_roots_cubic_function,
+)
+
+
+def test_calculate_cubic_hermite_coefficients():
+    """Test the calculate_cubic_hermite_coefficients method of the Function class."""
+    # Function: f(x) = x**3 + 2x**2 -1 ; derivative: f'(x) = 3x**2 + 4x
+    x = np.array([-3, -2, -1, 0, 1])
+    y = np.array([-10, -1, 0, -1, 2])
+
+    # Selects two points as x0 and x1
+    x0, x1 = 0, 1
+    y0, y1 = -1, 2
+    yp0, yp1 = 0, 7
+
+    a, b, c, d = calculate_cubic_hermite_coefficients(x0, x1, y0, yp0, y1, yp1)
+
+    assert np.isclose(a, 1)
+    assert np.isclose(b, 2)
+    assert np.isclose(c, 0)
+    assert np.isclose(d, -1)
+    assert np.allclose(
+        a * x**3 + b * x**2 + c * x + d,
+        y,
+    )
+
+
+def test_cardanos_root_finding():
+    """Tests the find_roots_cubic_function method of the Function class."""
+    # Function: f(x) = x**3 + 2x**2 -1
+    # roots: (-1 - 5**0.5) / 2; -1; (-1 + 5**0.5) / 2
+
+    roots = list(find_roots_cubic_function(a=1, b=2, c=0, d=-1))
+    roots.sort(key=lambda x: x.real)
+
+    assert np.isclose(roots[0].real, (-1 - 5**0.5) / 2)
+    assert np.isclose(roots[1].real, -1)
+    assert np.isclose(roots[2].real, (-1 + 5**0.5) / 2)
+
+    assert np.isclose(roots[0].imag, 0)
+    assert np.isclose(roots[1].imag, 0)
+    assert np.isclose(roots[2].imag, 0)
diff --git a/tests/unit/test_utilities.py b/tests/unit/test_utilities.py
index b07064906..43df536dd 100644
--- a/tests/unit/test_utilities.py
+++ b/tests/unit/test_utilities.py
@@ -48,7 +48,7 @@ def test_create_dispersion_dictionary():
     """Test if the function returns a dictionary with the correct keys.
     It reads the keys from the dictionary generated by the utilities function
     and compares them to the expected.
-    Be careful if you change the "fixtures/dispersion/Valetudo_inputs.csv" file.
+    Be careful if you change the "fixtures/monte_carlo/Valetudo_inputs.csv" file.
 
     Parameters
     ----------
@@ -60,11 +60,11 @@ def test_create_dispersion_dictionary():
     """
 
     returned_dict = utilities.create_dispersion_dictionary(
-        "tests/fixtures/dispersion/Valetudo_inputs.csv"
+        "tests/fixtures/monte_carlo/Valetudo_inputs.csv"
     )
 
     test_array = np.genfromtxt(
-        "tests/fixtures/dispersion/Valetudo_inputs.csv",
+        "tests/fixtures/monte_carlo/Valetudo_inputs.csv",
         usecols=(1, 2, 3),
         skip_header=1,
         delimiter=";",
@@ -153,7 +153,7 @@ def test_fin_flutter_analysis(flight_calisto_custom_wind):
     assert np.isclose(flutter_mach(np.inf), 1.0048188594647927, atol=5e-3)
     assert np.isclose(safety_factor(0), 64.78797, atol=5e-3)
     assert np.isclose(safety_factor(10), 2.1948620401502072, atol=5e-3)
-    assert np.isclose(safety_factor(np.inf), 61.64222220469224, atol=5e-3)
+    assert np.isclose(safety_factor(np.inf), 61.64222220697017, atol=5e-3)
 
 
 def test_flutter_prints(flight_calisto_custom_wind):

From 5d806c6a20f7fc2119181603ff2c3d81e0e45341 Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Fri, 14 Jun 2024 19:32:53 +0200
Subject: [PATCH 110/120] MNT: unecessary variable

---
 rocketpy/simulation/flight.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 417be86af..d0164cdda 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -1883,8 +1883,6 @@ def u_dot_parachute(self, t, u, post_processing=False):
         ay = Dy / (mp + ma)
         az = (Dz - 9.8 * mp) / (mp + ma)
 
-        u_dot = [vx, vy, vz, ax, ay, az, 0, 0, 0, 0, 0, 0, 0]
-
         if post_processing:
             self.__post_processed_variables.append(
                 [t, ax, ay, az, 0, 0, 0, Dx, Dy, Dz, 0, 0, 0]

From de99d86d1746cad742ec335bddc7c69dee86cd1c Mon Sep 17 00:00:00 2001
From: MateusStano <mateusstano@usp.br>
Date: Mon, 8 Jul 2024 23:52:54 +0200
Subject: [PATCH 111/120] DEV: solve merge issues

---
 tests/test_function.py    | 523 --------------------------------------
 tests/test_monte_carlo.py | 171 -------------
 2 files changed, 694 deletions(-)
 delete mode 100644 tests/test_function.py
 delete mode 100644 tests/test_monte_carlo.py

diff --git a/tests/test_function.py b/tests/test_function.py
deleted file mode 100644
index 6f4122e47..000000000
--- a/tests/test_function.py
+++ /dev/null
@@ -1,523 +0,0 @@
-from unittest.mock import patch
-
-import matplotlib as plt
-import numpy as np
-import pytest
-
-from rocketpy import Function
-
-plt.rcParams.update({"figure.max_open_warning": 0})
-
-
-# Test Function creation from .csv file
-def test_function_from_csv(func_from_csv, func_2d_from_csv):
-    """Test the Function class creation from a .csv file.
-
-    Parameters
-    ----------
-    func_from_csv : rocketpy.Function
-        A Function object created from a .csv file.
-    func_2d_from_csv : rocketpy.Function
-        A Function object created from a .csv file with 2 inputs.
-    """
-    # Assert the function is zero at 0 but with a certain tolerance
-    assert np.isclose(func_from_csv(0), 0.0, atol=1e-6)
-    assert np.isclose(func_2d_from_csv(0, 0), 0.0, atol=1e-6)
-    # Check the __str__ method
-    assert func_from_csv.__str__() == "Function from R1 to R1 : (Scalar) → (Scalar)"
-    assert (
-        func_2d_from_csv.__str__()
-        == "Function from R2 to R1 : (Input 1, Input 2) → (Scalar)"
-    )
-    # Check the __repr__ method
-    assert func_from_csv.__repr__() == "'Function from R1 to R1 : (Scalar) → (Scalar)'"
-    assert (
-        func_2d_from_csv.__repr__()
-        == "'Function from R2 to R1 : (Input 1, Input 2) → (Scalar)'"
-    )
-
-
-@pytest.mark.parametrize(
-    "csv_file",
-    [
-        "tests/fixtures/function/1d_quotes.csv",
-        "tests/fixtures/function/1d_no_quotes.csv",
-    ],
-)
-def test_func_from_csv_with_header(csv_file):
-    """Tests if a Function can be created from a CSV file with a single header
-    line. It tests cases where the fields are separated by quotes and without
-    quotes."""
-    f = Function(csv_file)
-    assert f.__repr__() == "'Function from R1 to R1 : (time) → (value)'"
-    assert np.isclose(f(0), 100)
-    assert np.isclose(f(0) + f(1), 300), "Error summing the values of the function"
-
-
-def test_getters(func_from_csv, func_2d_from_csv):
-    """Test the different getters of the Function class.
-
-    Parameters
-    ----------
-    func_from_csv : rocketpy.Function
-        A Function object created from a .csv file.
-    """
-    assert func_from_csv.get_inputs() == ["Scalar"]
-    assert func_from_csv.get_outputs() == ["Scalar"]
-    assert func_from_csv.get_interpolation_method() == "spline"
-    assert func_from_csv.get_extrapolation_method() == "constant"
-    assert np.isclose(func_from_csv.get_value(0), 0.0, atol=1e-6)
-    assert np.isclose(func_from_csv.get_value_opt(0), 0.0, atol=1e-6)
-
-    assert func_2d_from_csv.get_inputs() == ["Input 1", "Input 2"]
-    assert func_2d_from_csv.get_outputs() == ["Scalar"]
-    assert func_2d_from_csv.get_interpolation_method() == "shepard"
-    assert func_2d_from_csv.get_extrapolation_method() == "natural"
-    assert np.isclose(func_2d_from_csv.get_value(0.1, 0.8), 0.058, atol=1e-6)
-    assert np.isclose(func_2d_from_csv.get_value_opt(0.1, 0.8), 0.058, atol=1e-6)
-
-
-def test_setters(func_from_csv, func_2d_from_csv):
-    """Test the different setters of the Function class.
-
-    Parameters
-    ----------
-    func_from_csv : rocketpy.Function
-        A Function object created from a .csv file.
-    """
-    # Test set methods
-    func_from_csv.set_inputs(["Scalar2"])
-    assert func_from_csv.get_inputs() == ["Scalar2"]
-    func_from_csv.set_outputs(["Scalar2"])
-    assert func_from_csv.get_outputs() == ["Scalar2"]
-    func_from_csv.set_interpolation("linear")
-    assert func_from_csv.get_interpolation_method() == "linear"
-    func_from_csv.set_extrapolation("natural")
-    assert func_from_csv.get_extrapolation_method() == "natural"
-
-    func_2d_from_csv.set_inputs(["Scalar1", "Scalar2"])
-    assert func_2d_from_csv.get_inputs() == ["Scalar1", "Scalar2"]
-    func_2d_from_csv.set_outputs(["Scalar3"])
-    assert func_2d_from_csv.get_outputs() == ["Scalar3"]
-    func_2d_from_csv.set_interpolation("shepard")
-    assert func_2d_from_csv.get_interpolation_method() == "shepard"
-    func_2d_from_csv.set_extrapolation("zero")
-    # 2d functions do not support zero extrapolation, must change to natural
-    assert func_2d_from_csv.get_extrapolation_method() == "natural"
-
-
-@patch("matplotlib.pyplot.show")
-def test_plots(mock_show, func_from_csv, func_2d_from_csv):
-    """Test different plot methods of the Function class.
-
-    Parameters
-    ----------
-    mock_show : Mock
-        Mock of the matplotlib.pyplot.show method.
-    func_from_csv : rocketpy.Function
-        A Function object created from a .csv file.
-    """
-    # Test plot methods
-    assert func_from_csv.plot() == None
-    assert func_2d_from_csv.plot() == None
-    # Test plot methods with limits
-    assert func_from_csv.plot(-1, 1) == None
-    assert func_2d_from_csv.plot(-1, 1) == None
-    # Test compare_plots
-    func2 = Function(
-        source="tests/fixtures/airfoils/e473-10e6-degrees.csv",
-        inputs=["Scalar"],
-        outputs=["Scalar"],
-        interpolation="linear",
-        extrapolation="natural",
-    )
-    assert (
-        func_from_csv.compare_plots([func_from_csv, func2], return_object=False) == None
-    )
-
-
-def test_interpolation_methods(linear_func):
-    """Tests some of the interpolation methods of the Function class. Methods
-    not tested here are already being called in other tests.
-
-    Parameters
-    ----------
-    linear_func : rocketpy.Function
-        A Function object created from a list of values.
-    """
-    # Test Akima
-    assert isinstance(linear_func.set_interpolation("akima"), Function)
-    linear_func.set_interpolation("akima")
-    assert isinstance(linear_func.get_interpolation_method(), str)
-    assert linear_func.get_interpolation_method() == "akima"
-    assert np.isclose(linear_func.get_value(0), 0.0, atol=1e-6)
-
-    # Test polynomial
-
-    assert isinstance(linear_func.set_interpolation("polynomial"), Function)
-    linear_func.set_interpolation("polynomial")
-    assert isinstance(linear_func.get_interpolation_method(), str)
-    assert linear_func.get_interpolation_method() == "polynomial"
-    assert np.isclose(linear_func.get_value(0), 0.0, atol=1e-6)
-
-
-def test_extrapolation_methods(linear_func):
-    """Test some of the extrapolation methods of the Function class. Methods
-    not tested here are already being called in other tests.
-
-    Parameters
-    ----------
-    linear_func : rocketpy.Function
-        A Function object created from a list of values.
-    """
-    # Test zero
-    linear_func.set_extrapolation("zero")
-    assert linear_func.get_extrapolation_method() == "zero"
-    assert np.isclose(linear_func.get_value(-1), 0, atol=1e-6)
-
-    # Test constant
-    assert isinstance(linear_func.set_extrapolation("constant"), Function)
-    linear_func.set_extrapolation("constant")
-    assert isinstance(linear_func.get_extrapolation_method(), str)
-    assert linear_func.get_extrapolation_method() == "constant"
-    assert np.isclose(linear_func.get_value(-1), 0, atol=1e-6)
-
-    # Test natural for linear interpolation
-    linear_func.set_interpolation("linear")
-    assert isinstance(linear_func.set_extrapolation("natural"), Function)
-    linear_func.set_extrapolation("natural")
-    assert isinstance(linear_func.get_extrapolation_method(), str)
-    assert linear_func.get_extrapolation_method() == "natural"
-    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
-
-    # Test natural for spline interpolation
-    linear_func.set_interpolation("spline")
-    assert isinstance(linear_func.set_extrapolation("natural"), Function)
-    linear_func.set_extrapolation("natural")
-    assert isinstance(linear_func.get_extrapolation_method(), str)
-    assert linear_func.get_extrapolation_method() == "natural"
-    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
-
-    # Test natural for akima interpolation
-    linear_func.set_interpolation("akima")
-    assert isinstance(linear_func.set_extrapolation("natural"), Function)
-    linear_func.set_extrapolation("natural")
-    assert isinstance(linear_func.get_extrapolation_method(), str)
-    assert linear_func.get_extrapolation_method() == "natural"
-    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
-
-    # Test natural for polynomial interpolation
-    linear_func.set_interpolation("polynomial")
-    assert isinstance(linear_func.set_extrapolation("natural"), Function)
-    linear_func.set_extrapolation("natural")
-    assert isinstance(linear_func.get_extrapolation_method(), str)
-    assert linear_func.get_extrapolation_method() == "natural"
-    assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
-
-
-@pytest.mark.parametrize("a", [-1, 0, 1])
-@pytest.mark.parametrize("b", [-1, 0, 1])
-def test_multivariable_dataset(a, b):
-    """Test the Function class with a multivariable dataset."""
-    # Test plane f(x,y) = x + y
-    source = [
-        (-1, -1, -2),
-        (-1, 0, -1),
-        (-1, 1, 0),
-        (0, -1, -1),
-        (0, 0, 0),
-        (0, 1, 1),
-        (1, -1, 0),
-        (1, 0, 1),
-        (1, 1, 2),
-    ]
-    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
-
-    # Assert interpolation and extrapolation methods
-    assert func.get_interpolation_method() == "shepard"
-    assert func.get_extrapolation_method() == "natural"
-
-    # Assert values
-    assert np.isclose(func(a, b), a + b, atol=1e-6)
-
-
-@pytest.mark.parametrize(
-    "x,y,z_expected",
-    [
-        (1, 0, 0),
-        (0, 1, 0),
-        (0, 0, 1),
-        (0.5, 0.5, 1 / 3),
-        (0.25, 0.25, 25 / (25 + 2 * 5**0.5)),
-        ([0, 0.5], [0, 0.5], [1, 1 / 3]),
-    ],
-)
-def test_2d_shepard_interpolation(x, y, z_expected):
-    """Test the shepard interpolation method of the Function class."""
-    # Test plane x + y + z = 1
-    source = [(1, 0, 0), (0, 1, 0), (0, 0, 1)]
-    func = Function(
-        source=source, inputs=["x", "y"], outputs=["z"], interpolation="shepard"
-    )
-    z = func(x, y)
-    z_opt = func.get_value_opt(x, y)
-    assert np.isclose(z, z_opt, atol=1e-8).all()
-    assert np.isclose(z_expected, z, atol=1e-8).all()
-
-
-@pytest.mark.parametrize(
-    "x,y,z,w_expected",
-    [
-        (0, 0, 0, 1),
-        (1, 0, 0, 0),
-        (0, 1, 0, 0),
-        (0, 0, 1, 0),
-        (0.5, 0.5, 0.5, 1 / 4),
-        (0.25, 0.25, 0.25, 0.700632626832),
-        ([0, 0.5], [0, 0.5], [0, 0.5], [1, 1 / 4]),
-    ],
-)
-def test_3d_shepard_interpolation(x, y, z, w_expected):
-    """Test the shepard interpolation method of the Function class."""
-    # Test plane x + y + z + w = 1
-    source = [(1, 0, 0, 0), (0, 1, 0, 0), (0, 0, 1, 0), (0, 0, 0, 1)]
-    func = Function(
-        source=source, inputs=["x", "y", "z"], outputs=["w"], interpolation="shepard"
-    )
-    w = func(x, y, z)
-    w_opt = func.get_value_opt(x, y, z)
-    assert np.isclose(w, w_opt, atol=1e-8).all()
-    assert np.isclose(w_expected, w, atol=1e-8).all()
-
-
-@pytest.mark.parametrize("a", [-1, -0.5, 0, 0.5, 1])
-@pytest.mark.parametrize("b", [-1, -0.5, 0, 0.5, 1])
-def test_multivariable_function(a, b):
-    """Test the Function class with a multivariable function."""
-    # Test plane f(x,y) = sin(x + y)
-    source = lambda x, y: np.sin(x + y)
-    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
-
-    # Assert values
-    assert np.isclose(func(a, b), np.sin(a + b), atol=1e-6)
-
-
-@patch("matplotlib.pyplot.show")
-def test_multivariable_dataset_plot(mock_show):
-    """Test the plot method of the Function class with a multivariable dataset."""
-    # Test plane f(x,y) = x - y
-    source = [
-        (-1, -1, -1),
-        (-1, 0, -1),
-        (-1, 1, -2),
-        (0, 1, 1),
-        (0, 0, 0),
-        (0, 1, -1),
-        (1, -1, 2),
-        (1, 0, 1),
-        (1, 1, 0),
-    ]
-    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
-
-    # Assert plot
-    assert func.plot() == None
-
-
-@patch("matplotlib.pyplot.show")
-def test_multivariable_function_plot(mock_show):
-    """Test the plot method of the Function class with a multivariable function."""
-    # Test plane f(x,y) = sin(x + y)
-    source = lambda x, y: np.sin(x * y)
-    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
-
-    # Assert plot
-    assert func.plot() == None
-
-
-def test_set_discrete_2d():
-    """Tests the set_discrete method of the Function for
-    two dimensional domains.
-    """
-    func = Function(lambda x, y: x**2 + y**2)
-    discretized_func = func.set_discrete([-5, -7], [8, 10], [50, 100])
-
-    assert isinstance(discretized_func, Function)
-    assert isinstance(func, Function)
-    assert discretized_func.source.shape == (50 * 100, 3)
-    assert np.isclose(discretized_func.source[0, 0], -5)
-    assert np.isclose(discretized_func.source[0, 1], -7)
-    assert np.isclose(discretized_func.source[-1, 0], 8)
-    assert np.isclose(discretized_func.source[-1, 1], 10)
-
-
-def test_set_discrete_2d_simplified():
-    """Tests the set_discrete method of the Function for
-    two dimensional domains with simplified inputs.
-    """
-    source = [(1, 0, 0), (0, 1, 0), (0, 0, 1)]
-    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
-    discretized_func = func.set_discrete(-1, 1, 10)
-
-    assert isinstance(discretized_func, Function)
-    assert isinstance(func, Function)
-    assert discretized_func.source.shape == (100, 3)
-    assert np.isclose(discretized_func.source[0, 0], -1)
-    assert np.isclose(discretized_func.source[0, 1], -1)
-    assert np.isclose(discretized_func.source[-1, 0], 1)
-    assert np.isclose(discretized_func.source[-1, 1], 1)
-
-
-def test_set_discrete_based_on_2d_model(func_2d_from_csv):
-    """Tests the set_discrete_based_on_model method with a 2d model
-    Function.
-    """
-    func = Function(lambda x, y: x**2 + y**2)
-    discretized_func = func.set_discrete_based_on_model(func_2d_from_csv)
-
-    assert isinstance(discretized_func, Function)
-    assert isinstance(func, Function)
-    assert np.array_equal(
-        discretized_func.source[:, :2], func_2d_from_csv.source[:, :2]
-    )
-    assert discretized_func.__interpolation__ == func_2d_from_csv.__interpolation__
-    assert discretized_func.__extrapolation__ == func_2d_from_csv.__extrapolation__
-
-
-@pytest.mark.parametrize(
-    "x,y,z_expected",
-    [
-        (1, 0, 0),
-        (0, 1, 0),
-        (0, 0, 1),
-        (0.5, 0.5, 1 / 3),
-        (0.25, 0.25, 25 / (25 + 2 * 5**0.5)),
-        ([0, 0.5], [0, 0.5], [1, 1 / 3]),
-    ],
-)
-def test_shepard_interpolation(x, y, z_expected):
-    """Test the shepard interpolation method of the Function class."""
-    # Test plane x + y + z = 1
-    source = [(1, 0, 0), (0, 1, 0), (0, 0, 1)]
-    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
-    z = func(x, y)
-    assert np.isclose(z, z_expected, atol=1e-8).all()
-
-
-@pytest.mark.parametrize("other", [1, 0.1, np.int_(1), np.float_(0.1), np.array([1])])
-def test_sum_arithmetic_priority(other):
-    """Test the arithmetic priority of the add operation of the Function class,
-    specially comparing to the numpy array operations.
-    """
-    func_lambda = Function(lambda x: x**2)
-    func_array = Function([(0, 0), (1, 1), (2, 4)])
-
-    assert isinstance(func_lambda + func_array, Function)
-    assert isinstance(func_array + func_lambda, Function)
-    assert isinstance(func_lambda + other, Function)
-    assert isinstance(other + func_lambda, Function)
-    assert isinstance(func_array + other, Function)
-    assert isinstance(other + func_array, Function)
-
-
-@pytest.mark.parametrize("other", [1, 0.1, np.int_(1), np.float_(0.1), np.array([1])])
-def test_sub_arithmetic_priority(other):
-    """Test the arithmetic priority of the sub operation of the Function class,
-    specially comparing to the numpy array operations.
-    """
-    func_lambda = Function(lambda x: x**2)
-    func_array = Function([(0, 0), (1, 1), (2, 4)])
-
-    assert isinstance(func_lambda - func_array, Function)
-    assert isinstance(func_array - func_lambda, Function)
-    assert isinstance(func_lambda - other, Function)
-    assert isinstance(other - func_lambda, Function)
-    assert isinstance(func_array - other, Function)
-    assert isinstance(other - func_array, Function)
-
-
-@pytest.mark.parametrize("other", [1, 0.1, np.int_(1), np.float_(0.1), np.array([1])])
-def test_mul_arithmetic_priority(other):
-    """Test the arithmetic priority of the mul operation of the Function class,
-    specially comparing to the numpy array operations.
-    """
-    func_lambda = Function(lambda x: x**2)
-    func_array = Function([(0, 0), (1, 1), (2, 4)])
-
-    assert isinstance(func_lambda * func_array, Function)
-    assert isinstance(func_array * func_lambda, Function)
-    assert isinstance(func_lambda * other, Function)
-    assert isinstance(other * func_lambda, Function)
-    assert isinstance(func_array * other, Function)
-    assert isinstance(other * func_array, Function)
-
-
-@pytest.mark.parametrize("other", [1, 0.1, np.int_(1), np.float_(0.1), np.array([1])])
-def test_truediv_arithmetic_priority(other):
-    """Test the arithmetic priority of the truediv operation of the Function class,
-    specially comparing to the numpy array operations.
-    """
-    func_lambda = Function(lambda x: x**2)
-    func_array = Function([(1, 1), (2, 4)])
-
-    assert isinstance(func_lambda / func_array, Function)
-    assert isinstance(func_array / func_lambda, Function)
-    assert isinstance(func_lambda / other, Function)
-    assert isinstance(other / func_lambda, Function)
-    assert isinstance(func_array / other, Function)
-    assert isinstance(other / func_array, Function)
-
-
-@pytest.mark.parametrize("other", [1, 0.1, np.int_(1), np.float_(0.1), np.array([1])])
-def test_pow_arithmetic_priority(other):
-    """Test the arithmetic priority of the pow operation of the Function class,
-    specially comparing to the numpy array operations.
-    """
-    func_lambda = Function(lambda x: x**2)
-    func_array = Function([(0, 0), (1, 1), (2, 4)])
-
-    assert isinstance(func_lambda**func_array, Function)
-    assert isinstance(func_array**func_lambda, Function)
-    assert isinstance(func_lambda**other, Function)
-    assert isinstance(other**func_lambda, Function)
-    assert isinstance(func_array**other, Function)
-    assert isinstance(other**func_array, Function)
-
-
-@pytest.mark.parametrize("alpha", [0.1, 0.5, 0.9])
-def test_low_pass_filter(alpha):
-    """Test the low_pass_filter method of the Function class.
-
-    Parameters
-    ----------
-    alpha : float
-        Attenuation coefficient, 0 < alpha < 1.
-    """
-    # Create a test function, sinus here
-    source = np.array(
-        [(1, np.sin(1)), (2, np.sin(2)), (3, np.sin(3)), (4, np.sin(4)), (5, np.sin(5))]
-    )
-    func = Function(source)
-
-    # Apply low pass filter
-    filtered_func = func.low_pass_filter(alpha)
-
-    # Check that the method works as intended and returns the right object with no issue
-    assert isinstance(filtered_func, Function), "The returned type is not a Function"
-    assert np.array_equal(
-        filtered_func.source[0], source[0]
-    ), "The initial value is not the expected value"
-    assert len(filtered_func.source) == len(
-        source
-    ), "The filtered Function and the Function have different lengths"
-    assert (
-        filtered_func.__interpolation__ == func.__interpolation__
-    ), "The interpolation method was unexpectedly changed"
-    assert (
-        filtered_func.__extrapolation__ == func.__extrapolation__
-    ), "The extrapolation method was unexpectedly changed"
-    for i in range(1, len(source)):
-        expected = alpha * source[i][1] + (1 - alpha) * filtered_func.source[i - 1][1]
-        assert np.isclose(filtered_func.source[i][1], expected, atol=1e-6), (
-            f"The filtered value at index {i} is not the expected value. "
-            f"Expected: {expected}, Actual: {filtered_func.source[i][1]}"
-        )
diff --git a/tests/test_monte_carlo.py b/tests/test_monte_carlo.py
deleted file mode 100644
index 8142f91dd..000000000
--- a/tests/test_monte_carlo.py
+++ /dev/null
@@ -1,171 +0,0 @@
-import os
-from unittest.mock import patch
-
-import matplotlib as plt
-import numpy as np
-import pytest
-
-plt.rcParams.update({"figure.max_open_warning": 0})
-
-
-def test_stochastic_environment_create_object_with_wind_x(stochastic_environment):
-    """Tests the stochastic environment object by checking if the wind velocity
-    can be generated properly. The goal is to check if the create_object()
-    method is being called without any problems.
-
-    Parameters
-    ----------
-    stochastic_environment : StochasticEnvironment
-        The stochastic environment object, this is a pytest fixture.
-    """
-    wind_x_at_1000m = []
-    for _ in range(10):
-        random_env = stochastic_environment.create_object()
-        wind_x_at_1000m.append(random_env.wind_velocity_x(1000))
-
-    assert np.isclose(np.mean(wind_x_at_1000m), 0, atol=0.1)
-    assert np.isclose(np.std(wind_x_at_1000m), 0, atol=0.1)
-    # TODO: add a new test for the special case of ensemble member
-
-
-def test_stochastic_solid_motor_create_object_with_impulse(stochastic_solid_motor):
-    """Tests the stochastic solid motor object by checking if the total impulse
-    can be generated properly. The goal is to check if the create_object()
-    method is being called without any problems.
-
-    Parameters
-    ----------
-    stochastic_solid_motor : StochasticSolidMotor
-        The stochastic solid motor object, this is a pytest fixture.
-    """
-    total_impulse = []
-    for _ in range(20):
-        random_motor = stochastic_solid_motor.create_object()
-        total_impulse.append(random_motor.total_impulse)
-
-    assert np.isclose(np.mean(total_impulse), 6500, rtol=0.3)
-    assert np.isclose(np.std(total_impulse), 1000, rtol=0.3)
-
-
-def test_stochastic_calisto_create_object_with_static_margin(stochastic_calisto):
-    """Tests the stochastic calisto object by checking if the static margin
-    can be generated properly. The goal is to check if the create_object()
-    method is being called without any problems.
-
-    Parameters
-    ----------
-    stochastic_calisto : StochasticCalisto
-        The stochastic calisto object, this is a pytest fixture.
-    """
-
-    all_margins = []
-    for _ in range(10):
-        random_rocket = stochastic_calisto.create_object()
-        all_margins.append(random_rocket.static_margin(0))
-
-    assert np.isclose(np.mean(all_margins), 2.2625350013000434, rtol=0.15)
-    assert np.isclose(np.std(all_margins), 0.1, atol=0.2)
-
-
-@pytest.mark.slow
-def test_monte_carlo_simulate(monte_carlo_calisto):
-    """Tests the simulate method of the MonteCarlo class.
-
-    Parameters
-    ----------
-    monte_carlo_calisto : MonteCarlo
-        The MonteCarlo object, this is a pytest fixture.
-    """
-    # NOTE: this is really slow, it runs 10 flight simulations
-    monte_carlo_calisto.simulate(number_of_simulations=10, append=False)
-
-    assert monte_carlo_calisto.num_of_loaded_sims == 10
-    assert monte_carlo_calisto.number_of_simulations == 10
-    assert monte_carlo_calisto.filename == "monte_carlo_test"
-    assert monte_carlo_calisto.error_file == "monte_carlo_test.errors.txt"
-    assert monte_carlo_calisto.output_file == "monte_carlo_test.outputs.txt"
-    assert np.isclose(
-        monte_carlo_calisto.processed_results["apogee"][0], 4711, rtol=0.15
-    )
-    assert np.isclose(
-        monte_carlo_calisto.processed_results["impact_velocity"][0],
-        -5.234,
-        rtol=0.15,
-    )
-    os.remove("monte_carlo_test.errors.txt")
-    os.remove("monte_carlo_test.outputs.txt")
-    os.remove("monte_carlo_test.inputs.txt")
-
-
-def test_monte_carlo_set_inputs_log(monte_carlo_calisto):
-    """Tests the set_inputs_log method of the MonteCarlo class.
-
-    Parameters
-    ----------
-    monte_carlo_calisto : MonteCarlo
-        The MonteCarlo object, this is a pytest fixture.
-    """
-    monte_carlo_calisto.input_file = "tests/fixtures/monte_carlo/example.inputs.txt"
-    monte_carlo_calisto.set_inputs_log()
-    assert len(monte_carlo_calisto.inputs_log) == 10
-    assert all(isinstance(item, dict) for item in monte_carlo_calisto.inputs_log)
-    assert all(
-        "gravity" in item and "elevation" in item
-        for item in monte_carlo_calisto.inputs_log
-    )
-
-
-def test_monte_carlo_set_outputs_log(monte_carlo_calisto):
-    """Tests the set_outputs_log method of the MonteCarlo class.
-
-    Parameters
-    ----------
-    monte_carlo_calisto : MonteCarlo
-        The MonteCarlo object, this is a pytest fixture.
-    """
-    monte_carlo_calisto.output_file = "tests/fixtures/monte_carlo/example.outputs.txt"
-    monte_carlo_calisto.set_outputs_log()
-    assert len(monte_carlo_calisto.outputs_log) == 10
-    assert all(isinstance(item, dict) for item in monte_carlo_calisto.outputs_log)
-    assert all(
-        "apogee" in item and "impact_velocity" in item
-        for item in monte_carlo_calisto.outputs_log
-    )
-
-
-# def test_monte_carlo_set_errors_log(monte_carlo_calisto):
-#     monte_carlo_calisto.error_file = "tests/fixtures/monte_carlo/example.errors.txt"
-#     monte_carlo_calisto.set_errors_log()
-#     assert
-
-
-def test_monte_carlo_prints(monte_carlo_calisto):
-    """Tests the prints methods of the MonteCarlo class."""
-    monte_carlo_calisto.info()
-
-
-@patch("matplotlib.pyplot.show")
-def test_monte_carlo_plots(mock_show, monte_carlo_calisto):
-    """Tests the plots methods of the MonteCarlo class."""
-    assert monte_carlo_calisto.all_info() is None
-
-
-def test_monte_carlo_export_ellipses_to_kml(monte_carlo_calisto):
-    """Tests the export_ellipses_to_kml method of the MonteCarlo class.
-
-    Parameters
-    ----------
-    monte_carlo_calisto : MonteCarlo
-        The MonteCarlo object, this is a pytest fixture.
-    """
-    assert (
-        monte_carlo_calisto.export_ellipses_to_kml(
-            filename="monte_carlo_class_example.kml",
-            origin_lat=32,
-            origin_lon=-104,
-            type="impact",
-        )
-        is None
-    )
-
-    os.remove("monte_carlo_class_example.kml")

From 523a81942e7ff8a57ee361ca2828e93774ddc0eb Mon Sep 17 00:00:00 2001
From: MateusStano <69485049+MateusStano@users.noreply.github.com>
Date: Sun, 8 Sep 2024 02:33:07 +0200
Subject: [PATCH 112/120] ENH: Adds GNSS Receiver sensor (#636)

* ENH: class GNSS

* ENH: gnss prints

* ENH: add params to measure call

* ENH: export data

* ENH: pass env in .measure

* DOC: gnss attribute docs

* MNT: units in prints

* MNT: fix merge errors

* TST: add gnss tests

* TST: fix time nodes tests

* DEV: add gnss to sensors testing notebook

* DEV: fix merge errors

* MNT: lint and isort

* MNT: black notebooks

* TST: fix test by inversion of rotation

* TST: lower rel tolerances and delete duplicated tests

* MNT: minor fixes

* ENH: export sensor data by sensor name

* MNT: use inverted_haversine in GNSS

* BUG: bearing unit in inverted_haversine

* MNT: pylint

* TST: add test for export with sensor name

* MNT: rename `GNSS` class to `GnssReceiver`

* MNT: fix lint

* MNT: rename gnss file

---------

Co-authored-by: Gui-FernandesBR <guilherme_fernandes@usp.br>
---
 docs/notebooks/sensors_testing.ipynb       | 259 +++++++++++++--------
 rocketpy/__init__.py                       |   2 +-
 rocketpy/plots/rocket_plots.py             |  13 +-
 rocketpy/prints/sensors_prints.py          |  26 ++-
 rocketpy/rocket/parachute.py               |   1 +
 rocketpy/rocket/rocket.py                  |   3 +-
 rocketpy/sensors/__init__.py               |   1 +
 rocketpy/sensors/accelerometer.py          |  10 +-
 rocketpy/sensors/barometer.py              |  10 +-
 rocketpy/sensors/gnss_receiver.py          | 125 ++++++++++
 rocketpy/sensors/gyroscope.py              |   8 +-
 rocketpy/sensors/sensor.py                 |   8 +-
 rocketpy/simulation/flight.py              |  57 ++++-
 rocketpy/tools.py                          |  18 +-
 tests/fixtures/rockets/rocket_fixtures.py  |   2 +
 tests/fixtures/sensors/sensors_fixtures.py |  18 +-
 tests/{ => integration}/test_sensor.py     |  53 ++++-
 tests/unit/test_flight.py                  |   2 +
 tests/unit/test_flight_time_nodes.py       |  30 +--
 tests/unit/test_sensor.py                  | 149 ++++++++----
 tests/unit/test_tools.py                   |  50 +---
 tests/unit/test_tools_matrix.py            |   4 +-
 22 files changed, 583 insertions(+), 266 deletions(-)
 create mode 100644 rocketpy/sensors/gnss_receiver.py
 rename tests/{ => integration}/test_sensor.py (66%)

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors_testing.ipynb
index 83a777daa..e2b987c6b 100644
--- a/docs/notebooks/sensors_testing.ipynb
+++ b/docs/notebooks/sensors_testing.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -44,13 +44,74 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "colab": {},
     "colab_type": "code",
     "id": "5kl-Je8dNVFI"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Gravity Details\n",
+      "\n",
+      "Acceleration of gravity at surface level:    9.7913 m/s²\n",
+      "Acceleration of gravity at  10.000 km (ASL): 9.7649 m/s²\n",
+      "\n",
+      "\n",
+      "Launch Site Details\n",
+      "\n",
+      "Launch Site Latitude: 32.99025°\n",
+      "Launch Site Longitude: -106.97500°\n",
+      "Reference Datum: SIRGAS2000\n",
+      "Launch Site UTM coordinates: 315468.64 W    3651938.65 N\n",
+      "Launch Site UTM zone: 13S\n",
+      "Launch Site Surface Elevation: 1400.0 m\n",
+      "\n",
+      "\n",
+      "Atmospheric Model Details\n",
+      "\n",
+      "Atmospheric Model Type: custom_atmosphere\n",
+      "custom_atmosphere Maximum Height: 10.000 km\n",
+      "\n",
+      "\n",
+      "Surface Atmospheric Conditions\n",
+      "\n",
+      "Surface Wind Speed: 4.69 m/s\n",
+      "Surface Wind Direction: 219.81°\n",
+      "Surface Wind Heading: 39.81°\n",
+      "Surface Pressure: 856.02 hPa\n",
+      "Surface Temperature: 279.07 K\n",
+      "Surface Air Density: 1.069 kg/m³\n",
+      "Surface Speed of Sound: 334.55 m/s\n",
+      "\n",
+      "\n",
+      "Earth Model Details\n",
+      "\n",
+      "Earth Radius at Launch site: 6371.83 km\n",
+      "Semi-major Axis: 6378.14 km\n",
+      "Semi-minor Axis: 6356.75 km\n",
+      "Flattening: 0.0034\n",
+      "\n",
+      "\n",
+      "Atmospheric Model Plots\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x450 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "env = Environment(latitude=32.990254, longitude=-106.974998, elevation=1400)\n",
     "env.set_atmospheric_model(\n",
@@ -61,7 +122,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -91,7 +152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -136,47 +197,51 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from rocketpy import Accelerometer, Gyroscope, Barometer\n",
-    "accel_noisy_nosecone = Accelerometer(sampling_rate=100,\n",
-    "                  consider_gravity=False,\n",
-    "                  orientation=(60,60,60),\n",
-    "                  measurement_range=70,\n",
-    "                  resolution=0.4882,\n",
-    "                  noise_density=0.05,\n",
-    "                  random_walk_density=0.02,\n",
-    "                  constant_bias=1 ,\n",
-    "                  operating_temperature=25,\n",
-    "                  temperature_bias=0.02,\n",
-    "                  temperature_scale_factor=0.02,\n",
-    "                  cross_axis_sensitivity=0.02,\n",
-    "                  name='Accelerometer in Nosecone'\n",
-    "                )\n",
-    "accel_clean_cdm = Accelerometer(sampling_rate=100,\n",
-    "                  consider_gravity=False,\n",
-    "                  orientation=[[0.25, -0.0581, 0.9665],\n",
-    "                               [0.433, 0.8995, -0.0581],\n",
-    "                               [-0.8661, 0.433, 0.25]\n",
-    "                               ],\n",
-    "                  name='Accelerometer in CDM'\n",
-    "                  )\n",
+    "from rocketpy import Accelerometer, Gyroscope, Barometer, GnssReceiver\n",
+    "\n",
+    "accel_noisy_nosecone = Accelerometer(\n",
+    "    sampling_rate=100,\n",
+    "    consider_gravity=False,\n",
+    "    orientation=(60, 60, 60),\n",
+    "    measurement_range=70,\n",
+    "    resolution=0.4882,\n",
+    "    noise_density=0.05,\n",
+    "    random_walk_density=0.02,\n",
+    "    constant_bias=1,\n",
+    "    operating_temperature=25,\n",
+    "    temperature_bias=0.02,\n",
+    "    temperature_scale_factor=0.02,\n",
+    "    cross_axis_sensitivity=0.02,\n",
+    "    name='Accelerometer in Nosecone',\n",
+    ")\n",
+    "accel_clean_cdm = Accelerometer(\n",
+    "    sampling_rate=100,\n",
+    "    consider_gravity=False,\n",
+    "    orientation=[\n",
+    "        [0.25, -0.0581, 0.9665],\n",
+    "        [0.433, 0.8995, -0.0581],\n",
+    "        [-0.8661, 0.433, 0.25],\n",
+    "    ],\n",
+    "    name='Accelerometer in CDM',\n",
+    ")\n",
     "calisto.add_sensor(accel_noisy_nosecone, 1.278)\n",
     "calisto.add_sensor(accel_clean_cdm, -0.10482544178314143)  # , 127/2000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Identification of the Sensor:\n",
+      "Identification:\n",
       "\n",
       "Name:                      Accelerometer in Nosecone\n",
       "Type:                      Accelerometer\n",
@@ -184,29 +249,29 @@
       "Orientation of the Sensor:\n",
       "\n",
       "Orientation:               (60, 60, 60)\n",
-      "Normal Vector:             (0.9665063509461097, -0.05801270189221941, 0.2500000000000002)\n",
+      "Normal Vector:             (0.9665063509461147, -0.058012701892006885, 0.2500000000000297)\n",
       "Rotation Matrix:\n",
       "                           [0.25, -0.06, 0.97]\n",
       "                           [0.43, 0.9, -0.06]\n",
       "                           [-0.87, 0.43, 0.25]\n",
       "\n",
-      "Quantization of the Sensor:\n",
+      "Quantization:\n",
       "\n",
       "Measurement Range:         -70 to 70 (m/s^2)\n",
       "Resolution:                0.4882 m/s^2/LSB\n",
       "\n",
-      "Noise of the Sensor:\n",
+      "Noise:\n",
       "\n",
       "Noise Density:             (0.05, 0.05, 0.05) m/s^2/√Hz\n",
       "Noise Variance:            (1, 1, 1) (m/s^2)^2\n",
       "Random Walk Density:       (0.02, 0.02, 0.02) m/s^2/√Hz\n",
       "Random Walk Variance:      (1, 1, 1) (m/s^2)^2\n",
       "Constant Bias:             (1, 1, 1) m/s^2\n",
-      "Operating Temperature:     25 °C\n",
-      "Temperature Bias:          (0.02, 0.02, 0.02) m/s^2/°C\n",
-      "Temperature Scale Factor:  (0.02, 0.02, 0.02) %/°C\n",
+      "Operating Temperature:     25 K\n",
+      "Temperature Bias:          (0.02, 0.02, 0.02) m/s^2/K\n",
+      "Temperature Scale Factor:  (0.02, 0.02, 0.02) %/K\n",
       "Cross Axis Sensitivity:    0.02 %\n",
-      "Identification of the Sensor:\n",
+      "Identification:\n",
       "\n",
       "Name:                      Accelerometer in CDM\n",
       "Type:                      Accelerometer\n",
@@ -220,21 +285,21 @@
       "                           [0.43, 0.9, -0.06]\n",
       "                           [-0.87, 0.43, 0.25]\n",
       "\n",
-      "Quantization of the Sensor:\n",
+      "Quantization:\n",
       "\n",
       "Measurement Range:         -inf to inf (m/s^2)\n",
       "Resolution:                0 m/s^2/LSB\n",
       "\n",
-      "Noise of the Sensor:\n",
+      "Noise:\n",
       "\n",
       "Noise Density:             (0, 0, 0) m/s^2/√Hz\n",
       "Noise Variance:            (1, 1, 1) (m/s^2)^2\n",
       "Random Walk Density:       (0, 0, 0) m/s^2/√Hz\n",
       "Random Walk Variance:      (1, 1, 1) (m/s^2)^2\n",
       "Constant Bias:             (0, 0, 0) m/s^2\n",
-      "Operating Temperature:     25 °C\n",
-      "Temperature Bias:          (0, 0, 0) m/s^2/°C\n",
-      "Temperature Scale Factor:  (0, 0, 0) %/°C\n",
+      "Operating Temperature:     25 K\n",
+      "Temperature Bias:          (0, 0, 0) m/s^2/K\n",
+      "Temperature Scale Factor:  (0, 0, 0) %/K\n",
       "Cross Axis Sensitivity:    0 %\n"
      ]
     }
@@ -246,80 +311,74 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.001064225153655079"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "import numpy as np\n",
-    "np.radians(0.06097560975609756097560975609756)"
+    "gyro_clean = Gyroscope(sampling_rate=100)\n",
+    "gyro_noisy = Gyroscope(\n",
+    "    sampling_rate=100,\n",
+    "    resolution=0.001064225153655079,\n",
+    "    orientation=(-60, -60, -60),\n",
+    "    noise_density=[0, 0.03, 0.05],\n",
+    "    noise_variance=1.01,\n",
+    "    random_walk_density=[0, 0.01, 0.02],\n",
+    "    random_walk_variance=[1, 1, 1.05],\n",
+    "    constant_bias=[0, 0.3, 0.5],\n",
+    "    operating_temperature=25,\n",
+    "    temperature_bias=[0, 0.01, 0.02],\n",
+    "    temperature_scale_factor=[0, 0.01, 0.02],\n",
+    "    cross_axis_sensitivity=0.5,\n",
+    "    acceleration_sensitivity=[0, 0.0008, 0.0017],\n",
+    "    name=\"Gyroscope\",\n",
+    ")\n",
+    "calisto.add_sensor(gyro_clean, -0.10482544178314143)  # +0.5, 127/2000)\n",
+    "calisto.add_sensor(gyro_noisy, 1.278 - 0.4, 127 / 2000 - 127 / 4000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
-    "gyro_clean = Gyroscope(sampling_rate=100)\n",
-    "gyro_noisy = Gyroscope(\n",
-    "        sampling_rate=100,\n",
-    "        resolution=0.001064225153655079,\n",
-    "        orientation=(-60, -60, -60),\n",
-    "        noise_density=[0, 0.03, 0.05],\n",
-    "        noise_variance=1.01,\n",
-    "        random_walk_density=[0, 0.01, 0.02],\n",
-    "        random_walk_variance=[1, 1, 1.05],\n",
-    "        constant_bias=[0, 0.3, 0.5],\n",
-    "        operating_temperature=25,\n",
-    "        temperature_bias=[0, 0.01, 0.02],\n",
-    "        temperature_scale_factor=[0, 0.01, 0.02],\n",
-    "        cross_axis_sensitivity=0.5,\n",
-    "        acceleration_sensitivity=[0, 0.0008, 0.0017],\n",
-    "        name=\"Gyroscope\",\n",
-    "    )\n",
-    "calisto.add_sensor(gyro_clean, -0.10482544178314143)#+0.5, 127/2000)\n",
-    "calisto.add_sensor(gyro_noisy, 1.278-0.4, 127/2000-127/4000)"
+    "barometer_clean = Barometer(\n",
+    "    sampling_rate=50,\n",
+    "    measurement_range=100000,\n",
+    "    resolution=0.16,\n",
+    "    noise_density=19,\n",
+    "    noise_variance=19,\n",
+    "    random_walk_density=0.01,\n",
+    "    constant_bias=1,\n",
+    "    operating_temperature=25,\n",
+    "    temperature_bias=0.02,\n",
+    "    temperature_scale_factor=0.02,\n",
+    ")\n",
+    "calisto.add_sensor(barometer_clean, -0.10482544178314143 + 0.5, -127 / 2000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
-    "barometer_clean = Barometer(sampling_rate=50,\n",
-    "                            measurement_range=100000,\n",
-    "                            resolution=0.16,\n",
-    "                            noise_density=19,\n",
-    "                            noise_variance=19,\n",
-    "                            random_walk_density=0.01,\n",
-    "                            constant_bias=1,\n",
-    "                            operating_temperature=25,\n",
-    "                            temperature_bias=0.02,\n",
-    "                            temperature_scale_factor=0.02,\n",
-    "                            )\n",
-    "calisto.add_sensor(barometer_clean, -0.10482544178314143+0.5, -127/2000)"
+    "gnss_clean = GnssReceiver(\n",
+    "    sampling_rate=1,\n",
+    "    position_accuracy=1,\n",
+    "    altitude_accuracy=1,\n",
+    ")\n",
+    "calisto.add_sensor(gnss_clean, -0.10482544178314143 + 0.5, +127 / 2000)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -334,12 +393,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -563,7 +622,7 @@
     "plt.xlabel(\"Time (s)\")\n",
     "plt.ylabel(\"Acceleration az (m/s^2)\")\n",
     "plt.legend()\n",
-    "plt.show()\n"
+    "plt.show()"
    ]
   },
   {
@@ -657,7 +716,7 @@
     "plt.show()\n",
     "\n",
     "plt.plot(time1, wz, label='Noisy Gyroscope')\n",
-    "plt.xlim(0,4)\n",
+    "plt.xlim(0, 4)\n",
     "# plt.plot(time2, zz, label='Clean Gyroscope')\n",
     "plt.legend()\n",
     "plt.show()\n",
@@ -692,8 +751,8 @@
     }
    ],
    "source": [
-    "t,p = zip(*barometer_clean.measured_data)\n",
-    "plt.plot(t,p)\n",
+    "t, p = zip(*barometer_clean.measured_data)\n",
+    "plt.plot(t, p)\n",
     "plt.show()"
    ]
   },
diff --git a/rocketpy/__init__.py b/rocketpy/__init__.py
index d7d600802..276d60ce7 100644
--- a/rocketpy/__init__.py
+++ b/rocketpy/__init__.py
@@ -37,7 +37,7 @@
     Tail,
     TrapezoidalFins,
 )
-from .sensors import Accelerometer, Barometer, Gyroscope
+from .sensors import Accelerometer, Barometer, GnssReceiver, Gyroscope
 from .simulation import Flight, MonteCarlo
 from .stochastic import (
     StochasticEllipticalFins,
diff --git a/rocketpy/plots/rocket_plots.py b/rocketpy/plots/rocket_plots.py
index 465770afd..85751bc34 100644
--- a/rocketpy/plots/rocket_plots.py
+++ b/rocketpy/plots/rocket_plots.py
@@ -3,7 +3,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-from rocketpy.mathutils.vector_matrix import Vector
 from rocketpy.motors import EmptyMotor, HybridMotor, LiquidMotor, SolidMotor
 from rocketpy.rocket.aero_surface import Fins, NoseCone, Tail
 
@@ -166,8 +165,6 @@ def thrust_to_weight(self):
             lower=0, upper=self.rocket.motor.burn_out_time
         )
 
-        return None
-
     def draw(self, vis_args=None, plane="xz"):
         """Draws the rocket in a matplotlib figure.
 
@@ -204,7 +201,7 @@ def draw(self, vis_args=None, plane="xz"):
                 "line_width": 1.0,
             }
 
-        fig, ax = plt.subplots(figsize=(8, 6), facecolor=vis_args["background"])
+        _, ax = plt.subplots(figsize=(8, 6), facecolor=vis_args["background"])
         ax.set_aspect("equal")
         ax.grid(True, linestyle="--", linewidth=0.5)
 
@@ -217,7 +214,7 @@ def draw(self, vis_args=None, plane="xz"):
         self._draw_motor(last_radius, last_x, ax, vis_args)
         self._draw_rail_buttons(ax, vis_args)
         self._draw_center_of_mass_and_pressure(ax)
-        self._draw_sensors(ax, self.rocket.sensors, plane, vis_args)
+        self._draw_sensors(ax, self.rocket.sensors, plane)
 
         plt.title("Rocket Representation")
         plt.xlim()
@@ -386,7 +383,7 @@ def _draw_motor(self, last_radius, last_x, ax, vis_args):
         )
 
         # Get motor patches translated to the correct position
-        motor_patches = self._generate_motor_patches(total_csys, ax, vis_args)
+        motor_patches = self._generate_motor_patches(total_csys, ax)
 
         # Draw patches
         if not isinstance(self.rocket.motor, EmptyMotor):
@@ -407,7 +404,7 @@ def _draw_motor(self, last_radius, last_x, ax, vis_args):
         self._draw_nozzle_tube(last_radius, last_x, nozzle_position, ax, vis_args)
 
     def _generate_motor_patches(
-        self, total_csys, ax, vis_args
+        self, total_csys, ax
     ):  # pylint: disable=unused-argument
         """Generates motor patches for drawing"""
         motor_patches = []
@@ -554,7 +551,7 @@ def _draw_center_of_mass_and_pressure(self, ax):
             cp, 0, label="Static Center of Pressure", color="red", s=10, zorder=10
         )
 
-    def _draw_sensors(self, ax, sensors, plane, vis_args):
+    def _draw_sensors(self, ax, sensors, plane):
         """Draw the sensor as a small thick line at the position of the sensor,
         with a vector pointing in the direction normal of the sensor. Get the
         normal vector from the sensor orientation matrix."""
diff --git a/rocketpy/prints/sensors_prints.py b/rocketpy/prints/sensors_prints.py
index a454aa0fa..73ab062f8 100644
--- a/rocketpy/prints/sensors_prints.py
+++ b/rocketpy/prints/sensors_prints.py
@@ -16,17 +16,6 @@ def identity(self):
         self._print_aligned("Name:", self.sensor.name)
         self._print_aligned("Type:", self.sensor.__class__.__name__)
 
-    def orientation(self):
-        """Prints the orientation of the sensor."""
-        print("\nOrientation:\n")
-        self._print_aligned("Orientation:", self.sensor.orientation)
-        self._print_aligned("Normal Vector:", self.sensor.normal_vector)
-        print("Rotation Matrix:")
-        for row in self.sensor.rotation_matrix:
-            value = " ".join(f"{val:.2f}" for val in row)
-            value = [float(val) for val in value.split()]
-            self._print_aligned("", value)
-
     def quantization(self):
         """Prints the quantization of the sensor."""
         print("\nQuantization:\n")
@@ -115,3 +104,18 @@ def noise(self):
             "Acceleration Sensitivity:",
             f"{self.sensor.acceleration_sensitivity} rad/s/g",
         )
+
+
+class _GnssReceiverPrints(_SensorPrints):
+    """Class that contains all GnssReceiver prints."""
+
+    def accuracy(self):
+        """Prints the accuracy of the sensor."""
+        print("\nAccuracy:\n")
+        self._print_aligned("Position Accuracy:", f"{self.sensor.position_accuracy} m")
+        self._print_aligned("Altitude Accuracy:", f"{self.sensor.altitude_accuracy} m")
+
+    def all(self):
+        """Prints all information of the sensor."""
+        self.identity()
+        self.accuracy()
diff --git a/rocketpy/rocket/parachute.py b/rocketpy/rocket/parachute.py
index 7849ad950..4db84dc68 100644
--- a/rocketpy/rocket/parachute.py
+++ b/rocketpy/rocket/parachute.py
@@ -190,6 +190,7 @@ def __evaluate_trigger_function(self, trigger):
         """This is used to set the triggerfunc attribute that will be used to
         interact with the Flight class.
         """
+        # pylint: disable=unused-argument, function-redefined
         # The parachute is deployed by a custom function
         if callable(trigger):
             # work around for having added sensors to parachute triggers
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index e01d017fa..4e3c9e04d 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -4,8 +4,7 @@
 
 from rocketpy.control.controller import _Controller
 from rocketpy.mathutils.function import Function
-from rocketpy.mathutils.vector_matrix import Vector, Matrix
-from rocketpy.mathutils.vector_matrix import Matrix
+from rocketpy.mathutils.vector_matrix import Matrix, Vector
 from rocketpy.motors.motor import EmptyMotor
 from rocketpy.plots.rocket_plots import _RocketPlots
 from rocketpy.prints.rocket_prints import _RocketPrints
diff --git a/rocketpy/sensors/__init__.py b/rocketpy/sensors/__init__.py
index 40bac14cc..eb2e20730 100644
--- a/rocketpy/sensors/__init__.py
+++ b/rocketpy/sensors/__init__.py
@@ -1,4 +1,5 @@
 from .accelerometer import Accelerometer
 from .barometer import Barometer
+from .gnss_receiver import GnssReceiver
 from .gyroscope import Gyroscope
 from .sensor import InertialSensor, ScalarSensor, Sensor
diff --git a/rocketpy/sensors/accelerometer.py b/rocketpy/sensors/accelerometer.py
index bf67c88c1..607b1632e 100644
--- a/rocketpy/sensors/accelerometer.py
+++ b/rocketpy/sensors/accelerometer.py
@@ -4,6 +4,8 @@
 from ..prints.sensors_prints import _InertialSensorPrints
 from ..sensors.sensor import InertialSensor
 
+# pylint: disable=too-many-arguments
+
 
 class Accelerometer(InertialSensor):
     """Class for the accelerometer sensor
@@ -208,15 +210,13 @@ def measure(self, time, **kwargs):
                 Derivative of the state vector of the rocket.
             - relative_position : np.array
                 Position of the sensor relative to the rocket center of mass.
-            - gravity : float
-                Gravitational acceleration in m/s^2.
-            - pressure : Function
-                Atmospheric pressure profile as a function of altitude in Pa.
+            - environment : Environment
+                Environment object containing the atmospheric conditions.
         """
         u = kwargs["u"]
         u_dot = kwargs["u_dot"]
         relative_position = kwargs["relative_position"]
-        gravity = kwargs["gravity"]
+        gravity = kwargs["environment"].gravity.get_value_opt(u[3])
 
         # Linear acceleration of rocket cdm in inertial frame
         gravity = (
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index fbed17f56..4a324faf5 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -150,16 +150,12 @@ def measure(self, time, **kwargs):
                 Derivative of the state vector of the rocket.
             - relative_position : np.array
                 Position of the sensor relative to the rocket center of mass.
-            - gravity : float
-                Gravitational acceleration in m/s^2.
-            - pressure : Function
-                Atmospheric pressure profile as a function of altitude in Pa.
-            - elevation : float
-                Elevation of the launch site in meters.
+            - environment : Environment
+                Environment object containing the atmospheric conditions.
         """
         u = kwargs["u"]
         relative_position = kwargs["relative_position"]
-        pressure = kwargs["pressure"]
+        pressure = kwargs["environment"].pressure
 
         # Calculate the altitude of the sensor
         relative_altitude = (Matrix.transformation(u[6:10]) @ relative_position).z
diff --git a/rocketpy/sensors/gnss_receiver.py b/rocketpy/sensors/gnss_receiver.py
new file mode 100644
index 000000000..9502bd918
--- /dev/null
+++ b/rocketpy/sensors/gnss_receiver.py
@@ -0,0 +1,125 @@
+import math
+
+import numpy as np
+
+from rocketpy.tools import inverted_haversine
+
+from ..mathutils.vector_matrix import Matrix, Vector
+from ..prints.sensors_prints import _GnssReceiverPrints
+from .sensor import ScalarSensor
+
+
+class GnssReceiver(ScalarSensor):
+    """Class for the GNSS Receiver sensor.
+
+    Attributes
+    ----------
+    prints : _GnssReceiverPrints
+        Object that contains the print functions for the sensor.
+    sampling_rate : float
+        Sample rate of the sensor in Hz.
+    position_accuracy : float
+        Accuracy of the sensor interpreted as the standard deviation of the
+        position in meters.
+    altitude_accuracy : float
+        Accuracy of the sensor interpreted as the standard deviation of the
+        position in meters.
+    name : str
+        The name of the sensor.
+    measurement : tuple
+        The measurement of the sensor.
+    measured_data : list
+        The stored measured data of the sensor.
+    """
+
+    units = "°, m"
+
+    def __init__(
+        self,
+        sampling_rate,
+        position_accuracy=0,
+        altitude_accuracy=0,
+        name="GnssReceiver",
+    ):
+        """Initialize the Gnss Receiver sensor.
+
+        Parameters
+        ----------
+        sampling_rate : float
+            Sample rate of the sensor in Hz.
+        position_accuracy : float
+            Accuracy of the sensor interpreted as the standard deviation of the
+            position in meters. Default is 0.
+        altitude_accuracy : float
+            Accuracy of the sensor interpreted as the standard deviation of the
+            position in meters. Default is 0.
+        name : str
+            The name of the sensor. Default is "GnssReceiver".
+        """
+        super().__init__(sampling_rate=sampling_rate, name=name)
+        self.position_accuracy = position_accuracy
+        self.altitude_accuracy = altitude_accuracy
+
+        self.prints = _GnssReceiverPrints(self)
+
+    def measure(self, time, **kwargs):
+        """Measure the position of the rocket in latitude, longitude and
+        altitude.
+
+        Parameters
+        ----------
+        time : float
+            Current time in seconds.
+        kwargs : dict
+            Keyword arguments dictionary containing the following keys:
+            - u : np.array
+                State vector of the rocket.
+            - u_dot : np.array
+                Derivative of the state vector of the rocket.
+            - relative_position : np.array
+                Position of the sensor relative to the rocket center of mass.
+            - environment : Environment
+                Environment object containing the atmospheric conditions.
+        """
+        u = kwargs["u"]
+        relative_position = kwargs["relative_position"]
+        lat, lon = kwargs["environment"].latitude, kwargs["environment"].longitude
+        earth_radius = kwargs["environment"].earth_radius
+
+        # Get from state u and add relative position
+        x, y, z = (Matrix.transformation(u[6:10]) @ relative_position) + Vector(u[0:3])
+        # Apply accuracy to the position
+        x = np.random.normal(x, self.position_accuracy)
+        y = np.random.normal(y, self.position_accuracy)
+        altitude = np.random.normal(z, self.altitude_accuracy)
+
+        # Convert x and y to latitude and longitude
+        drift = (x**2 + y**2) ** 0.5
+        bearing = (2 * math.pi - math.atan2(-x, y)) * (180 / math.pi)
+
+        # Applies the haversine equation to find final lat/lon coordinates
+        latitude, longitude = inverted_haversine(lat, lon, drift, bearing, earth_radius)
+
+        self.measurement = (latitude, longitude, altitude)
+        self._save_data((time, *self.measurement))
+
+    def export_measured_data(self, filename, file_format="csv"):
+        """Export the measured values to a file
+
+        Parameters
+        ----------
+        filename : str
+            Name of the file to export the values to
+        file_format : str
+            Format of the file to export the values to. Options are "csv" and
+            "json". Default is "csv".
+
+        Returns
+        -------
+        None
+        """
+        self._generic_export_measured_data(
+            filename=filename,
+            file_format=file_format,
+            data_labels=("t", "latitude", "longitude", "altitude"),
+        )
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 049cde52d..455dcb449 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -4,6 +4,8 @@
 from ..prints.sensors_prints import _GyroscopePrints
 from ..sensors.sensor import InertialSensor
 
+# pylint: disable=too-many-arguments
+
 
 class Gyroscope(InertialSensor):
     """Class for the gyroscope sensor
@@ -210,10 +212,8 @@ def measure(self, time, **kwargs):
                 Derivative of the state vector of the rocket.
             - relative_position : np.array
                 Position of the sensor relative to the rocket center of mass.
-            - gravity : float
-                Gravitational acceleration in m/s^2.
-            - pressure : Function
-                Atmospheric pressure profile as a function of altitude in Pa.
+            - environment : Environment
+                Environment object containing the atmospheric conditions.
         """
         u = kwargs["u"]
         u_dot = kwargs["u_dot"]
diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index 8b0de3b6e..0a1e20bab 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -6,6 +6,7 @@
 from rocketpy.mathutils.vector_matrix import Matrix, Vector
 
 
+# pylint: disable=too-many-statements
 class Sensor(ABC):
     """Abstract class for sensors
 
@@ -183,27 +184,22 @@ def _save_data_multiple(self, data):
     @abstractmethod
     def measure(self, time, **kwargs):
         """Measure the sensor data at a given time"""
-        pass
 
     @abstractmethod
     def quantize(self, value):
         """Quantize the sensor measurement"""
-        pass
 
     @abstractmethod
     def apply_noise(self, value):
         """Add noise to the sensor measurement"""
-        pass
 
     @abstractmethod
     def apply_temperature_drift(self, value):
         """Apply temperature drift to the sensor measurement"""
-        pass
 
     @abstractmethod
     def export_measured_data(self, filename, file_format="csv"):
         """Export the measured values to a file"""
-        pass
 
     def _generic_export_measured_data(self, filename, file_format, data_labels):
         """Export the measured values to a file given the data labels of each
@@ -572,7 +568,7 @@ def apply_temperature_drift(self, value):
 
 
 class ScalarSensor(Sensor):
-    """Model of a scalar sensor (barometer, GPS, etc.). Scalar sensors are used
+    """Model of a scalar sensor (e.g. Barometer). Scalar sensors are used
     to measure a single scalar value. The measurements are not affected by the
     sensor's orientation in the rocket.
 
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index 94985aef9..9357bac98 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -664,10 +664,9 @@ def __simulate(self, verbose):
             # Initialize phase time nodes
             phase.time_nodes = self.TimeNodes()
             # Add first time node to the time_nodes list
-            phase.time_nodes.add_node(phase.t, [], [])
+            phase.time_nodes.add_node(phase.t, [], [], [])
             # Add non-overshootable parachute time nodes
             if self.time_overshoot is False:
-                # TODO: move parachutes to controllers
                 phase.time_nodes.add_parachutes(
                     self.parachutes, phase.t, phase.time_bound
                 )
@@ -717,10 +716,13 @@ def __simulate(self, verbose):
                             u=self.y_sol,
                             u_dot=u_dot,
                             relative_position=relative_position,
+                            environment=self.env,
                             gravity=self.env.gravity.get_value_opt(
                                 self.solution[-1][3]
                             ),
                             pressure=self.env.pressure,
+                            earth_radius=self.env.earth_radius,
+                            initial_coordinates=(self.env.latitude, self.env.longitude),
                         )
 
                 for controller in node._controllers:
@@ -891,7 +893,7 @@ def __simulate(self, verbose):
                             self.flight_phases.add_phase(self.t)
                             # Prepare to leave loops and start new flight phase
                             phase.time_nodes.flush_after(node_index)
-                            phase.time_nodes.add_node(self.t, [], [])
+                            phase.time_nodes.add_node(self.t, [], [], [])
                             phase.solver.status = "finished"
                     # Check for impact event
                     if self.y_sol[2] < self.env.elevation:
@@ -1143,7 +1145,7 @@ def __init_flight_state(self):
             self.out_of_rail_time = self.initial_solution[0]
             self.out_of_rail_time_index = 0
             self.initial_derivative = self.u_dot_generalized
-        if self._controllers:
+        if self._controllers or self.sensors:
             # Handle post process during simulation, get initial accel/forces
             self.initial_derivative(
                 self.t_initial, self.initial_solution[1:], post_processing=True
@@ -3173,6 +3175,47 @@ class attributes which are instances of the Function class. Usage
             encoding="utf-8",
         )
 
+    def export_sensor_data(self, file_name, sensor=None):
+        """Exports sensors data to a file. The file format can be either .csv or
+        .json.
+
+        Parameters
+        ----------
+        file_name : str
+            The file name or path of the exported file. Example: flight_data.csv
+            Do not use forbidden characters, such as / in Linux/Unix and
+            `<, >, :, ", /, \\, | ?, *` in Windows.
+        sensor : Sensor, string, optional
+            The sensor to export data from. Can be given as a Sensor object or
+            as a string with the sensor name. If None, all sensors data will be
+            exported. Default is None.
+        """
+        if sensor is None:
+            data_dict = {}
+            for used_sensor, measured_data in self.sensor_data.items():
+                data_dict[used_sensor.name] = measured_data
+        else:
+            # export data of only that sensor
+            data_dict = {}
+
+            if not isinstance(sensor, str):
+                data_dict[sensor.name] = self.sensor_data[sensor]
+            else:  # sensor is a string
+                matching_sensors = [s for s in self.sensor_data if s.name == sensor]
+
+                if len(matching_sensors) > 1:
+                    data_dict[sensor] = []
+                    for s in matching_sensors:
+                        data_dict[s.name].append(self.sensor_data[s])
+                elif len(matching_sensors) == 1:
+                    data_dict[sensor] = self.sensor_data[matching_sensors[0]]
+                else:
+                    raise ValueError("Sensor not found in the Flight.sensor_data.")
+
+        with open(file_name, "w") as file:
+            json.dump(data_dict, file)
+        print("Sensor data exported to", file_name)
+
     def export_kml(  # TODO: should be moved out of this class.
         self,
         file_name="trajectory.kml",
@@ -3469,8 +3512,6 @@ def __init__(self, t, derivative=None, callbacks=None, clear=True):
                 self.derivative = derivative
                 self.callbacks = callbacks[:] if callbacks is not None else []
                 self.clear = clear
-                self.time_bound = None
-                self.TimeNodes = None
 
             def __repr__(self):
                 name = "None" if self.derivative is None else self.derivative.__name__
@@ -3564,8 +3605,8 @@ def merge(self):
                     # Try to access the node and merge if it exists
                     tmp_dict[time].parachutes += node.parachutes
                     tmp_dict[time].callbacks += node.callbacks
-                    tmp_dict[-1]._component_sensors += node._component_sensors
-                    tmp_dict[-1]._controllers += node._controllers
+                    tmp_dict[time]._component_sensors += node._component_sensors
+                    tmp_dict[time]._controllers += node._controllers
                 except KeyError:
                     # If the node does not exist, add it to the dictionary
                     tmp_dict[time] = node
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index c96dd2364..84f0d910a 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -353,11 +353,15 @@ def inverted_haversine(lat0, lon0, distance, bearing, earth_radius=6.3781e6):
     # Apply inverted Haversine formula
     lat1_rad = math.asin(
         math.sin(lat0_rad) * math.cos(distance / earth_radius)
-        + math.cos(lat0_rad) * math.sin(distance / earth_radius) * math.cos(bearing)
+        + math.cos(lat0_rad)
+        * math.sin(distance / earth_radius)
+        * math.cos(math.radians(bearing))
     )
 
     lon1_rad = lon0_rad + math.atan2(
-        math.sin(bearing) * math.sin(distance / earth_radius) * math.cos(lat0_rad),
+        math.sin(math.radians(bearing))
+        * math.sin(distance / earth_radius)
+        * math.cos(lat0_rad),
         math.cos(distance / earth_radius) - math.sin(lat0_rad) * math.sin(lat1_rad),
     )
 
@@ -928,18 +932,18 @@ def quaternions_to_nutation(e1, e2):
     return (180 / np.pi) * 2 * np.arcsin(-((e1**2 + e2**2) ** 0.5))
 
 
-def euler_to_quaternions(yaw, pitch, roll):
+def euler_to_quaternions(roll, pitch, yaw):
     """Calculates the quaternions (Euler parameters) from the Euler angles in
     yaw, pitch, and roll sequence (3-2-1).
 
     Parameters
     ----------
-    yaw : float
-        Euler angle due to yaw (phi) in degrees
-    pitch : float
-        Euler angle due to pitch (theta) in degrees
     roll : float
         Euler angle due to roll (psi) in degrees
+    pitch : float
+        Euler angle due to pitch (theta) in degrees
+    yaw : float
+        Euler angle due to yaw (phi) in degrees
 
     Returns
     -------
diff --git a/tests/fixtures/rockets/rocket_fixtures.py b/tests/fixtures/rockets/rocket_fixtures.py
index 1a3a6194b..dd524645f 100644
--- a/tests/fixtures/rockets/rocket_fixtures.py
+++ b/tests/fixtures/rockets/rocket_fixtures.py
@@ -253,6 +253,7 @@ def calisto_with_sensors(
     ideal_accelerometer,
     ideal_gyroscope,
     ideal_barometer,
+    ideal_gnss,
 ):
     """Create an object class of the Rocket class to be used in the tests. This
     is the same Calisto rocket that was defined in the calisto fixture, but with
@@ -272,6 +273,7 @@ def calisto_with_sensors(
     calisto.add_sensor(ideal_accelerometer, -0.1180124376577797)
     calisto.add_sensor(ideal_gyroscope, -0.1180124376577797)
     calisto.add_sensor(ideal_barometer, -0.1180124376577797)
+    calisto.add_sensor(ideal_gnss, -0.1180124376577797)
     return calisto
 
 
diff --git a/tests/fixtures/sensors/sensors_fixtures.py b/tests/fixtures/sensors/sensors_fixtures.py
index 5f148d00b..1d01a59c3 100644
--- a/tests/fixtures/sensors/sensors_fixtures.py
+++ b/tests/fixtures/sensors/sensors_fixtures.py
@@ -1,8 +1,8 @@
-import numpy as np
 import pytest
 
 from rocketpy import Accelerometer, Gyroscope
 from rocketpy.sensors.barometer import Barometer
+from rocketpy.sensors.gnss_receiver import GnssReceiver
 
 
 @pytest.fixture
@@ -65,6 +65,15 @@ def noisy_barometer():
     )
 
 
+@pytest.fixture
+def noisy_gnss():
+    return GnssReceiver(
+        sampling_rate=1,
+        position_accuracy=1,
+        altitude_accuracy=1,
+    )
+
+
 @pytest.fixture
 def quantized_accelerometer():
     """Returns an accelerometer with all parameters set to non-default values,
@@ -117,3 +126,10 @@ def ideal_barometer():
     return Barometer(
         sampling_rate=10,
     )
+
+
+@pytest.fixture
+def ideal_gnss():
+    return GnssReceiver(
+        sampling_rate=1,
+    )
diff --git a/tests/test_sensor.py b/tests/integration/test_sensor.py
similarity index 66%
rename from tests/test_sensor.py
rename to tests/integration/test_sensor.py
index ba9a32b75..fe099127e 100644
--- a/tests/test_sensor.py
+++ b/tests/integration/test_sensor.py
@@ -2,11 +2,12 @@
 import os
 
 import numpy as np
-import pytest
 
 from rocketpy.mathutils.vector_matrix import Vector
 from rocketpy.rocket.components import Components
 from rocketpy.sensors.accelerometer import Accelerometer
+from rocketpy.sensors.barometer import Barometer
+from rocketpy.sensors.gnss_receiver import GnssReceiver
 from rocketpy.sensors.gyroscope import Gyroscope
 
 
@@ -24,6 +25,10 @@ def test_sensor_on_rocket(calisto_with_sensors):
     assert isinstance(sensors[1].position, Vector)
     assert isinstance(sensors[2].component, Gyroscope)
     assert isinstance(sensors[2].position, Vector)
+    assert isinstance(sensors[3].component, Barometer)
+    assert isinstance(sensors[3].position, Vector)
+    assert isinstance(sensors[4].component, GnssReceiver)
+    assert isinstance(sensors[4].position, Vector)
 
 
 def test_ideal_sensors(flight_calisto_with_sensors):
@@ -69,6 +74,18 @@ def test_ideal_sensors(flight_calisto_with_sensors):
     sim_data = flight_calisto_with_sensors.pressure(time)
     assert np.allclose(pressure, sim_data, atol=1e-12)
 
+    gnss = flight_calisto_with_sensors.rocket.sensors[4].component
+    time, latitude, longitude, altitude = zip(*gnss.measured_data)
+    latitude = np.array(latitude)
+    longitude = np.array(longitude)
+    altitude = np.array(altitude)
+    sim_latitude = flight_calisto_with_sensors.latitude(time)
+    sim_longitude = flight_calisto_with_sensors.longitude(time)
+    sim_altitude = flight_calisto_with_sensors.altitude(time)
+    assert np.allclose(latitude, sim_latitude, atol=1e-12)
+    assert np.allclose(longitude, sim_longitude, atol=1e-12)
+    assert np.allclose(altitude, sim_altitude, atol=1e-12)
+
 
 def test_export_all_sensors_data(flight_calisto_with_sensors):
     """Test the export of sensor data.
@@ -102,6 +119,10 @@ def test_export_all_sensors_data(flight_calisto_with_sensors):
         list(measurement)
         for measurement in flight_calisto_with_sensors.sensors[3].measured_data
     ]
+    flight_calisto_with_sensors.sensors[4].measured_data = [
+        list(measurement)
+        for measurement in flight_calisto_with_sensors.sensors[4].measured_data
+    ]
     assert (
         sensor_data["Accelerometer"]
         == flight_calisto_with_sensors.sensors[0].measured_data
@@ -112,4 +133,34 @@ def test_export_all_sensors_data(flight_calisto_with_sensors):
     assert (
         sensor_data["Barometer"] == flight_calisto_with_sensors.sensors[3].measured_data
     )
+    assert (
+        sensor_data["GnssReceiver"]
+        == flight_calisto_with_sensors.sensors[4].measured_data
+    )
+    os.remove(filename)
+
+
+def test_export_single_sensor_data(flight_calisto_with_sensors):
+    """Test the export of a single sensor data.
+
+    Parameters
+    ----------
+    flight_calisto_with_sensors : Flight
+        Pytest fixture for the flight of the calisto rocket with a set of ideal
+        sensors.
+    """
+    flight_calisto_with_sensors.export_sensor_data("test_sensor_data.json", "Gyroscope")
+    # read the json and parse as dict
+    filename = "test_sensor_data.json"
+    with open(filename, "r") as f:
+        data = f.read()
+        sensor_data = json.loads(data)
+    # convert list of tuples into list of lists to compare with the json
+    flight_calisto_with_sensors.sensors[2].measured_data = [
+        list(measurement)
+        for measurement in flight_calisto_with_sensors.sensors[2].measured_data
+    ]
+    assert (
+        sensor_data["Gyroscope"] == flight_calisto_with_sensors.sensors[2].measured_data
+    )
     os.remove(filename)
diff --git a/tests/unit/test_flight.py b/tests/unit/test_flight.py
index b5516eea3..115a96413 100644
--- a/tests/unit/test_flight.py
+++ b/tests/unit/test_flight.py
@@ -1,3 +1,5 @@
+import json
+import os
 from unittest.mock import patch
 
 import matplotlib as plt
diff --git a/tests/unit/test_flight_time_nodes.py b/tests/unit/test_flight_time_nodes.py
index 10f6b6c30..446b4523f 100644
--- a/tests/unit/test_flight_time_nodes.py
+++ b/tests/unit/test_flight_time_nodes.py
@@ -14,7 +14,7 @@ def test_time_nodes_init(flight_calisto):
 
 def test_time_nodes_getitem(flight_calisto):
     time_nodes = flight_calisto.TimeNodes()
-    time_nodes.add_node(1.0, [], [])
+    time_nodes.add_node(1.0, [], [], [])
     assert isinstance(time_nodes[0], flight_calisto.TimeNodes.TimeNode)
     assert time_nodes[0].t == 1.0
 
@@ -26,7 +26,7 @@ def test_time_nodes_len(flight_calisto):
 
 def test_time_nodes_add(flight_calisto):
     time_nodes = flight_calisto.TimeNodes()
-    example_node = flight_calisto.TimeNodes.TimeNode(1.0, [], [])
+    example_node = flight_calisto.TimeNodes.TimeNode(1.0, [], [], [])
     time_nodes.add(example_node)
     assert len(time_nodes) == 1
     assert isinstance(time_nodes[0], flight_calisto.TimeNodes.TimeNode)
@@ -35,7 +35,7 @@ def test_time_nodes_add(flight_calisto):
 
 def test_time_nodes_add_node(flight_calisto):
     time_nodes = flight_calisto.TimeNodes()
-    time_nodes.add_node(2.0, [], [])
+    time_nodes.add_node(2.0, [], [], [])
     assert len(time_nodes) == 1
     assert time_nodes[0].t == 2.0
     assert len(time_nodes[0].parachutes) == 0
@@ -53,9 +53,9 @@ def test_time_nodes_add_node(flight_calisto):
 
 def test_time_nodes_sort(flight_calisto):
     time_nodes = flight_calisto.TimeNodes()
-    time_nodes.add_node(3.0, [], [])
-    time_nodes.add_node(1.0, [], [])
-    time_nodes.add_node(2.0, [], [])
+    time_nodes.add_node(3.0, [], [], [])
+    time_nodes.add_node(1.0, [], [], [])
+    time_nodes.add_node(2.0, [], [], [])
     time_nodes.sort()
     assert len(time_nodes) == 3
     assert time_nodes[0].t == 1.0
@@ -65,9 +65,9 @@ def test_time_nodes_sort(flight_calisto):
 
 def test_time_nodes_merge(flight_calisto):
     time_nodes = flight_calisto.TimeNodes()
-    time_nodes.add_node(1.0, [], [])
-    time_nodes.add_node(1.0, [], [])
-    time_nodes.add_node(2.0, [], [])
+    time_nodes.add_node(1.0, [], [], [])
+    time_nodes.add_node(1.0, [], [], [])
+    time_nodes.add_node(2.0, [], [], [])
     time_nodes.merge()
     assert len(time_nodes) == 2
     assert time_nodes[0].t == 1.0
@@ -80,9 +80,9 @@ def test_time_nodes_merge(flight_calisto):
 
 def test_time_nodes_flush_after(flight_calisto):
     time_nodes = flight_calisto.TimeNodes()
-    time_nodes.add_node(1.0, [], [])
-    time_nodes.add_node(2.0, [], [])
-    time_nodes.add_node(3.0, [], [])
+    time_nodes.add_node(1.0, [], [], [])
+    time_nodes.add_node(2.0, [], [], [])
+    time_nodes.add_node(3.0, [], [], [])
     time_nodes.flush_after(1)
     assert len(time_nodes) == 2
     assert time_nodes[0].t == 1.0
@@ -90,14 +90,14 @@ def test_time_nodes_flush_after(flight_calisto):
 
 
 def test_time_node_init(flight_calisto):
-    node = flight_calisto.TimeNodes.TimeNode(1.0, [], [])
+    node = flight_calisto.TimeNodes.TimeNode(1.0, [], [], [])
     assert node.t == 1.0
     assert len(node.parachutes) == 0
     assert len(node.callbacks) == 0
 
 
 def test_time_node_lt(flight_calisto):
-    node1 = flight_calisto.TimeNodes.TimeNode(1.0, [], [])
-    node2 = flight_calisto.TimeNodes.TimeNode(2.0, [], [])
+    node1 = flight_calisto.TimeNodes.TimeNode(1.0, [], [], [])
+    node2 = flight_calisto.TimeNodes.TimeNode(2.0, [], [], [])
     assert node1 < node2
     assert not node2 < node1
diff --git a/tests/unit/test_sensor.py b/tests/unit/test_sensor.py
index 186466ccb..54fde52f9 100644
--- a/tests/unit/test_sensor.py
+++ b/tests/unit/test_sensor.py
@@ -52,6 +52,7 @@
         "quantized_gyroscope",
         "noisy_barometer",
         "quantized_barometer",
+        "noisy_gnss",
     ],
 )
 def test_sensors_prints(sensor, request):
@@ -105,9 +106,6 @@ def test_scalar_quantization(quantized_barometer):
     assert quantized_barometer.quantize(1001) == 1000.96
 
 
-import pytest
-
-
 @pytest.mark.parametrize(
     "sensor, input_value, expected_output",
     [
@@ -156,7 +154,7 @@ def test_quantization(sensor, input_value, expected_output, request):
         "ideal_gyroscope",
     ],
 )
-def test_inertial_measured_data(sensor, request):
+def test_inertial_measured_data(sensor, request, example_plain_env):
     """Test the measured_data property of the Sensor class. Checks if
     the measured data is treated properly when the sensor is added once or more
     than once to the rocket.
@@ -168,7 +166,7 @@ def test_inertial_measured_data(sensor, request):
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
+        environment=example_plain_env,
     )
     assert len(sensor.measured_data) == 1
     sensor.measure(
@@ -176,7 +174,7 @@ def test_inertial_measured_data(sensor, request):
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
+        environment=example_plain_env,
     )
     assert len(sensor.measured_data) == 2
     assert all(isinstance(i, tuple) for i in sensor.measured_data)
@@ -192,7 +190,7 @@ def test_inertial_measured_data(sensor, request):
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
+        environment=example_plain_env,
     )
     assert len(sensor.measured_data) == 2
     assert len(sensor.measured_data[0]) == 3
@@ -202,61 +200,70 @@ def test_inertial_measured_data(sensor, request):
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
+        environment=example_plain_env,
     )
     assert len(sensor.measured_data[0]) == 3
     assert len(sensor.measured_data[1]) == 3
 
 
-def test_scalar_measured_data(ideal_barometer, example_plain_env):
+@pytest.mark.parametrize(
+    "sensor",
+    [
+        "ideal_barometer",
+        "ideal_gnss",
+    ],
+)
+def test_scalar_measured_data(sensor, request, example_plain_env):
     """Test the measure method of ScalarSensor. Checks if saved
     measurement is (P) and if measured_data is [(t, P), ...]
     """
+    sensor = request.getfixturevalue(sensor)
+
     t = TIME
     u = U
 
-    ideal_barometer.measure(
+    sensor.measure(
         t,
         u=u,
         relative_position=Vector([0, 0, 0]),
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
-    assert len(ideal_barometer.measured_data) == 1
-    ideal_barometer.measure(
+    assert len(sensor.measured_data) == 1
+    sensor.measure(
         t,
         u=u,
         relative_position=Vector([0, 0, 0]),
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
-    assert len(ideal_barometer.measured_data) == 2
-    assert all(isinstance(i, tuple) for i in ideal_barometer.measured_data)
+    assert len(sensor.measured_data) == 2
+    assert all(isinstance(i, tuple) for i in sensor.measured_data)
 
     # check case when sensor is added more than once to the rocket
-    ideal_barometer.measured_data = [
-        ideal_barometer.measured_data[:],
-        ideal_barometer.measured_data[:],
+    sensor.measured_data = [
+        sensor.measured_data[:],
+        sensor.measured_data[:],
     ]
-    ideal_barometer._save_data = ideal_barometer._save_data_multiple
-    ideal_barometer.measure(
+    sensor._save_data = sensor._save_data_multiple
+    sensor.measure(
         t,
         u=u,
         relative_position=Vector([0, 0, 0]),
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
-    assert len(ideal_barometer.measured_data) == 2
-    assert len(ideal_barometer.measured_data[0]) == 3
-    assert len(ideal_barometer.measured_data[1]) == 2
-    ideal_barometer.measure(
+    assert len(sensor.measured_data) == 2
+    assert len(sensor.measured_data[0]) == 3
+    assert len(sensor.measured_data[1]) == 2
+    sensor.measure(
         t,
         u=u,
         relative_position=Vector([0, 0, 0]),
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
-    assert len(ideal_barometer.measured_data[0]) == 3
-    assert len(ideal_barometer.measured_data[1]) == 3
+    assert len(sensor.measured_data[0]) == 3
+    assert len(sensor.measured_data[1]) == 3
 
 
-def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
+def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer, example_plain_env):
     """Test the measure method of the Accelerometer class. Checks if saved
     measurement is (ax,ay,az) and if measured_data is [(t, (ax,ay,az)), ...]
     """
@@ -296,7 +303,7 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
         u=U,
         u_dot=U_DOT,
         relative_position=relative_position,
-        gravity=GRAVITY,
+        environment=example_plain_env,
     )
     assert noisy_rotated_accelerometer.measurement == approx([ax, ay, az], rel=0.1)
     assert len(noisy_rotated_accelerometer.measurement) == 3
@@ -306,7 +313,7 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer):
     assert noisy_rotated_accelerometer.measured_data[0][0] == TIME
 
 
-def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
+def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope, example_plain_env):
     """Test the measure method of the Gyroscope class. Checks if saved
     measurement is (wx,wy,wz) and if measured_data is [(t, (wx,wy,wz)), ...]
     """
@@ -337,7 +344,7 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope):
         u=U,
         u_dot=U_DOT,
         relative_position=relative_position,
-        gravity=GRAVITY,
+        environment=example_plain_env,
     )
     assert noisy_rotated_gyroscope.measurement == approx([wx, wy, wz], rel=0.3)
     assert len(noisy_rotated_gyroscope.measurement) == 3
@@ -360,22 +367,88 @@ def test_noisy_barometer(noisy_barometer, example_plain_env):
         time=TIME,
         u=U,
         relative_position=relative_position,
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
     assert noisy_barometer.measurement == approx(P, rel=0.03)
     assert noisy_barometer.measured_data[0][1] == approx(P, rel=0.03)
     assert noisy_barometer.measured_data[0][0] == TIME
 
 
+def test_noisy_gnss(noisy_gnss, example_plain_env):
+    """Test the measure method of the GnssReceiver class. Checks if saved
+    measurement is (latitude, longitude, altitude) and if measured_data is [(t, (latitude, longitude, altitude)), ...]
+    """
+    # expected measurement without noise
+    relative_position = Vector([0.4, 0.4, 1])
+    lat, lon = example_plain_env.latitude, example_plain_env.longitude
+    earth_radius = example_plain_env.earth_radius
+    x, y, z = (Matrix.transformation(U[6:10]) @ relative_position) + Vector(U[0:3])
+    drift = (x**2 + y**2) ** 0.5
+    bearing = (2 * np.pi - np.arctan2(-x, y)) * (180 / np.pi)
+    latitude = np.degrees(
+        np.arcsin(
+            np.sin(np.radians(lat)) * np.cos(drift / earth_radius)
+            + np.cos(np.radians(lat))
+            * np.sin(drift / earth_radius)
+            * np.cos(np.radians(bearing))
+        )
+    )
+    longitude = np.degrees(
+        np.radians(lon)
+        + np.arctan2(
+            np.sin(np.radians(bearing))
+            * np.sin(drift / earth_radius)
+            * np.cos(np.radians(lat)),
+            np.cos(drift / earth_radius)
+            - np.sin(np.radians(lat)) * np.sin(np.radians(latitude)),
+        )
+    )
+    altitude = z
+
+    noisy_gnss.measure(
+        time=TIME,
+        u=U,
+        relative_position=relative_position,
+        environment=example_plain_env,
+    )
+    assert noisy_gnss.measurement == approx([latitude, longitude, altitude], abs=3.2)
+    assert len(noisy_gnss.measurement) == 3
+    assert noisy_gnss.measured_data[0][1:] == approx(
+        [latitude, longitude, altitude], abs=3.2
+    )
+    assert noisy_gnss.measured_data[0][0] == TIME
+
+    # check last measurement considering noise error bounds
+    noisy_gnss.measure(
+        time=TIME,
+        u=U,
+        relative_position=relative_position,
+        environment=example_plain_env,
+    )
+    assert noisy_gnss.measurement == approx([latitude, longitude, altitude], abs=3.2)
+    assert len(noisy_gnss.measurement) == 3
+    assert noisy_gnss.measured_data[1][1:] == approx(
+        [latitude, longitude, altitude], abs=3.2
+    )
+    assert noisy_gnss.measured_data[1][0] == TIME
+
+
 @pytest.mark.parametrize(
     "sensor, file_format, expected_header, expected_keys",
     [
         ("ideal_accelerometer", "csv", "t,ax,ay,az\n", ("ax", "ay", "az")),
-        ("ideal_gyroscope", "csv", "t,wx,wy,wz\n", ("wx", "wy", "wz")),
         ("ideal_accelerometer", "json", None, ("ax", "ay", "az")),
+        ("ideal_gyroscope", "csv", "t,wx,wy,wz\n", ("wx", "wy", "wz")),
         ("ideal_gyroscope", "json", None, ("wx", "wy", "wz")),
         ("ideal_barometer", "csv", "t,pressure\n", ("pressure",)),
         ("ideal_barometer", "json", None, ("pressure",)),
+        (
+            "ideal_gnss",
+            "csv",
+            "t,latitude,longitude,altitude\n",
+            ("latitude", "longitude", "altitude"),
+        ),
+        ("ideal_gnss", "json", None, ("latitude", "longitude", "altitude")),
     ],
 )
 def test_export_data(
@@ -391,16 +464,14 @@ def test_export_data(
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
     sensor.measure(
         time=TIME,
         u=U,
         u_dot=U_DOT,
         relative_position=Vector([0, 0, 0]),
-        gravity=GRAVITY,
-        pressure=example_plain_env.pressure,
+        environment=example_plain_env,
     )
 
     file_name = f"sensors.{file_format}"
diff --git a/tests/unit/test_tools.py b/tests/unit/test_tools.py
index 3079c5286..4b2f8b14f 100644
--- a/tests/unit/test_tools.py
+++ b/tests/unit/test_tools.py
@@ -2,8 +2,8 @@
 import pytest
 
 from rocketpy.tools import (
-    euler_to_quaternions,
     calculate_cubic_hermite_coefficients,
+    euler_to_quaternions,
     find_roots_cubic_function,
 )
 
@@ -20,54 +20,6 @@ def test_euler_to_quaternions(angles, expected_quaternions):
     assert round(q3, 7) == expected_quaternions[3]
 
 
-def test_calculate_cubic_hermite_coefficients():
-    """Test the calculate_cubic_hermite_coefficients method of the Function class."""
-    # Function: f(x) = x**3 + 2x**2 -1 ; derivative: f'(x) = 3x**2 + 4x
-    x = np.array([-3, -2, -1, 0, 1])
-    y = np.array([-10, -1, 0, -1, 2])
-
-    # Selects two points as x0 and x1
-    x0, x1 = 0, 1
-    y0, y1 = -1, 2
-    yp0, yp1 = 0, 7
-
-    a, b, c, d = calculate_cubic_hermite_coefficients(x0, x1, y0, yp0, y1, yp1)
-
-    assert np.isclose(a, 1)
-    assert np.isclose(b, 2)
-    assert np.isclose(c, 0)
-    assert np.isclose(d, -1)
-    assert np.allclose(
-        a * x**3 + b * x**2 + c * x + d,
-        y,
-    )
-
-
-def test_cardanos_root_finding():
-    """Tests the find_roots_cubic_function method of the Function class."""
-    # Function: f(x) = x**3 + 2x**2 -1
-    # roots: (-1 - 5**0.5) / 2; -1; (-1 + 5**0.5) / 2
-
-    roots = list(find_roots_cubic_function(a=1, b=2, c=0, d=-1))
-    roots.sort(key=lambda x: x.real)
-
-    assert np.isclose(roots[0].real, (-1 - 5**0.5) / 2)
-    assert np.isclose(roots[1].real, -1)
-    assert np.isclose(roots[2].real, (-1 + 5**0.5) / 2)
-
-    assert np.isclose(roots[0].imag, 0)
-    assert np.isclose(roots[1].imag, 0)
-    assert np.isclose(roots[2].imag, 0)
-
-
-import numpy as np
-
-from rocketpy.tools import (
-    calculate_cubic_hermite_coefficients,
-    find_roots_cubic_function,
-)
-
-
 def test_calculate_cubic_hermite_coefficients():
     """Test the calculate_cubic_hermite_coefficients method of the Function class."""
     # Function: f(x) = x**3 + 2x**2 -1 ; derivative: f'(x) = 3x**2 + 4x
diff --git a/tests/unit/test_tools_matrix.py b/tests/unit/test_tools_matrix.py
index 5d9e4b3f6..c2b5f0148 100644
--- a/tests/unit/test_tools_matrix.py
+++ b/tests/unit/test_tools_matrix.py
@@ -245,9 +245,9 @@ def test_matrix_transformation():
 
 
 def test_matrix_transformation_euler_angles():
-    phi = 90
+    phi = 0
     theta = 0
-    psi = 0
+    psi = 90
     matrix = Matrix.transformation_euler_angles(phi, theta, psi)
     matrix = matrix.round(12)
     # Check that the matrix is orthogonal

From 6899e9e25d30bc57b368153c737c5120eda49922 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Sat, 7 Sep 2024 21:47:07 -0300
Subject: [PATCH 113/120] DEV: updates changelog

---
 CHANGELOG.md | 13 +------------
 1 file changed, 1 insertion(+), 12 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index f025d8fb3..a4bf8a3cb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -30,20 +30,9 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
 <!-- These are the changes that were not released yet, please add them correctly.
 Attention: The newest changes should be on top -->
 
-## [1.3.0.post1] - 2024-06-02
-
-You can install this version by running `pip install rocketpy==1.3.0.post1`
-
-### Fixed
-
-- BUG: pyproject.toml Main Module Finding. [#616](https://github.com/RocketPy-Team/RocketPy/pull/616)
-
-## [1.3.0] - 2024-06-01
-
-You can install this version by running `pip install rocketpy==1.3.0`
-
 ### Added
 
+- ENH: Adds Sensors classes [683](https://github.com/RocketPy-Team/RocketPy/pull/683)
 - ENH: Add STFT function to Function class [#620](https://github.com/RocketPy-Team/RocketPy/pull/620) 
 - ENH: Rocket Axis Definition [#635](https://github.com/RocketPy-Team/RocketPy/pull/635)
 

From 6e44d8fd5f97a57398ff5919f7ad2fd15c565ce9 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Sat, 7 Sep 2024 22:20:32 -0300
Subject: [PATCH 114/120] MNT: fix lint

---
 .vscode/settings.json            |   5 +
 tests/integration/test_sensor.py | 107 ++++++++--------
 tests/unit/test_sensor.py        | 204 ++++++++++++++++++++++---------
 3 files changed, 201 insertions(+), 115 deletions(-)

diff --git a/.vscode/settings.json b/.vscode/settings.json
index bc43e427c..5e557842c 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -132,11 +132,14 @@
         "github",
         "Glauert",
         "gmaps",
+        "Gnss",
         "Gomes",
         "Gonçalvez",
         "grav",
         "Guilherme",
         "Haim",
+        "headlength",
+        "headwidth",
         "hemis",
         "hgtprs",
         "hgtsfc",
@@ -212,6 +215,7 @@
         "noaaruc",
         "noaarucsounding",
         "num2pydate",
+        "numericalunits",
         "numfig",
         "numpy",
         "numref",
@@ -235,6 +239,7 @@
         "repr",
         "reynolds",
         "rightarrow",
+        "rmul",
         "ROABs",
         "rocketpy",
         "rocketusage",
diff --git a/tests/integration/test_sensor.py b/tests/integration/test_sensor.py
index fe099127e..2998b5f99 100644
--- a/tests/integration/test_sensor.py
+++ b/tests/integration/test_sensor.py
@@ -2,6 +2,7 @@
 import os
 
 import numpy as np
+import pytest
 
 from rocketpy.mathutils.vector_matrix import Vector
 from rocketpy.rocket.components import Components
@@ -31,60 +32,58 @@ def test_sensor_on_rocket(calisto_with_sensors):
     assert isinstance(sensors[4].position, Vector)
 
 
-def test_ideal_sensors(flight_calisto_with_sensors):
-    """Test the ideal sensors. All types of sensors are here to reduce
-    testing time.
-
-    Parameters
-    ----------
-    flight_calisto_with_sensors : Flight
-        Pytest fixture for the flight of the calisto rocket with an ideal accelerometer and a gyroscope.
-    """
-    accelerometer = flight_calisto_with_sensors.rocket.sensors[0].component
-    time, ax, ay, az = zip(*accelerometer.measured_data[0])
-    ax = np.array(ax)
-    ay = np.array(ay)
-    az = np.array(az)
-    a = np.sqrt(ax**2 + ay**2 + az**2)
-    sim_accel = flight_calisto_with_sensors.acceleration(time)
-
-    # tolerance is bounded to numerical errors in the transformation matrixes
-    assert np.allclose(a, sim_accel, atol=1e-12)
-    # check if both added accelerometer instances saved the same data
-    assert (
-        flight_calisto_with_sensors.sensors[0].measured_data[0]
-        == flight_calisto_with_sensors.sensors[0].measured_data[1]
-    )
-
-    gyroscope = flight_calisto_with_sensors.rocket.sensors[2].component
-    time, wx, wy, wz = zip(*gyroscope.measured_data)
-    wx = np.array(wx)
-    wy = np.array(wy)
-    wz = np.array(wz)
-    w = np.sqrt(wx**2 + wy**2 + wz**2)
-    flight_wx = np.array(flight_calisto_with_sensors.w1(time))
-    flight_wy = np.array(flight_calisto_with_sensors.w2(time))
-    flight_wz = np.array(flight_calisto_with_sensors.w3(time))
-    sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
-    assert np.allclose(w, sim_w, atol=1e-12)
-
-    barometer = flight_calisto_with_sensors.rocket.sensors[3].component
-    time, pressure = zip(*barometer.measured_data)
-    pressure = np.array(pressure)
-    sim_data = flight_calisto_with_sensors.pressure(time)
-    assert np.allclose(pressure, sim_data, atol=1e-12)
-
-    gnss = flight_calisto_with_sensors.rocket.sensors[4].component
-    time, latitude, longitude, altitude = zip(*gnss.measured_data)
-    latitude = np.array(latitude)
-    longitude = np.array(longitude)
-    altitude = np.array(altitude)
-    sim_latitude = flight_calisto_with_sensors.latitude(time)
-    sim_longitude = flight_calisto_with_sensors.longitude(time)
-    sim_altitude = flight_calisto_with_sensors.altitude(time)
-    assert np.allclose(latitude, sim_latitude, atol=1e-12)
-    assert np.allclose(longitude, sim_longitude, atol=1e-12)
-    assert np.allclose(altitude, sim_altitude, atol=1e-12)
+class TestIdealSensors:
+    """Test a flight with ideal sensors on the rocket."""
+
+    @pytest.fixture(autouse=True)
+    def setup(self, flight_calisto_with_sensors):
+        """Setup an flight fixture for all tests."""
+        self.flight = flight_calisto_with_sensors
+
+    def test_accelerometer(self):
+        """Test an ideal accelerometer."""
+        accelerometer = self.flight.rocket.sensors[0].component
+        time, ax, ay, az = zip(*accelerometer.measured_data[0])
+        a = np.sqrt(np.array(ax) ** 2 + np.array(ay) ** 2 + np.array(az) ** 2)
+        sim_accel = self.flight.acceleration(time)
+
+        # tolerance is bounded to numerical errors in the transformation matrixes
+        assert np.allclose(a, sim_accel, atol=1e-12)
+        # check if both added accelerometer instances saved the same data
+        assert (
+            self.flight.sensors[0].measured_data[0]
+            == self.flight.sensors[0].measured_data[1]
+        )
+
+    def test_gyroscope(self):
+        """Test an ideal gyroscope."""
+        gyroscope = self.flight.rocket.sensors[2].component
+        time, wx, wy, wz = zip(*gyroscope.measured_data)
+        w = np.sqrt(np.array(wx) ** 2 + np.array(wy) ** 2 + np.array(wz) ** 2)
+        flight_wx = np.array(self.flight.w1(time))
+        flight_wy = np.array(self.flight.w2(time))
+        flight_wz = np.array(self.flight.w3(time))
+        sim_w = np.sqrt(flight_wx**2 + flight_wy**2 + flight_wz**2)
+        assert np.allclose(w, sim_w, atol=1e-12)
+
+    def test_barometer(self):
+        """Test an ideal barometer."""
+        barometer = self.flight.rocket.sensors[3].component
+        time, pressure = zip(*barometer.measured_data)
+        pressure = np.array(pressure)
+        sim_data = self.flight.pressure(time)
+        assert np.allclose(pressure, sim_data, atol=1e-12)
+
+    def test_gnss_receiver(self):
+        """Test an ideal GnssReceiver."""
+        gnss = self.flight.rocket.sensors[4].component
+        time, latitude, longitude, altitude = zip(*gnss.measured_data)
+        sim_latitude = self.flight.latitude(time)
+        sim_longitude = self.flight.longitude(time)
+        sim_altitude = self.flight.altitude(time)
+        assert np.allclose(np.array(latitude), sim_latitude, atol=1e-12)
+        assert np.allclose(np.array(longitude), sim_longitude, atol=1e-12)
+        assert np.allclose(np.array(altitude), sim_altitude, atol=1e-12)
 
 
 def test_export_all_sensors_data(flight_calisto_with_sensors):
diff --git a/tests/unit/test_sensor.py b/tests/unit/test_sensor.py
index 54fde52f9..73f8e7dcc 100644
--- a/tests/unit/test_sensor.py
+++ b/tests/unit/test_sensor.py
@@ -270,11 +270,11 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer, example_plain_
 
     # calculate acceleration at sensor position in inertial frame
     relative_position = Vector([0.4, 0.4, 1])
-    a_I = Vector(U_DOT[3:6]) + Vector([0, 0, -GRAVITY])
+    inertial_acceleration = Vector(U_DOT[3:6]) + Vector([0, 0, -GRAVITY])
     omega = Vector(U[10:13])
     omega_dot = Vector(U_DOT[10:13])
-    accel = (
-        a_I
+    acceleration = (
+        inertial_acceleration
         + Vector.cross(omega_dot, relative_position)
         + Vector.cross(omega, Vector.cross(omega, relative_position))
     )
@@ -291,7 +291,7 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer, example_plain_
     total_rotation = sensor_rotation @ cross_axis_sensitivity
     rocket_rotation = Matrix.transformation(U[6:10])
     # expected measurement without noise
-    ax, ay, az = total_rotation @ (rocket_rotation @ accel)
+    ax, ay, az = total_rotation @ (rocket_rotation @ acceleration)
     # expected measurement with constant bias
     ax += 0.5
     ay += 0.5
@@ -434,31 +434,21 @@ def test_noisy_gnss(noisy_gnss, example_plain_env):
 
 
 @pytest.mark.parametrize(
-    "sensor, file_format, expected_header, expected_keys",
+    "sensor, file_format, expected_header",
     [
-        ("ideal_accelerometer", "csv", "t,ax,ay,az\n", ("ax", "ay", "az")),
-        ("ideal_accelerometer", "json", None, ("ax", "ay", "az")),
-        ("ideal_gyroscope", "csv", "t,wx,wy,wz\n", ("wx", "wy", "wz")),
-        ("ideal_gyroscope", "json", None, ("wx", "wy", "wz")),
-        ("ideal_barometer", "csv", "t,pressure\n", ("pressure",)),
-        ("ideal_barometer", "json", None, ("pressure",)),
-        (
-            "ideal_gnss",
-            "csv",
-            "t,latitude,longitude,altitude\n",
-            ("latitude", "longitude", "altitude"),
-        ),
-        ("ideal_gnss", "json", None, ("latitude", "longitude", "altitude")),
+        ("ideal_accelerometer", "csv", "t,ax,ay,az\n"),
+        ("ideal_gyroscope", "csv", "t,wx,wy,wz\n"),
+        ("ideal_barometer", "csv", "t,pressure\n"),
+        ("ideal_gnss", "csv", "t,latitude,longitude,altitude\n"),
     ],
 )
-def test_export_data(
-    sensor, file_format, expected_header, expected_keys, request, example_plain_env
+def test_export_data_csv(
+    sensor, file_format, expected_header, request, example_plain_env
 ):
-    """Test the export_data method of the sensors. Checks if the data is
-    exported correctly in the specified file_format.
-    """
+    """Test the export_data method for CSV format."""
     sensor = request.getfixturevalue(sensor)
 
+    # Perform measurement
     sensor.measure(
         time=TIME,
         u=U,
@@ -466,6 +456,40 @@ def test_export_data(
         relative_position=Vector([0, 0, 0]),
         environment=example_plain_env,
     )
+    file_name = f"sensors.{file_format}"
+
+    # Export data
+    sensor.export_measured_data(file_name, file_format=file_format)
+
+    # Check CSV contents
+    with open(file_name, "r") as file:
+        contents = file.read()
+
+    expected_data = expected_header
+    for data in sensor.measured_data:
+        expected_data += ",".join(map(str, data)) + "\n"
+
+    assert contents == expected_data
+
+    os.remove(file_name)
+
+
+@pytest.mark.parametrize(
+    "sensor, file_format, expected_keys",
+    [
+        ("ideal_accelerometer", "json", ("ax", "ay", "az")),
+        ("ideal_gyroscope", "json", ("wx", "wy", "wz")),
+        ("ideal_barometer", "json", ("pressure",)),
+        ("ideal_gnss", "json", ("latitude", "longitude", "altitude")),
+    ],
+)
+def test_export_data_json(
+    sensor, file_format, expected_keys, request, example_plain_env
+):
+    """Test the export_data method for JSON format."""
+    sensor = request.getfixturevalue(sensor)
+
+    # Perform measurement
     sensor.measure(
         time=TIME,
         u=U,
@@ -473,61 +497,119 @@ def test_export_data(
         relative_position=Vector([0, 0, 0]),
         environment=example_plain_env,
     )
+    file_name = f"sensors.{file_format}"
+
+    # Export data
+    sensor.export_measured_data(file_name, file_format=file_format)
+
+    # Check JSON contents
+    with open(file_name, "r") as file:
+        contents = json.load(file)
+
+    expected_data = {"t": []}
+    for key in expected_keys:
+        expected_data[key] = []
+
+    for data in sensor.measured_data:
+        expected_data["t"].append(data[0])
+        for i, key in enumerate(expected_keys):
+            expected_data[key].append(data[i + 1])
 
+    assert contents == expected_data
+
+    os.remove(file_name)
+
+
+@pytest.mark.parametrize(
+    "sensor, file_format, expected_header",
+    [
+        ("ideal_accelerometer", "csv", "t,ax,ay,az\n"),
+        ("ideal_gyroscope", "csv", "t,wx,wy,wz\n"),
+    ],
+)
+def test_export_multiple_sensors_csv(
+    sensor, file_format, expected_header, request, example_plain_env
+):
+    """Test exporting data for multiple instances in CSV format."""
+    sensor = request.getfixturevalue(sensor)
+
+    # Perform measurement
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        environment=example_plain_env,
+    )
+    sensor.measured_data = [sensor.measured_data[:], sensor.measured_data[:]]
     file_name = f"sensors.{file_format}"
 
+    # Export multiple data
     sensor.export_measured_data(file_name, file_format=file_format)
 
-    if file_format == "csv":
-        with open(file_name, "r") as file:
-            contents = file.read()
+    # Check CSV for both instances
+    with open(f"{file_name}_1", "r") as file:
+        contents_1 = file.read()
 
-        expected_data = expected_header
-        for data in sensor.measured_data:
-            expected_data += ",".join(map(str, data)) + "\n"
+    with open(f"{file_name}_2", "r") as file:
+        contents_2 = file.read()
 
-        assert contents == expected_data
+    expected_data = expected_header
+    for data in sensor.measured_data[0]:
+        expected_data += ",".join(map(str, data)) + "\n"
 
-    elif file_format == "json":
-        with open(file_name, "r") as file:
-            contents = json.load(file)
+    assert contents_1 == expected_data
+    assert contents_2 == expected_data
 
-        expected_data = {"t": []}
-        for key in expected_keys:
-            expected_data[key] = []
+    os.remove(f"{file_name}_1")
+    os.remove(f"{file_name}_2")
 
-        for data in sensor.measured_data:
-            expected_data["t"].append(data[0])
-            for i, key in enumerate(expected_keys):
-                expected_data[key].append(data[i + 1])
 
-        assert contents == expected_data
+@pytest.mark.parametrize(
+    "sensor, file_format, expected_keys",
+    [
+        ("ideal_accelerometer", "json", ("ax", "ay", "az")),
+        ("ideal_gyroscope", "json", ("wx", "wy", "wz")),
+    ],
+)
+def test_export_multiple_sensors_json(
+    sensor, file_format, expected_keys, request, example_plain_env
+):
+    """Test exporting data for multiple instances in JSON format."""
+    sensor = request.getfixturevalue(sensor)
 
-    # check exports for sensors added more than once to the rocket
-    sensor.measured_data = [
-        sensor.measured_data[:],
-        sensor.measured_data[:],
-    ]
+    # Perform measurement
+    sensor.measure(
+        time=TIME,
+        u=U,
+        u_dot=U_DOT,
+        relative_position=Vector([0, 0, 0]),
+        environment=example_plain_env,
+    )
+    sensor.measured_data = [sensor.measured_data[:], sensor.measured_data[:]]
+    file_name = f"sensors.{file_format}"
+
+    # Export multiple data
     sensor.export_measured_data(file_name, file_format=file_format)
 
-    if file_format == "csv":
-        with open(f"{file_name}_1", "r") as file:
-            contents = file.read()
-        assert contents == expected_data
+    # Check JSON for both instances
+    with open(f"{file_name}_1", "r") as file:
+        contents_1 = json.load(file)
 
-        with open(f"{file_name}_2", "r") as file:
-            contents = file.read()
-        assert contents == expected_data
+    with open(f"{file_name}_2", "r") as file:
+        contents_2 = json.load(file)
 
-    elif file_format == "json":
-        with open(f"{file_name}_1", "r") as file:
-            contents = json.load(file)
-        assert contents == expected_data
+    expected_data = {"t": []}
+    for key in expected_keys:
+        expected_data[key] = []
 
-        with open(f"{file_name}_2", "r") as file:
-            contents = json.load(file)
-        assert contents == expected_data
+    for data in sensor.measured_data[0]:
+        expected_data["t"].append(data[0])
+        for i, key in enumerate(expected_keys):
+            expected_data[key].append(data[i + 1])
+
+    assert contents_1 == expected_data
+    assert contents_2 == expected_data
 
-    os.remove(file_name)
     os.remove(f"{file_name}_1")
     os.remove(f"{file_name}_2")

From 1a3506768aa319881e503695f4de0fb52f2c67ef Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Sat, 7 Sep 2024 23:04:01 -0300
Subject: [PATCH 115/120] DOC: improve sensors documentation

---
 docs/notebooks/sensors_testing.ipynb          | 208 ++++++++++++------
 .../classes/sensors/abstract/index.rst        |  11 +
 .../sensors/abstract/inertial_sensor.rst      |   5 +
 .../sensors/abstract/scalar_sensor.rst        |   5 +
 .../classes/sensors/abstract/sensor.rst       |   5 +
 .../classes/sensors/accelerometer.rst         |   5 +
 docs/reference/classes/sensors/barometer.rst  |   5 +
 .../classes/sensors/gnss_receiver.rst         |   5 +
 docs/reference/classes/sensors/gyroscope.rst  |   5 +
 docs/reference/classes/sensors/index.rst      |  12 +
 docs/user/index.rst                           |   1 +
 11 files changed, 203 insertions(+), 64 deletions(-)
 create mode 100644 docs/reference/classes/sensors/abstract/index.rst
 create mode 100644 docs/reference/classes/sensors/abstract/inertial_sensor.rst
 create mode 100644 docs/reference/classes/sensors/abstract/scalar_sensor.rst
 create mode 100644 docs/reference/classes/sensors/abstract/sensor.rst
 create mode 100644 docs/reference/classes/sensors/accelerometer.rst
 create mode 100644 docs/reference/classes/sensors/barometer.rst
 create mode 100644 docs/reference/classes/sensors/gnss_receiver.rst
 create mode 100644 docs/reference/classes/sensors/gyroscope.rst
 create mode 100644 docs/reference/classes/sensors/index.rst

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors_testing.ipynb
index e2b987c6b..15af3ac0b 100644
--- a/docs/notebooks/sensors_testing.ipynb
+++ b/docs/notebooks/sensors_testing.ipynb
@@ -8,9 +8,9 @@
     "id": "nvAT8wcRNVEk"
    },
    "source": [
-    "# -----------\n",
+    "# Sensor Class usage\n",
     "\n",
-    "notebook to test sensors... should not be merged"
+    "This code aims to briefly exemplify the usage of the Sensor classes.\n"
    ]
   },
   {
@@ -42,6 +42,13 @@
     "%matplotlib inline"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create an Environment"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -77,7 +84,6 @@
       "Atmospheric Model Type: custom_atmosphere\n",
       "custom_atmosphere Maximum Height: 10.000 km\n",
       "\n",
-      "\n",
       "Surface Atmospheric Conditions\n",
       "\n",
       "Surface Wind Speed: 4.69 m/s\n",
@@ -103,7 +109,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 900x450 with 4 Axes>"
       ]
@@ -120,6 +126,13 @@
     "env.info()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create a Motor"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 4,
@@ -150,6 +163,13 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create a Rocket"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 5,
@@ -195,6 +215,13 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Adds Sensors to the Rocket"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -359,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -373,12 +400,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -393,12 +420,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -411,6 +438,13 @@
     "calisto.draw(plane=\"yz\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add Air Brakes to the Rocket"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 13,
@@ -503,6 +537,13 @@
     "# air_brakes.all_info()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulate Flight"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 16,
@@ -524,6 +565,13 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualize the results"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 17,
@@ -538,17 +586,28 @@
     }
    ],
    "source": [
-    "barometer_clean.export_measured_data(\"aaaa.csv\")"
+    "# To export sensor data to a csv file:\n",
+    "barometer_clean.export_measured_data(\"exported_barometer_data.csv\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -558,17 +617,27 @@
     }
    ],
    "source": [
-    "test_flight.altitude()"
+    "# To visualize the altitude.\n",
+    "# Notice that the air brakes makes the rocket achieve a perfect apogee\n",
+    "test_flight.altitude()\n",
+    "test_flight.pressure()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Accelerometer"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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IREZGmoiICNOnTx/z8MMP17hPTnVfVuFHZxFnZmYawKxbt67W9axcudL06dPHeDyeav++p7odNamPs5msyg1u0vLy8oiOjiY3N7dhBgO/9mvY8p7/ecchcMP8H+Z9NRfm3wamspuu5RnQ/wbodSVEt63fOvZvhjm/OPG4nfPvhJ/fU7/rFZGTVlJSQmZmJh06dDjlOwU3N8YYOnfuzO23317tjFWxtxN9Fmr7/W2/A7SnI98PI+6rBYk1s2HBHYCBLpfAoP+FdoP8h4caQqtu8LsP4YM7IfMzCG/pHzB8xkXw/VpYNcN/FlRYLKTd3jA1iIg0gAMHDvD666+TlZXFjTfeGOxy5DSjMFMffOU/PC+uvLz3ymf9p1IDnH0zXPII1MNtzn9SfGf47bxjp/e52j8wePFkWHwfpJ4Lbfo3fD0iIvWgVatWxMfH8/zzzxMbGxvscuQ0ozBTH6r1zByGT6fDxw/5X5/3B0i/v+F6Y07GoHHw/ZewcT68dRPcugw8Lfzz9n3tP6Oqdd/To1YRkaM0gxERUgdBu2hek+I9KsyUF/4QZC788+kTZMBfxy8fg6g2/jOf3h3nv8bNWzfBc4Ph+QvgzVHgLf+pJYmIiJw2FGbqw9E9M1UuehAuvOv0CTJVwuPgqtngcME3b8Nf28F/3/xh/sb5/nE++l+QiIjYhMJMffhxmPnF3+C8Y6+MeNpIHQiXPQmOyitDxnaA0Yvh12/4L9S37mX/HcBFRERsQGNm6kPVAODLn4HkMyGxZ3DrqY0zR0CnIf77SrU9G1yVl99On+ofJLzwbv94mrBYKMmDlHP8F/ITERE5zSjM1Adf5TVkotvaI8hUiUr2P442aBzs+8p/peJ5t/4w3d0CJm4GT2Tj1igiIvITdJipPlQdZnKEnLidHViWv4dp4G0QnQqJlXdcLcv33/xSRETkNKMwUx+qzv5xNJGOrpAwuOQvcMd/4bbP/YehAHJ2BbcuEbENy7KOucljc9W+fXsef/zxYJfRpDWRb9/g8vkqcADrvs+noPRAsMupd12dSbQCKg7t1C+MiJCVlcXDDz/Me++9x/fff0+rVq3o168f48ePZ+jQocEur0avvfYav/nNb/j973/PM888E+xybGXq1KnMnz+f9evXB7uU49J3Uz3IKSgmDrj33S18Y0qDXU69+6PLwVgXrPvqK84eHOxqRCSYvv32W8477zxiYmKYPn06vXv3pry8nA8//JAxY8awefPmYJdYoxdffJE777yT5557jkcffdRW98MqKyvD7XYHu4w6a8jt0GGm+lB5mCkxJoLuraOa3KMw3H9DTEfu7mDuZRE5Ddx+++1YlsXq1au58sor6dKlCz179mTChAl88cUXx33fnj17uOaaa4iJiSEuLo7LL7+cb7/9NjD/P//5DxdddBHx8fFER0dzwQUX8OWXX1ZbhmVZvPDCC1xxxRWEh4fTuXNn3n333Z+sOTMzkxUrVnD33XfTpUsX3n777WPazJo1i549e+LxeGjdujVjx44NzMvJyeHWW28lMTGR0NBQevXqxYIFCwLzP//8cwYPHkxYWBgpKSmMGzeOwsLC49aTk5PDTTfdREJCAlFRUfz85z/nq6++CsyfOnUq/fr144UXXqh288Xdu3dz+eWXExkZSVRUFNdccw3Z2dnHvG/WrFmkpqYSGRnJ7bffjtfr5ZFHHiEpKYlWrVrx8MMP17qeOXPmcP/99/PVV19hWRaWZTFnzpw6bUdDUM9MPXDgP5vpnst606nHgCBXU/++W1sI/36GuLJ9GGOwTrcLAYo0BcZAeVFw1h0SXqsLfB4+fJiFCxfy8MMPExERccz8mJiYGt9XXl5ORkYGaWlpfPbZZ7hcLh566CGGDRvG119/jdvtJj8/n5EjR/LUU09hjOHRRx/lF7/4Bdu2baNFixaBZd1///088sgjTJ8+naeeeooRI0awa9cu4uLijlv37NmzufTSS4mOjuY3v/kNL774Ir/+9a8D82fMmMGECRP4y1/+wiWXXEJubi7Lly8HwOfzcckll5Cfn88///lPOnXqxMaNG3E6nQDs2LGDYcOG8dBDDzFr1iwOHDjA2LFjGTt2LLNnz66xnquvvpqwsDA++OADoqOjee655xg6dChbt24NbMf27dt56623ePvtt3E6nfh8vkCQWbZsGRUVFYwZM4Zrr72WpUuXBpa9Y8cOPvjgAxYuXMiOHTu46qqr2LlzJ126dGHZsmWsWLGC3/3ud6SnpzNw4MCfrOfaa69lw4YNLFy4kI8++giA6OjoU96OBmOagdzcXAOY3NzcBll+3uREY6ZEmd3b/tsgyw+2kv07jJkSZUomx5n9uUXBLkekSSguLjYbN240xcXF/gmlBcZMiQrOo7SgVjWvWrXKAObtt9/+ybaAmTdvnjHGmJdfftl07drV+Hy+wPzS0lITFhZmPvzwwxrf7/V6TYsWLcy///3vasu89957A68LCgoMYD744IPj1uH1ek1KSoqZP3++McaYAwcOGLfbbXbu3Blok5ycbO65554a3//hhx8ah8NhtmzZUuP80aNHm1tuuaXatM8++8w4HI7Av227du3MY489FpgXFRVlSkpKqr2nU6dO5rnnnjPGGDNlyhQTEhJi9u/fH5i/aNEi43Q6ze7duwPTvvnmGwOY1atXB94XHh5u8vLyAm0yMjJM+/btjdfrDUzr2rWrmTZt2knV07dv32O28VS2oybHfBaOUtvvb/XM1ANXZc+MO6QJnJpdA09cKhU48FgVfLc7k4RePYJdkogEgTnF25x89dVXbN++vVoPC0BJSQk7duwAIDs7m3vvvZelS5eyf/9+vF4vRUVF7N5d/fB2nz59As8jIiKIiopi//79x1334sWLKSws5Be/+AUA8fHxXHTRRcyaNYsHH3yQ/fv3s3fv3uMOXF6/fj1t27alS5cux922r7/+mldeeSUwzRiDz+cjMzOT7t27H9O+oKCAli1bVpteXFwc2BcA7dq1IyEhIfB606ZNpKSkkJKSEpjWo0cPYmJi2LRpE2ef7T/rtH379tX2c2JiIk6nE4fDUW1a1T6rbT01bfepbEdDUZipI6/P4KwKMx5PkKtpIE4Xhx3xtPLtp+hAJqAwI1LvQsLhz3uDt+5a6Ny5M5ZlnfQg34KCAgYMGFDtC79K1RfdyJEjOXToEE888QTt2rXD4/GQlpZGWVlZ9VJ/9J9Gy7Lw+XzHXfeLL77I4cOHCQsLC0zz+Xx8/fXX3H///dWm1+Sn5hcUFHDrrbcybtyxt7BJTU2tsX3r1q2rHRqqcvRhupoO49VGTfvnRPustvX8WENvx8lSmKmjsgofHvy/FE1htPnx5Hha06p4PxWHvg12KSJNk2WBu3H+8J+quLg4MjIyeOaZZxg3btwxX1Q5OTk1fgH279+fuXPn0qpVK6Kiompc9vLly3n22WcDPSh79uzh4MGDdar30KFDvPPOO7z++uv07PnD1dm9Xi8/+9nPWLRoEcOGDaN9+/YsWbKEIUOGHLOMPn368N1337F169Yae2f69+/Pxo0bOeOMM2pVU//+/cnKysLlctG+fftab0v37t3Zs2cPe/bsCfTObNy4kZycHHr0OPX/YNamHrfbjdfrPen3NSadzVRH5RXlOCx/16vL1TQPMwEUhbXxP8ndE9xCRCSonnnmGbxeL+eccw5vvfUW27ZtY9OmTTz55JOkpaXV+J4RI0YQHx/P5ZdfzmeffUZmZiZLly5l3LhxfPfdd4C/1+fll19m06ZNrFq1ihEjRvxkr8hPefnll2nZsiXXXHMNvXr1Cjz69u3LL37xC1588UXAf9bNo48+ypNPPsm2bdv48ssveeqppwC44IILOP/887nyyitZvHgxmZmZgQG2AHfddRcrVqxg7NixrF+/nm3btvHOO+9UOxvqaOnp6aSlpTF8+HAWLVrEt99+y4oVK7jnnntYs2bNcbclPT2d3r17M2LECL788ktWr17NDTfcwAUXXMBZZ511yvuoNvW0b9+ezMxM1q9fz8GDByktLT3l7WgoCjN15C0vDzxvymGmrIX/9Gx3wXdBrkREgqljx458+eWXDBkyhIkTJ9KrVy8uuugilixZwowZM2p8T3h4OJ9++impqan86le/onv37owePZqSkpJAT82LL77IkSNH6N+/P7/97W8ZN24crVq1qlOts2bN4oorrqjxDMwrr7ySd999l4MHDzJy5Egef/xxnn32WXr27Mkvf/lLtm3bFmj71ltvcfbZZ3P99dfTo0cP7rzzzkBPRZ8+fVi2bBlbt25l8ODBnHnmmUyePJnk5ORj1gn+Qzzvv/8+559/PjfeeCNdunThuuuuY9euXSQmJh53WyzL4p133iE2Npbzzz+f9PR0OnbsyNy5c+u0j2pTz5VXXsmwYcMYMmQICQkJvPbaa6e8HQ3FMqc6ostG8vLyiI6OJjc397hdnKfqwOHDJDzZAQDz571Yp3k38alaPe9JzvnqPv4bOoDed38c7HJEbK+kpITMzMwGv/6GyOnuRJ+F2n5/q2emjnxH9cxYTeFGk8cR0rI9ALFlWcEtRERE5EcUZurI6z1qpH1TudFkDWKTOwGQ4N2P8Xl/orWIiEjjUZipI1+Fv2fGayxwNN3dmdS2E15j4bHKOXzg+2CXIyIiEtB0v30bSUVVmLEa8DLNp4HQ0FAOWP6LIx3Yve0nWouIiDQehZk68nkrAPDStMMMQI47yf9z3/GvCikiItLYFGbqyFvuHzNT0QzCTFGE/1oz5Qe/DW4hIk1IMzihVOSE6uMzoDBTRz5v5WGmZhBmfFH+S3NbebpwnkhdVV1ivqgoSHfKFjlNVH0GfnzbhZPRdE+/aSQ/HGZq+rvSFdcOdkFEUZDuHyPShDidTmJiYgI3/AsPD6/x4m4iTZUxhqKiIvbv309MTAxO56l3CjT9b+AGFjibyWr6nVwRif6LA8aW7wtyJSJNQ1KSfxzaie76LNLUxcTEBD4Lp0phpo58Fc1nAHBcG/+N1JJ8+ykurSDMo18fkbqwLIvWrVvTqlUryo+6AKdIcxESElKnHpkq+jaqo8CYGavp78q41h3wYRFqlbNp97d071y7u8SKyIk5nc56+YMu0lw1/WMjDcxUhhlfE7/ODIDl8nDI4b/WTF7WziBXIyIi4qcwU0dVPTO+ZnCYCSA3xH9cs/RgZpArERER8VOYqSPjqxwz0wwOMwEUhvtva+89sjvIlYiIiPgpzNRR1dlMzeEwE0BFVAoAIbrWjIiInCYUZurIVF5nprmEGVdcOwDCi3SzSREROT0ozNRR1WEmXzM5zBTeyn+tmZjy7CBXIiIi4qcwU0dVZzOZZtIz07JNZwBa+7IpLa8IcjUiIiIKM3X2w2Gm5tEzE5vckQrjIMwq47s9OqNJRESCT2Gmjn44zNQ8emYsl4cDzlYAHNy1KcjViIiIKMzUXeAwU/PomQHIDfOf0VS4b1uQKxEREVGYqbOqw0zG0Tx6ZgDKo9sD4Du0I7iFiIiIoDBTd4HDTCFBLqTxuOI7ARCavyvIlYiIiCjM1J2v8jBTM+qZiW7bFYC40u8wxgS5GhERae4UZurK6wWaz6nZAPGp3QFIIZvs3JIgVyMiIs2dwkxdBXpmms9hJnfLDviwaGEVs2uPDjWJiEhwKczUVeWYGZrRYSZCQjniSgDg0J7NQS5GRESaO4WZuvJVnc3UfHpmAPLDUwEoztLp2SIiElwKM3VkNceeGcAX479Hk3VkZ5ArERGR5k5hpo4sUxVmms9F8wA8iWcAEFGwO8iViIhIc6cwU1e+yrOZmlmYiW3bDYAk717ySsqDXI2IiDRnCjN1ZFWezdTcembC2/YGoJu1mw079wa5GhERac4UZuqqcsyM1czCDHEdORjSBo9Vwbf/eS/Y1YiISDNmmzDzzDPP0L59e0JDQxk4cCCrV68OdkkAmIoyAFxuT5AraWSWRW7KEABa7fskyMWIiEhzZoswM3fuXCZMmMCUKVP48ssv6du3LxkZGezfvz+odZWUe8nPPQyAIzQqqLUEQ3ivSwHoXbya/blFQa5GRESaK1uEmb///e/cfPPN3HjjjfTo0YOZM2cSHh7OrFmzglrXrVP+ysXOtQCERMQEtZZgaN1nKMWEkmjlsPzzj4NdjoiINFOnfZgpKytj7dq1pKenB6Y5HA7S09NZuXJlje8pLS0lLy+v2qMh3BEyL/C8TevkBlnHac3lYUNofwAyV8z7icYiIiIN47QPMwcPHsTr9ZKYmFhtemJiIllZWTW+Z9q0aURHRwceKSkpDVJbTOdz2RpxFtlnXENM9yENso7TnfeMDAB+7vySZVsPBLkaERFpKMYY8krKKSn38t/vcrnmuZW0v/s92t/9Hmt3HQlqbU3yFJxJkyYxYcKEwOu8vLwGCTTtf/NUvS/TbgakX0PFf++nn2Mnf3zlaQZPmYrDYQW7LBGRJq2orAKPy4mzhr+3JeVenA6L0gofkR5XoL3Dsigq82IBG/bmsiUrnw7xEXRMiCTC7STzYCHXPv8FAG6Xg/8dcgavrd7N3twSwBBFEbFWPgnkkGDl0t3K4XxXDgnkkvfCXykc9zIRCe0acS/84LQPM/Hx8TidTrKzs6tNz87OJikpqcb3eDwePJ5mdnZRkITEJFM86A5cKx/lPp7n/Hs78fEDv8HtOu07/UREqjlSWEZMeAiW9dP/IcsvKSc0xEmIs/Z/64rKKigs9VJa4Q8bIU4H8ZGewPL+sXIXZ6bG8NWeXAa0i+XjzfvZn19CQqSHHslRPLdsJxv3VR820SUxkq3ZBQAkRnnIziutNt9FBWGUEUopYVYZYZQSTimhlc/XUUaYVUoYpURQwt2uAmIpINbKJ2ZZAcMoIMaTTywFuCzfCbdv6br1XHixwkyN3G43AwYMYMmSJQwfPhwAn8/HkiVLGDt2bHCLEwDC0iexbvk7nOnYzt9dT/PS5wO5+cKuwS5LRGzqSGEZIS5HoFehJh9tzOZIURlX9m/L9znFWBZUeA3t4yPYvr+Af36xiwMFpXSKj6BtXDgd4iMoKvOy80ABl/VNZvrCLcxds4dRg9oTEx7CE0u2YcwPy5/2K/+FQT/8JoulW6ofQu+W1ILNWfnH1BTitCj3GiwLjAGPy0F6j0QWb8ymrKJ6ELDwEUpZZdDwB4pQyviYMsKsMtbiDxuhVhnFlLKRMi62Svkf1w+BJMwqI/RwKWEhlYGkpJQwd1U48QcYt+Wtw7/EsYqMhwMmmgPE0LNLZ3wRiaw97CYmoS0Xpg2s13WdDMuYo//5Tk9z585l5MiRPPfcc5xzzjk8/vjjvPHGG2zevPmYsTQ1ycvLIzo6mtzcXKKimt8p1I0h//utOF+4gHBTxIyKy0i9ZjqX9mkd7LJE5EdyisrYc7iYFqEuIkNdGAOFpRWEhjhJig4NtPv2YCFJ0aF8d6SI1LgI3C4H//0ul9teWcs57eP4Wed4wt0uWkeH8uLnmQzsGEdsuJuJb3xFcbmX2PAQ7vtlD3YeKKRzYiQrth9i7po9AFzcIxFPiJOyCi+7Dxfjclj89/vcU9gag5sKXHhx4cWJFxc+nHhx4sNp+Sqn+wihIvBwWxW4j35NBSE1THNbR78ur3xv1Xoq11G5PtfRP60f5lf99FSGlKoA47Ea9zYwPmNRhIdi3JQY/88iPJTgwRMWyb4ii2I8RMa0YsMRJxed1Z02yW1wRbYkOi4RwuIgPA5Cwhq17tp+f9sizAA8/fTTTJ8+naysLPr168eTTz7JwIG1S4EKM43Dt2E+jn+NBODGsj9xz/g/cEarFkGuSsSe9uYUE+J0kNDCw6Z9eezLLebzbYfwGcPQ7q3Yl1PCgYJSSsu9bMnOx+sz/O68DhwoKOXxj7aRebCwDms3ODBYlT+deHFTjodyPFYFHsr8X/aV0/zhoPI55XisctxUVL6uwKr60rd8OAIBwOCqCg3VllG5/MrXgflU4LbKA8t0V9bSFJSaEH/IwE2xceN1hZEYF0NehYuoFlEU+NwcKHXQLjGe1d8XU2aFMrBrW5yeCPYVWmQVW/Ru35pi3Hy5r4yzzkgmPCKKnAonsdExxMbEgNON10BWXgltYho3kNRFkwszdaEw03iy544jcdNL5JgILi39PxY/8BvC3af90cwmxRhTq2P+cvKMMSzamE2bmDCMgdXfHuarPTm0j49g0TdZXNAlgb4pMbidDj7bdoALuibwuzlrTmod553RkuXbDwVeuyknhgJiLP9YhhirACf+QZxAIHBUhQSH5cNNBdEUEGMVBt4bbRUSSTGRFNPCKiKCEpz8+NCHwWnZ/yuhzPj7ZozDRbnx7xkcTgoqnJThosJy4bVclOPCZ4WQX+GkHBfJcVEkt4wiq9BHTItIvsku5ozWcYSFhrIrt5webeMp9jmxHC48bjfhoR4spwscLjIPl/Jdbhlt4lpQUA6pCS3AclHus6iwnLSOi6HcGUqJ8eB1eoiJjvb3crhCweEM9i47bSnMHEVhphFVlLLvsQtpXbiRr30dmN11Jo+NODfYVTWq3OJytmbnkxDpoaTCS7ekKKo+Zhv35bFs6wE6t2rB8u0H+c257ajw+XhpxS6uOastLoeD3m2jA+1LK3yEhvj/0P04pHh9hlU7D9G/XSwelwPLshj/+jrmr9/LI1f1IaNHElFhrhqDTVmFj3fWf0+Z10fH+EjOah+LBfgMOB1W4AyJf36xi6KyCpKiw4iPdHN2+zhCnA5e+Gwna749woPDe7EtOx+3y0FqXDgJLTxU+AwW4HI62J9fwuMfbeOWwR1pExtGudfHut05xEW4cbscdEqIrLZdVc9LK7xs3pfP8h0H2XmgkNjwEPbnl7LncBF/u7ovWXklvP/ffdw1rBufbj3I3xZtCfREuBwWFT7//kuODmXWjWfTNbHFMevIKynnzje/ZvfhIsLcTjZ8n8uoQe05kF9Kt9YtOFRQxuDOCfxr7R7e35BVOebBEE0hydYhwikhxPLi+FEgMJUxI4QKIigh0vIHCP/zEiIpIsIqIZJiwijFAkzl+wwWDnz+EGIVEEc+4Vb1AZ3B5DMWpYRQhotS3JThwuMJIzIykrxyB8bpJioyErcnlD15PvYVeOmeEk9eqcHhdOEzDqIjQzlQUI7lcBAeFkaJz0VMi0hCw8KxXB5CQ8OwXB6oejg9FBsnHk8YjhD/62rzfC48Hg9FXouIUDeWgkGTojBzFIWZRpazm/wnBtHC5PNqxRCSf/s8F3ZtFbRyfD7Dsq0HOLtDXLUBhZv25bF8+0EqKrvnq77EvT6Dzxg+336Q0XP+w7Rf9cbCYvuBAgpKK1j7rf96Cu1ahrM1O59vDx17KwcXFcSSjwNDCW4qcOLAEEoZkVYxERQTShkGi0zTmlwi8PLDH2EnXqIoxIuTUkIoJQT4cSgxhOClHGcN88BDWWC9x7Yxld3//i/nHCLx4qhWA0AUBYRSTgurCAtDkQmllBAMVmWPgI8SPKRY+8knjFDKyTPhlOCmHFflMh1YQChlganRViHFuHHg//Pjq/wiBwtjoIVVTCvrCGGU0sLy7yuAwsr1V+CkonJkRAuKaGXlkGDl0MrKIYYCDFBEKDtNa/aalszzDq62D0IpJcU6QIq1n2TrEKGUVVZb/c+hxyonicO0tg7R2jpMsnWQiCCEC6+xyCGSHBNJHhGEhobhdjk4UFCGMRYtW4RS5rMo8YLL5aJH25Y4w2Op8MQQEtmS0pAoXOExuMJjKHdF4HNHERoRDVU3yK0Mel6fweF04jUWToeDcp+FO8RJcQWEhobhs1w4T+LsHZG6Upg5isJM4yvetBjP61fjsAx3lt/MlaMnMbBjyzov99uDhWzOymdo91a4HFbgf9uvrtrNn+f9l/HpnRncOYHvjhQx6/NMvvqu+qDC/qkx3JDWngVf7+OjTdk48BFFIRU4K0OHi1BKaWMdJMU6QGvrED4clJgQynHhwktb6yBtrIMkWweJtIopMf6w4sNBjFVAinWAVlbOSW2Xz1gcJJoyXERQQqxVcMx8/4C9UI6YSGKsQmLJJ6TyTIUy46QMf41uygmlrNrhgqr5vspwEUIFkVZJtXV4jUUR/gGgVmXw+qlTMe3mOxNPGKW0tI49E+VkHDItyDURlUM7LTwhTtwuB/nFPwzq9OGggFDiYlsSExNHy5YtqXBFcKjcgzOsBeGRMezINaTGhbNyxyH6pkQTFuIkK7eELu1TcUS0xBcaiyMiDjxR4FCIkOZHYeYoCjPBse3NyXT+5glKjYtryiZz4c8v4Y6LulRrU1LuZXXmYWLD3bSLD+eLHYfYc6SYBxdsDLRJ757Id0eKKk+F9I8P8FVevLp/SjSZe/bQ0dpHO8t/LaIiQinCQxRFtLOy6eDIIolDlOOiGA8luImhgFRrPynW/mqDCCuMo96+wL3GwlgWrqMOQ/iwKDChFBBGiXETb+URZZ3+N+ksdkRSYcDtKz3hWRh5JoxISnCcYNxFhXFQYoVh4cVn/GHU+tGA03zCOGTFEhcbS64vjAMlFrHhbuJDytmfk0dxSQkuvLQIMbgjYvi2NJLWbdqT2KYdG3NCaBnqIzR/Dy32fk5U3tbj1BpOcURbQlq2Z3+pk8iwUFrHRvL1dzkcLixjUKeWhIS4cUQnQ1QbHDFt2eONxUS1ITUxvm47VERqRWHmKAozQeLz8dH9F5FurWGfieOy0od5ZNRQdh0q4sEFG/H96DfPwkc3aw9nOrbTydqLEy8V+HsUEsihu2M37a0sIq0SioyHQjz+gY4NEAaKrXD2Wq3IdScS7nYRapVTVlrC4aJyvjfx9O/dhw6dukJYDFSUgres8sISLSC2HUSn+E9ldDjAWw4+r78r3+kOdOkD/vd4y8jbt50j+7+jXVI8hERARDyExoDx+pdfXgwluXB4JzhDICIBIuLZmesjwmVIDHf4a/CWga/C/4hOAePzDy4sK/Qvx/j8Px0u/2mWDhe4I6GiGMqKoLxyXxqfv+boNuAKA+cPh+cO5ZdwqLCMLklR/vrLCiEk3L9Ol9s/zeet3Cde//Z7yzEhYWzIKqJzUgyhoaE0mrJCTNFhvl23hDatk3HHJENUsn/7ReS0pjBzFIWZICrJI+vRQSSV76HIeLi5fALx5HKuYxMDHZtoZeUQghdf5cDHUz3Vcr8jAW9sRxwOJ4dzcgg3xfhCIolK7owz4QxiWndiy94j/PfbLHonhlBoRdC5Sy9aJHfxf7H5KqCixB8aQsIgLLaed4SIiJwshZmjKMwElzmwBeuZc2rVtsCE8l1ET1J7DORQCWzdlwPeMrq3b0ty17Mhvos/aJQVVPYiWBDbHtzhDbkJIiISBLX9/tYFQKTBWQnVb22wzncGCT0voE2/i7HiO/sPvRj/aa+RUW3pVnlIIxw4/u1BExqwYhERsROFGWlUe6xkznxgbbDLEBGRJkTn+omIiIitKcyIiIiIrSnMSKOyaPLjzUVEpJEpzIiIiIitKcyIiIiIrSnMSKMyNdwQUUREpC4UZkRERMTWFGakUWkAsIiI1DeFGREREbE1hRkRERGxNYUZaVQaACwiIvVNYUZERERsTWFGGpUGAIuISH1TmBERERFbU5gRERERW1OYkUalAcAiIlLfFGZERETE1hRmRERExNYUZqRR6WwmERGpbwozIiIiYmsKM9KoNABYRETqm8KMiIiI2JrCjIiIiNiawow0Kg0AFhGR+qYwIyIiIramMCONSgOARUSkvinMiIiIiK0pzIiIiIitKcxIo9IAYBERqW8KM9Ko3C79yomISP3SN4s0qpYR7mCXICIiTYzCjDQqp0O/ciIiUr/0zSIiIiK2pjAjjUwDgEVEpH4pzIiIiIitKcyIiIiIrSnMSCPT7QxERKR+KcyIiIiIrSnMSCPTAGAREalfCjMiIiJiawozIiIiYmsKM9LINABYRETql8KMiIiI2JrCjDQyDQAWEZH6pTAjIiIittZgYebhhx9m0KBBhIeHExMTU2Ob3bt3c+mllxIeHk6rVq3405/+REVFRbU2S5cupX///ng8Hs444wzmzJnTUCWLiIiIDTVYmCkrK+Pqq6/mtttuq3G+1+vl0ksvpaysjBUrVvDSSy8xZ84cJk+eHGiTmZnJpZdeypAhQ1i/fj3jx4/npptu4sMPP2yosqXBaQCwiIjUL8sY06CDGObMmcP48ePJycmpNv2DDz7gl7/8JXv37iUxMRGAmTNnctddd3HgwAHcbjd33XUX7733Hhs2bAi877rrriMnJ4eFCxfWuoa8vDyio6PJzc0lKiqqXrZLTtLUaP/PuE4w7svg1iIiIrZQ2+/voI2ZWblyJb179w4EGYCMjAzy8vL45ptvAm3S09OrvS8jI4OVK1eecNmlpaXk5eVVe8jpQgOARUSkfgUtzGRlZVULMkDgdVZW1gnb5OXlUVxcfNxlT5s2jejo6MAjJSWlnqsXERGR08VJhZm7774by7JO+Ni8eXND1VprkyZNIjc3N/DYs2dPsEsSERGRBuI6mcYTJ05k1KhRJ2zTsWPHWi0rKSmJ1atXV5uWnZ0dmFf1s2ra0W2ioqIICws77rI9Hg8ej6dWdYiIiIi9nVSYSUhIICEhoV5WnJaWxsMPP8z+/ftp1aoVAIsXLyYqKooePXoE2rz//vvV3rd48WLS0tLqpQYJBp3NJCIi9avBxszs3r2b9evXs3v3brxeL+vXr2f9+vUUFBQAcPHFF9OjRw9++9vf8tVXX/Hhhx9y7733MmbMmECvyu9//3t27tzJnXfeyebNm3n22Wd54403uOOOOxqqbGlwGgAsIiL166R6Zk7G5MmTeemllwKvzzzzTAA++eQTLrzwQpxOJwsWLOC2224jLS2NiIgIRo4cyQMPPBB4T4cOHXjvvfe44447eOKJJ2jbti0vvPACGRkZDVW2iIiI2EyDX2fmdKDrzJwGAteZ6Qjj1gW3FhERsYXT/jozIiIiIvVBYUYamQYAi4hI/VKYEREREVtTmJFG1uSHaImISCNTmBERERFbU5gRERERW1OYkUamAcAiIlK/FGZERETE1hRmpJFpALCIiNQvhRkRERGxNYUZERERsTWFGWlkGgAsIiL1S2FGREREbE1hRhqZBgCLiEj9UpgRERERW1OYEREREVtTmJFGpgHAIiJSvxRmRERExNYUZqSRaQCwiIjUL4UZERERsTWFGREREbE1hRkRERGxNYUZaWQ6m0lEROqXwow0Mg0AFhGR+qUwIyIiIramMCMiIiK2pjAjIiIitqYwI41MA4BFRKR+KcxII9MAYBERqV8KMyIiImJrCjMiIiJiawozIiIiYmsKM9LINABYRETql8KMNDINABYRkfqlMCMiIiK2pjAjIiIitqYwIyIiIramMCONTAOARUSkfinMiIiIiK0pzEgj09lMIiJSvxRmRERExNYUZkRERMTWFGakkWkAsIiI1C+FGREREbE1hRlpZBoALCIi9UthRkRERGxNYUZERERsTWFGREREbE1hRhqZzmYSEZH6pTAjjUwDgEVEpH4pzIiIiIitKcyIiIiIrSnMiIiIiK0pzEgj0wBgERGpXwoz0sg0AFhEROpXg4WZb7/9ltGjR9OhQwfCwsLo1KkTU6ZMoaysrFq7r7/+msGDBxMaGkpKSgqPPPLIMct688036datG6GhofTu3Zv333+/ocoWERERm2mwMLN582Z8Ph/PPfcc33zzDY899hgzZ87kz3/+c6BNXl4eF198Me3atWPt2rVMnz6dqVOn8vzzzwfarFixguuvv57Ro0ezbt06hg8fzvDhw9mwYUNDlS4iIiI2YhljGq3ff/r06cyYMYOdO3cCMGPGDO655x6ysrJwu90A3H333cyfP5/NmzcDcO2111JYWMiCBQsCyzn33HPp168fM2fOrNV68/LyiI6OJjc3l6ioqHreKqmVqdH+n3EdYdy64NYiIiK2UNvv70YdM5Obm0tcXFzg9cqVKzn//PMDQQYgIyODLVu2cOTIkUCb9PT0asvJyMhg5cqVx11PaWkpeXl51R5yutAAYBERqV+NFma2b9/OU089xa233hqYlpWVRWJiYrV2Va+zsrJO2KZqfk2mTZtGdHR04JGSklJfmyF1pgHAIiJSv046zNx9991YlnXCR9Uhoirff/89w4YN4+qrr+bmm2+ut+KPZ9KkSeTm5gYee/bsafB1ioiISHC4TvYNEydOZNSoUSds07Fjx8DzvXv3MmTIEAYNGlRtYC9AUlIS2dnZ1aZVvU5KSjphm6r5NfF4PHg8np/cFhEREbG/kw4zCQkJJCQk1Krt999/z5AhQxgwYACzZ8/G4ajeEZSWlsY999xDeXk5ISEhACxevJiuXbsSGxsbaLNkyRLGjx8feN/ixYtJS0s72dJFRESkCWqwMTPff/89F154Iampqfztb3/jwIEDZGVlVRvr8utf/xq3283o0aP55ptvmDt3Lk888QQTJkwItPnDH/7AwoULefTRR9m8eTNTp05lzZo1jB07tqFKlwalAcAiIlK/TrpnprYWL17M9u3b2b59O23btq02r+ps8OjoaBYtWsSYMWMYMGAA8fHxTJ48mVtuuSXQdtCgQbz66qvce++9/PnPf6Zz587Mnz+fXr16NVTp0qA0AFhEROpXo15nJlh0nZnTgK4zIyIiJ+m0vM6MiIiISH1TmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5iRRqbbGYiISP1SmJFG1uQvOC0iIo1MYUZERERsTWFGREREbE1hRkRERGxNYUYamQYAi4hI/VKYkUamAcAiIlK/FGZERETE1hRmRERExNYUZkRERMTWFGakkWkAsIiI1C+FGWlkGgAsIiL1S2FGREREbE1hRkRERGxNYUZERERsTWFGGpkGAIuISP1SmJFGpgHAIiJSvxRmRERExNYUZkRERMTWFGZERETE1hRmRERExNYUZkRERMTWFGZERETE1hRmRERExNYUZkRERMTWFGZERETE1hRmRERExNYUZkRERMTWFGZERETE1hRmRERExNYUZkRERMTWFGZERETE1hRmRERExNYUZkRERMTWFGZERETE1hRmRERExNYUZqSRWcEuQEREmhiFGWlkJtgFiIhIE6MwIyIiIramMCMiIiK2pjAjIiIitqYwIyIiIramMCMiIiK2pjAjIiIitqYwIyIiIramMCMiIiK2pjAjIiIittagYeZ//ud/SE1NJTQ0lNatW/Pb3/6WvXv3Vmvz9ddfM3jwYEJDQ0lJSeGRRx45Zjlvvvkm3bp1IzQ0lN69e/P+++83ZNkiIiJiIw0aZoYMGcIbb7zBli1beOutt9ixYwdXXXVVYH5eXh4XX3wx7dq1Y+3atUyfPp2pU6fy/PPPB9qsWLGC66+/ntGjR7Nu3TqGDx/O8OHD2bBhQ0OWLiIiIjZhGWMa7WY57777LsOHD6e0tJSQkBBmzJjBPffcQ1ZWFm63G4C7776b+fPns3nzZgCuvfZaCgsLWbBgQWA55557Lv369WPmzJm1Wm9eXh7R0dHk5uYSFRVV/xsmP21qtP9nXEcYty64tYiIiC3U9vu70cbMHD58mFdeeYVBgwYREhICwMqVKzn//PMDQQYgIyODLVu2cOTIkUCb9PT0asvKyMhg5cqVx11XaWkpeXl51R4iIiLSNDV4mLnrrruIiIigZcuW7N69m3feeScwLysri8TExGrtq15nZWWdsE3V/JpMmzaN6OjowCMlJaW+NkdEREROMycdZu6++24syzrho+oQEcCf/vQn1q1bx6JFi3A6ndxwww009JGtSZMmkZubG3js2bOnQdcnIiIiweM62TdMnDiRUaNGnbBNx44dA8/j4+OJj4+nS5cudO/enZSUFL744gvS0tJISkoiOzu72nurXiclJQV+1tSman5NPB4PHo/nZDZLREREbOqkw0xCQgIJCQmntDKfzwf4x7QApKWlcc8991BeXh4YR7N48WK6du1KbGxsoM2SJUsYP358YDmLFy8mLS3tlGoQERGRpqXBxsysWrWKp59+mvXr17Nr1y4+/vhjrr/+ejp16hQIIr/+9a9xu92MHj2ab775hrlz5/LEE08wYcKEwHL+8Ic/sHDhQh599FE2b97M1KlTWbNmDWPHjm2o0kVERMRGGizMhIeH8/bbbzN06FC6du3K6NGj6dOnD8uWLQscAoqOjmbRokVkZmYyYMAAJk6cyOTJk7nlllsCyxk0aBCvvvoqzz//PH379uVf//oX8+fPp1evXg1VuoiIiNhIo15nJlh0nZnTgK4zIyIiJ+m0u86MiIiISENQmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtTmBERERFbU5gRERERW1OYEREREVtrlDBTWlpKv379sCyL9evXV5v39ddfM3jwYEJDQ0lJSeGRRx455v1vvvkm3bp1IzQ0lN69e/P+++83RtkiIiJiA40SZu68806Sk5OPmZ6Xl8fFF19Mu3btWLt2LdOnT2fq1Kk8//zzgTYrVqzg+uuvZ/To0axbt47hw4czfPhwNmzY0Bili4iIyGmuwcPMBx98wKJFi/jb3/52zLxXXnmFsrIyZs2aRc+ePbnuuusYN24cf//73wNtnnjiCYYNG8af/vQnunfvzoMPPkj//v15+umnG7p0ERERsYEGDTPZ2dncfPPNvPzyy4SHhx8zf+XKlZx//vm43e7AtIyMDLZs2cKRI0cCbdLT06u9LyMjg5UrVx53vaWlpeTl5VV7iIiISNPUYGHGGMOoUaP4/e9/z1lnnVVjm6ysLBITE6tNq3qdlZV1wjZV82sybdo0oqOjA4+UlJS6bIqIiIicxk46zNx9991YlnXCx+bNm3nqqafIz89n0qRJDVH3CU2aNInc3NzAY8+ePY1eg4iIiDQO18m+YeLEiYwaNeqEbTp27MjHH3/MypUr8Xg81eadddZZjBgxgpdeeomkpCSys7Orza96nZSUFPhZU5uq+TXxeDzHrFdERESappMOMwkJCSQkJPxkuyeffJKHHnoo8Hrv3r1kZGQwd+5cBg4cCEBaWhr33HMP5eXlhISEALB48WK6du1KbGxsoM2SJUsYP358YFmLFy8mLS3tZEsXERGRJuikw0xtpaamVnsdGRkJQKdOnWjbti0Av/71r7n//vsZPXo0d911Fxs2bOCJJ57gscceC7zvD3/4AxdccAGPPvool156Ka+//jpr1qypdvq2iIiINF9BvQJwdHQ0ixYtIjMzkwEDBjBx4kQmT57MLbfcEmgzaNAgXn31VZ5//nn69u3Lv/71L+bPn0+vXr2CWLmIiIicLixjjAl2EQ0tLy+P6OhocnNziYqKCnY5zdPUaP/PuI4wbl1waxEREVuo7fe37s0kjSO8pf9np6HBrUNERJqcBhszI1LNrZ/B1g+g7/XBrkRERJoYhRlpHNFt4Oybgl2FiIg0QTrMJCIiIramMCMiIiK2pjAjIiIitqYwIyIiIramMCMiIiK2pjAjIiIitqYwIyIiIramMCMiIiK2pjAjIiIitqYwIyIiIramMCMiIiK2pjAjIiIitqYwIyIiIrbWLO6abYwBIC8vL8iViIiISG1VfW9XfY8fT7MIM/n5+QCkpKQEuRIRERE5Wfn5+URHRx93vmV+Ku40AT6fj71799KiRQssy6q35ebl5ZGSksKePXuIioqqt+VK7enfILi0/4NL+z+4tP8bnjGG/Px8kpOTcTiOPzKmWfTMOBwO2rZt22DLj4qK0i9ykOnfILi0/4NL+z+4tP8b1ol6ZKpoALCIiIjYmsKMiIiI2JrCTB14PB6mTJmCx+MJdinNlv4Ngkv7P7i0/4NL+//00SwGAIuIiEjTpZ4ZERERsTWFGREREbE1hRkRERGxNYUZERERsTWFmTp45plnaN++PaGhoQwcOJDVq1cHu6RmYerUqViWVe3RrVu3YJfVpH366adcdtllJCcnY1kW8+fPrzbfGMPkyZNp3bo1YWFhpKens23btuAU2wT91P4fNWrUMZ+JYcOGBafYJmjatGmcffbZtGjRglatWjF8+HC2bNlSrU1JSQljxoyhZcuWREZGcuWVV5KdnR2kipsfhZlTNHfuXCZMmMCUKVP48ssv6du3LxkZGezfvz/YpTULPXv2ZN++fYHH559/HuySmrTCwkL69u3LM888U+P8Rx55hCeffJKZM2eyatUqIiIiyMjIoKSkpJErbZp+av8DDBs2rNpn4rXXXmvECpu2ZcuWMWbMGL744gsWL15MeXk5F198MYWFhYE2d9xxB//+97958803WbZsGXv37uVXv/pVEKtuZoycknPOOceMGTMm8Nrr9Zrk5GQzbdq0IFbVPEyZMsX07ds32GU0W4CZN29e4LXP5zNJSUlm+vTpgWk5OTnG4/GY1157LQgVNm0/3v/GGDNy5Ehz+eWXB6We5mj//v0GMMuWLTPG+H/fQ0JCzJtvvhlos2nTJgOYlStXBqvMZkU9M6egrKyMtWvXkp6eHpjmcDhIT09n5cqVQays+di2bRvJycl07NiRESNGsHv37mCX1GxlZmaSlZVV7fMQHR3NwIED9XloREuXLqVVq1Z07dqV2267jUOHDgW7pCYrNzcXgLi4OADWrl1LeXl5tc9At27dSE1N1WegkSjMnIKDBw/i9XpJTEysNj0xMZGsrKwgVdV8DBw4kDlz5rBw4UJmzJhBZmYmgwcPJj8/P9ilNUtVv/P6PATPsGHD+Mc//sGSJUv461//yrJly7jkkkvwer3BLq3J8fl8jB8/nvPOO49evXoB/s+A2+0mJiamWlt9BhpPs7hrtjQtl1xySeB5nz59GDhwIO3ateONN95g9OjRQaxMJDiuu+66wPPevXvTp08fOnXqxNKlSxk6dGgQK2t6xowZw4YNGzRO7zSjnplTEB8fj9PpPGakenZ2NklJSUGqqvmKiYmhS5cubN++PdilNEtVv/P6PJw+OnbsSHx8vD4T9Wzs2LEsWLCATz75hLZt2wamJyUlUVZWRk5OTrX2+gw0HoWZU+B2uxkwYABLliwJTPP5fCxZsoS0tLQgVtY8FRQUsGPHDlq3bh3sUpqlDh06kJSUVO3zkJeXx6pVq/R5CJLvvvuOQ4cO6TNRT4wxjB07lnnz5vHxxx/ToUOHavMHDBhASEhItc/Ali1b2L17tz4DjUSHmU7RhAkTGDlyJGeddRbnnHMOjz/+OIWFhdx4443BLq3J++Mf/8hll11Gu3bt2Lt3L1OmTMHpdHL99dcHu7Qmq6CgoNr/8jMzM1m/fj1xcXGkpqYyfvx4HnroITp37kyHDh247777SE5OZvjw4cErugk50f6Pi4vj/vvv58orryQpKYkdO3Zw5513csYZZ5CRkRHEqpuOMWPG8Oqrr/LOO+/QokWLwDiY6OhowsLCiI6OZvTo0UyYMIG4uDiioqL43//9X9LS0jj33HODXH0zEezTqezsqaeeMqmpqcbtdptzzjnHfPHFF8EuqVm49tprTevWrY3b7TZt2rQx1157rdm+fXuwy2rSPvnkEwMc8xg5cqQxxn969n333WcSExONx+MxQ4cONVu2bAlu0U3IifZ/UVGRufjii01CQoIJCQkx7dq1MzfffLPJysoKdtlNRk37HjCzZ88OtCkuLja33367iY2NNeHh4eaKK64w+/btC17RzYxljDGNH6FERERE6ofGzIiIiIitKcyIiIiIrSnMiIiIiK0pzIiIiIitKcyIiIiIrSnMiIiIiK0pzIiIiIitKcyIiIiIrSnMiIiIiK0pzIiIiIitKcyIiIiIrSnMiIiIiK39f0yZzMAu2GwIAAAAAElFTkSuQmCC",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -578,7 +647,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -588,7 +657,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -608,6 +677,8 @@
     "plt.xlabel(\"Time (s)\")\n",
     "plt.ylabel(\"Acceleration ax (m/s^2)\")\n",
     "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.title(\"Acceleration comparison - ax\")\n",
     "plt.show()\n",
     "\n",
     "plt.plot(time1, ay, label=\"Noisy Accelerometer\")\n",
@@ -615,6 +686,8 @@
     "plt.xlabel(\"Time (s)\")\n",
     "plt.ylabel(\"Acceleration ay (m/s^2)\")\n",
     "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.title(\"Acceleration comparison - ay\")\n",
     "plt.show()\n",
     "\n",
     "plt.plot(time1, az, label=\"Noisy Accelerometer\")\n",
@@ -622,27 +695,26 @@
     "plt.xlabel(\"Time (s)\")\n",
     "plt.ylabel(\"Acceleration az (m/s^2)\")\n",
     "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.title(\"Acceleration comparison - az\")\n",
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Total Acceleration"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/plain": [
-       "(0.0, 4.0)"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -652,27 +724,35 @@
     }
    ],
    "source": [
-    "# now plot the total acceleration\n",
-    "\n",
     "abs_a = (np.array(ax) ** 2 + np.array(ay) ** 2 + np.array(az) ** 2) ** 0.5\n",
     "abs_b = (np.array(bx) ** 2 + np.array(by) ** 2 + np.array(bz) ** 2) ** 0.5\n",
-    "plt.plot(time1, abs_a, label=\"noisy\")\n",
+    "\n",
     "plt.plot(time2, abs_b, label=\"clean\")\n",
+    "plt.plot(time1, abs_a, label=\"noisy\")\n",
     "plt.xlabel(\"Time (s)\")\n",
     "plt.ylabel(\"Acceleration (m/s^2)\")\n",
     "plt.legend()\n",
-    "plt.xlim(0, 10)\n",
+    "plt.xlim(0, 20)\n",
+    "plt.grid()\n",
+    "plt.title(\"Acceleration\")\n",
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Gyroscope"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -682,7 +762,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -692,7 +772,17 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -735,35 +825,20 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 27,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "source": [
-    "t, p = zip(*barometer_clean.measured_data)\n",
-    "plt.plot(t, p)\n",
-    "plt.show()"
+    "### Barometer"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -773,15 +848,20 @@
     }
    ],
    "source": [
-    "test_flight.pressure()"
+    "time_barometer, pressure_barometer = zip(*barometer_clean.measured_data)\n",
+    "\n",
+    "rocket_pressure = test_flight.pressure.y_array\n",
+    "rocket_time = test_flight.pressure.x_array\n",
+    "\n",
+    "plt.plot(rocket_time, rocket_pressure, label=\"Rocket\")\n",
+    "plt.plot(time_barometer, pressure_barometer, label=\"Barometer\")\n",
+    "plt.xlabel(\"Time (s)\")\n",
+    "plt.ylabel(\"Pressure (Pa)\")\n",
+    "plt.title(\"Pressure comparison\")\n",
+    "plt.grid()\n",
+    "plt.legend()\n",
+    "plt.show()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/docs/reference/classes/sensors/abstract/index.rst b/docs/reference/classes/sensors/abstract/index.rst
new file mode 100644
index 000000000..e016c93de
--- /dev/null
+++ b/docs/reference/classes/sensors/abstract/index.rst
@@ -0,0 +1,11 @@
+Sensors Abstract Classes
+========================
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Contents:
+
+   Sensor Class <sensor>
+   Inertial Sensor Class <inertial_sensor>
+   Scalar Sensor Class <scalar_sensor>
+
diff --git a/docs/reference/classes/sensors/abstract/inertial_sensor.rst b/docs/reference/classes/sensors/abstract/inertial_sensor.rst
new file mode 100644
index 000000000..2e85205d6
--- /dev/null
+++ b/docs/reference/classes/sensors/abstract/inertial_sensor.rst
@@ -0,0 +1,5 @@
+Inertial Class
+--------------
+
+.. autoclass:: rocketpy.sensors.InertialSensor
+    :members:
diff --git a/docs/reference/classes/sensors/abstract/scalar_sensor.rst b/docs/reference/classes/sensors/abstract/scalar_sensor.rst
new file mode 100644
index 000000000..42e8aae95
--- /dev/null
+++ b/docs/reference/classes/sensors/abstract/scalar_sensor.rst
@@ -0,0 +1,5 @@
+Scalar Sensor Class
+-------------------
+
+.. autoclass:: rocketpy.sensors.ScalarSensor
+    :members:
diff --git a/docs/reference/classes/sensors/abstract/sensor.rst b/docs/reference/classes/sensors/abstract/sensor.rst
new file mode 100644
index 000000000..188744f98
--- /dev/null
+++ b/docs/reference/classes/sensors/abstract/sensor.rst
@@ -0,0 +1,5 @@
+Sensor Class
+------------
+
+.. autoclass:: rocketpy.sensors.Barometer
+    :members:
diff --git a/docs/reference/classes/sensors/accelerometer.rst b/docs/reference/classes/sensors/accelerometer.rst
new file mode 100644
index 000000000..0eac1e4c0
--- /dev/null
+++ b/docs/reference/classes/sensors/accelerometer.rst
@@ -0,0 +1,5 @@
+Accelerometer Class
+---------------
+
+.. autoclass:: rocketpy.sensors.Accelerometer
+    :members:
diff --git a/docs/reference/classes/sensors/barometer.rst b/docs/reference/classes/sensors/barometer.rst
new file mode 100644
index 000000000..4fba284ca
--- /dev/null
+++ b/docs/reference/classes/sensors/barometer.rst
@@ -0,0 +1,5 @@
+Barometer Class
+---------------
+
+.. autoclass:: rocketpy.sensors.Barometer
+    :members:
diff --git a/docs/reference/classes/sensors/gnss_receiver.rst b/docs/reference/classes/sensors/gnss_receiver.rst
new file mode 100644
index 000000000..a5efa2332
--- /dev/null
+++ b/docs/reference/classes/sensors/gnss_receiver.rst
@@ -0,0 +1,5 @@
+GNSS Receiver Class
+-------------------
+
+.. autoclass:: rocketpy.sensors.GnssReceiver
+    :members:
diff --git a/docs/reference/classes/sensors/gyroscope.rst b/docs/reference/classes/sensors/gyroscope.rst
new file mode 100644
index 000000000..948f93e4c
--- /dev/null
+++ b/docs/reference/classes/sensors/gyroscope.rst
@@ -0,0 +1,5 @@
+Gyroscope Class
+---------------
+
+.. autoclass:: rocketpy.sensors.Gyroscope
+    :members:
diff --git a/docs/reference/classes/sensors/index.rst b/docs/reference/classes/sensors/index.rst
new file mode 100644
index 000000000..98c79aafd
--- /dev/null
+++ b/docs/reference/classes/sensors/index.rst
@@ -0,0 +1,12 @@
+Sensor Classes
+==============
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Contents:
+
+   Sensors Abstract Classes <abstract/index>
+   Accelerometer Class <accelerometer>
+   Barometer Class <barometer>
+   Gyroscope Class <gyroscope>
+   GNSS Receiver Class <gnss>
diff --git a/docs/user/index.rst b/docs/user/index.rst
index 5698aafcc..aa88cba9b 100644
--- a/docs/user/index.rst
+++ b/docs/user/index.rst
@@ -24,6 +24,7 @@ RocketPy's User Guide
    Compare Flights Class<compare_flights.rst>
    Deployable Payload <deployable.rst>
    Air Brakes Example <airbrakes.rst>
+   ../notebooks/sensors_testing.ipynb
    ../matlab/matlab.rst
 
 .. toctree::

From f4cdc2bce30565c0f4a4e5b9b85627e66635a91b Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Sat, 7 Sep 2024 23:06:51 -0300
Subject: [PATCH 116/120] DOC: rename sensors notebook

---
 docs/notebooks/{sensors_testing.ipynb => sensors.ipynb} | 0
 docs/user/index.rst                                     | 2 +-
 2 files changed, 1 insertion(+), 1 deletion(-)
 rename docs/notebooks/{sensors_testing.ipynb => sensors.ipynb} (100%)

diff --git a/docs/notebooks/sensors_testing.ipynb b/docs/notebooks/sensors.ipynb
similarity index 100%
rename from docs/notebooks/sensors_testing.ipynb
rename to docs/notebooks/sensors.ipynb
diff --git a/docs/user/index.rst b/docs/user/index.rst
index aa88cba9b..287e82708 100644
--- a/docs/user/index.rst
+++ b/docs/user/index.rst
@@ -24,7 +24,7 @@ RocketPy's User Guide
    Compare Flights Class<compare_flights.rst>
    Deployable Payload <deployable.rst>
    Air Brakes Example <airbrakes.rst>
-   ../notebooks/sensors_testing.ipynb
+   ../notebooks/sensors.ipynb
    ../matlab/matlab.rst
 
 .. toctree::

From a0fb6ad1d95584ea937eee987dd5cefe6d2e7a22 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Wed, 11 Sep 2024 21:32:16 -0300
Subject: [PATCH 117/120] MNT: Add warning for experimental development in
 Sensor classes

---
 rocketpy/sensors/sensor.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index 0a1e20bab..7ae3ad3dc 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -1,4 +1,5 @@
 import json
+import warnings
 from abc import ABC, abstractmethod
 
 import numpy as np
@@ -116,6 +117,13 @@ def __init__(
         --------
         TODO link to documentation on noise model
         """
+        warnings.warn(
+            "The Sensor class (and all its subclasses) is still under "
+            "experimental development. Some features may be changed in future "
+            "versions, although we will try to keep the changes to a minimum.",
+            UserWarning,
+        )
+
         self.sampling_rate = sampling_rate
         self.resolution = resolution
         self.operating_temperature = operating_temperature

From 2c142c4883ac9535137b8663b7bc67121c7cbe04 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Thu, 12 Sep 2024 01:40:36 -0300
Subject: [PATCH 118/120] MNT: rename euler-quaternion conversions

---
 rocketpy/mathutils/vector_matrix.py |  4 +-
 rocketpy/simulation/flight.py       |  4 +-
 rocketpy/tools.py                   | 76 +++++++++++++++--------------
 tests/unit/test_sensor.py           |  6 +--
 tests/unit/test_tools.py            |  4 +-
 5 files changed, 48 insertions(+), 46 deletions(-)

diff --git a/rocketpy/mathutils/vector_matrix.py b/rocketpy/mathutils/vector_matrix.py
index f82760b1d..f0ccc36ee 100644
--- a/rocketpy/mathutils/vector_matrix.py
+++ b/rocketpy/mathutils/vector_matrix.py
@@ -2,7 +2,7 @@
 from functools import cached_property
 from itertools import product
 
-from rocketpy.tools import euler_to_quaternions, normalize_quaternions
+from rocketpy.tools import euler321_to_quaternions, normalize_quaternions
 
 
 class Vector:
@@ -1081,7 +1081,7 @@ def transformation_euler_angles(roll, pitch, yaw):
         Matrix
             The transformation matrix from frame B to frame A.
         """
-        return Matrix.transformation(euler_to_quaternions(roll, pitch, yaw))
+        return Matrix.transformation(euler321_to_quaternions(roll, pitch, yaw))
 
 
 if __name__ == "__main__":
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index a43d51d30..f5733dfab 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -15,7 +15,7 @@
 from ..prints.flight_prints import _FlightPrints
 from ..tools import (
     calculate_cubic_hermite_coefficients,
-    euler_angles_to_euler_parameters,
+    euler313_to_quaternions,
     find_closest,
     find_root_linear_interpolation,
     find_roots_cubic_function,
@@ -1126,7 +1126,7 @@ def __init_flight_state(self):
                 pass
 
             # 3-1-3 Euler Angles to Euler Parameters
-            e0_init, e1_init, e2_init, e3_init = euler_angles_to_euler_parameters(
+            e0_init, e1_init, e2_init, e3_init = euler313_to_quaternions(
                 self.phi_init, self.theta_init, self.psi_init
             )
             # Store initial conditions
diff --git a/rocketpy/tools.py b/rocketpy/tools.py
index 11d38f701..27b3dcda8 100644
--- a/rocketpy/tools.py
+++ b/rocketpy/tools.py
@@ -1087,27 +1087,47 @@ def quaternions_to_nutation(e1, e2):
     return (180 / np.pi) * 2 * np.arcsin(-((e1**2 + e2**2) ** 0.5))
 
 
-def euler_to_quaternions(roll, pitch, yaw):
+def normalize_quaternions(quaternions):
+    """Normalizes the quaternions (Euler parameters) to have unit magnitude.
+
+    Parameters
+    ----------
+    quaternions : tuple
+        Tuple containing the Euler parameters e0, e1, e2, e3
+
+    Returns
+    -------
+    tuple
+        Tuple containing the Euler parameters e0, e1, e2, e3
+    """
+    q_w, q_x, q_y, q_z = quaternions
+    q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
+    if q_norm == 0:
+        return 1, 0, 0, 0
+    return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
+
+
+def euler321_to_quaternions(psi, theta, phi):
     """Calculates the quaternions (Euler parameters) from the Euler angles in
     yaw, pitch, and roll sequence (3-2-1).
 
     Parameters
     ----------
-    roll : float
-        Euler angle due to roll (psi) in degrees
-    pitch : float
-        Euler angle due to pitch (theta) in degrees
-    yaw : float
-        Euler angle due to yaw (phi) in degrees
+    psi : float
+        Euler angle due to roll in degrees, also known as the spin angle.
+    theta : float
+        Euler angle due to pitch in degrees, also known as the nutation angle.
+    phi : float
+        Euler angle due to yaw in degrees, also known as the precession angle.
 
     Returns
     -------
-    tuple
+    tuple[float, float, float, float]
         Tuple containing the Euler parameters e0, e1, e2, e3
     """
-    phi = math.radians(yaw)
-    theta = math.radians(pitch)
-    psi = math.radians(roll)
+    phi = math.radians(phi)
+    theta = math.radians(theta)
+    psi = math.radians(psi)
     cr = math.cos(phi / 2)
     sr = math.sin(phi / 2)
     cp = math.cos(theta / 2)
@@ -1121,38 +1141,20 @@ def euler_to_quaternions(roll, pitch, yaw):
     return e0, e1, e2, e3
 
 
-def normalize_quaternions(quaternions):
-    """Normalizes the quaternions (Euler parameters) to have unit magnitude.
-
-    Parameters
-    ----------
-    quaternions : tuple
-        Tuple containing the Euler parameters e0, e1, e2, e3
-
-    Returns
-    -------
-    tuple
-        Tuple containing the Euler parameters e0, e1, e2, e3
-    """
-    q_w, q_x, q_y, q_z = quaternions
-    q_norm = (q_w**2 + q_x**2 + q_y**2 + q_z**2) ** 0.5
-    if q_norm == 0:
-        return 1, 0, 0, 0
-    return q_w / q_norm, q_x / q_norm, q_y / q_norm, q_z / q_norm
-
-
-def euler_angles_to_euler_parameters(phi, theta, psi):
-    """Convert 3-1-3 Euler Angles to Euler Parameters (quaternions).
+def euler313_to_quaternions(phi, theta, psi):
+    """Convert 3-1-3 Euler angles to Euler parameters (quaternions).
 
     Parameters
     ----------
     phi : float
-        Rotation angle around the z-axis (in radians). Represents the precession angle.
+        Rotation angle around the z-axis (in radians). Represents the precession
+        angle or the yaw angle.
     theta : float
-        Rotation angle around the x-axis (in radians). Represents the nutation angle.
+        Rotation angle around the x-axis (in radians). Represents the nutation
+        angle or the pitch angle.
     psi : float
-        Rotation angle around the z-axis (in radians). Represents the spin angle.
-
+        Rotation angle around the z-axis (in radians). Represents the spin angle
+        or the roll angle.
 
     Returns
     -------
diff --git a/tests/unit/test_sensor.py b/tests/unit/test_sensor.py
index 73f8e7dcc..33c62bb87 100644
--- a/tests/unit/test_sensor.py
+++ b/tests/unit/test_sensor.py
@@ -6,7 +6,7 @@
 from pytest import approx
 
 from rocketpy.mathutils.vector_matrix import Matrix, Vector
-from rocketpy.tools import euler_to_quaternions
+from rocketpy.tools import euler321_to_quaternions
 
 # calisto standard simulation no wind solution index 200
 TIME = 3.338513236767685
@@ -287,7 +287,7 @@ def test_noisy_rotated_accelerometer(noisy_rotated_accelerometer, example_plain_
             [0.005, 0.005, 1],
         ]
     )
-    sensor_rotation = Matrix.transformation(euler_to_quaternions(60, 60, 60))
+    sensor_rotation = Matrix.transformation(euler321_to_quaternions(60, 60, 60))
     total_rotation = sensor_rotation @ cross_axis_sensitivity
     rocket_rotation = Matrix.transformation(U[6:10])
     # expected measurement without noise
@@ -328,7 +328,7 @@ def test_noisy_rotated_gyroscope(noisy_rotated_gyroscope, example_plain_env):
             [0.005, 0.005, 1],
         ]
     )
-    sensor_rotation = Matrix.transformation(euler_to_quaternions(-60, -60, -60))
+    sensor_rotation = Matrix.transformation(euler321_to_quaternions(-60, -60, -60))
     total_rotation = sensor_rotation @ cross_axis_sensitivity
     rocket_rotation = Matrix.transformation(U[6:10])
     # expected measurement without noise
diff --git a/tests/unit/test_tools.py b/tests/unit/test_tools.py
index 4b2f8b14f..d399d5fc5 100644
--- a/tests/unit/test_tools.py
+++ b/tests/unit/test_tools.py
@@ -3,7 +3,7 @@
 
 from rocketpy.tools import (
     calculate_cubic_hermite_coefficients,
-    euler_to_quaternions,
+    euler321_to_quaternions,
     find_roots_cubic_function,
 )
 
@@ -13,7 +13,7 @@
     [((0, 0, 0), (1, 0, 0, 0)), ((90, 90, 90), (0.7071068, 0, 0.7071068, 0))],
 )
 def test_euler_to_quaternions(angles, expected_quaternions):
-    q0, q1, q2, q3 = euler_to_quaternions(*angles)
+    q0, q1, q2, q3 = euler321_to_quaternions(*angles)
     assert round(q0, 7) == expected_quaternions[0]
     assert round(q1, 7) == expected_quaternions[1]
     assert round(q2, 7) == expected_quaternions[2]

From bb8af25617c31ab54d9aa82612245c5d4978ea7c Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Thu, 12 Sep 2024 02:06:04 -0300
Subject: [PATCH 119/120] MNT: minor adjustments before merging sensors

---
 rocketpy/environment/tools.py |  2 +-
 rocketpy/motors/tank.py       |  2 +-
 rocketpy/rocket/parachute.py  |  4 ++--
 rocketpy/rocket/rocket.py     | 25 ++++++++++++-------------
 rocketpy/sensors/barometer.py |  2 +-
 rocketpy/sensors/gyroscope.py |  3 +--
 rocketpy/sensors/sensor.py    |  2 --
 rocketpy/simulation/flight.py |  4 ++--
 8 files changed, 20 insertions(+), 24 deletions(-)

diff --git a/rocketpy/environment/tools.py b/rocketpy/environment/tools.py
index dfa2698a1..4fc3ca7c7 100644
--- a/rocketpy/environment/tools.py
+++ b/rocketpy/environment/tools.py
@@ -532,7 +532,7 @@ def utm_to_geodesic(  # pylint: disable=too-many-locals,too-many-statements
     x, y, utm_zone, hemis, semi_major_axis=6378137.0, flattening=1 / 298.257223563
 ):
     # NOTE: already documented in the Environment class.
-    # TODO: deprecated the static method from the environment class, use only this one.
+    # TODO: deprecate the static method from the environment class, use only this one.
 
     if hemis == "N":
         y = y + 10000000
diff --git a/rocketpy/motors/tank.py b/rocketpy/motors/tank.py
index 6fabaa341..a3b21f434 100644
--- a/rocketpy/motors/tank.py
+++ b/rocketpy/motors/tank.py
@@ -1158,7 +1158,7 @@ def gas_volume(self):
         Function
             Volume of the gas as a function of time.
         """
-        # TODO: there's a bug on the gas_center_of_mass is I don't discretize here
+        # TODO: there's a bug on the gas_center_of_mass if I don't discretize here
         func = Function(self.geometry.total_volume).set_discrete_based_on_model(
             self.liquid_volume
         )
diff --git a/rocketpy/rocket/parachute.py b/rocketpy/rocket/parachute.py
index cd9f2c23e..c465c4367 100644
--- a/rocketpy/rocket/parachute.py
+++ b/rocketpy/rocket/parachute.py
@@ -34,8 +34,8 @@ class Parachute:
            ``sensor.measurement`` attribute. The sensors are listed in the same
            order as they are added to the rocket.
 
-        The function should return True if the parachute ejection system should
-        be triggered and False otherwise.
+        The function should return ``True`` if the parachute ejection system
+        should be triggered and False otherwise.
 
         - A float value, representing an absolute height in meters. In this
         case, the parachute will be ejected when the rocket reaches this height
diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py
index b07152576..a5964808f 100644
--- a/rocketpy/rocket/rocket.py
+++ b/rocketpy/rocket/rocket.py
@@ -1347,30 +1347,29 @@ def add_parachute(
         self.parachutes.append(parachute)
         return self.parachutes[-1]
 
-    def add_sensor(self, sensor, position, x_offset=0, y_offset=0):
+    def add_sensor(self, sensor, position):
         """Adds a sensor to the rocket.
 
         Parameters
         ----------
         sensor : Sensor
             Sensor to be added to the rocket.
-        position : int, float, tuple
-            Position, in meters, of the sensor's coordinate system origin
-            relative to the user defined rocket coordinate system.
-        x_offset : int, float, optional
-            Distance in meters by which the sensor is to be translated in the
-            rocket's x direction relative to geometrical center line.
-            Default is 0.
-        y_offset : int, float, optional
-            Distance in meters by which the sensor is to be translated in the
-            rocket's y direction relative to geometrical center line.
-            Default is 0.
+        position : int, float, tuple, list, Vector
+            Position of the sensor. If a Vector, tuple or list is passed, it
+            must be in the format (x, y, z) where x, y, and z are defined in the
+            rocket's user defined coordinate system. If a single value is
+            passed, it is assumed to be along the z-axis (centerline) of the
+            rocket's user defined coordinate system and angular_position and
+            radius must be given.
 
         Returns
         -------
         None
         """
-        self.sensors.add(sensor, Vector([x_offset, y_offset, position]))
+        if isinstance(position, (float, int)):
+            position = (0, 0, position)
+        position = Vector(position)
+        self.sensors.add(sensor, position)
         try:
             sensor._attached_rockets[self] += 1
         except KeyError:
diff --git a/rocketpy/sensors/barometer.py b/rocketpy/sensors/barometer.py
index 4a324faf5..9e6fceb16 100644
--- a/rocketpy/sensors/barometer.py
+++ b/rocketpy/sensors/barometer.py
@@ -71,7 +71,7 @@ def __init__(
         sampling_rate : float
             Sample rate of the sensor in Hz.
         measurement_range : float, tuple, optional
-            The measurement range of the sensor in the Pa. If a float, the same
+            The measurement range of the sensor in Pa. If a float, the same
             range is applied both for positive and negative values. If a tuple,
             the first value is the positive range and the second value is the
             negative range. Default is np.inf.
diff --git a/rocketpy/sensors/gyroscope.py b/rocketpy/sensors/gyroscope.py
index 455dcb449..eb1337a73 100644
--- a/rocketpy/sensors/gyroscope.py
+++ b/rocketpy/sensors/gyroscope.py
@@ -228,8 +228,7 @@ def measure(self, time, **kwargs):
         )
         W = inertial_to_sensor @ omega
 
-        # Apply noise + bias
-        # Apply noise + bias and quatize
+        # Apply noise + bias and quantize
         W = self.apply_noise(W)
         W = self.apply_temperature_drift(W)
 
diff --git a/rocketpy/sensors/sensor.py b/rocketpy/sensors/sensor.py
index 7ae3ad3dc..fe15384ba 100644
--- a/rocketpy/sensors/sensor.py
+++ b/rocketpy/sensors/sensor.py
@@ -352,8 +352,6 @@ def __init__(
               standard rotation sequence is z-y-x (3-2-1) is used, meaning the
               sensor is first rotated by ψ around the x axis, then by θ around
               the new y axis and finally by φ around the new z axis.
-              TODO: x and y are not defined in the rocket class. User has no
-              way to know which axis is which.
             - A list of lists (matrix) of shape 3x3, representing the rotation
               matrix from the sensor frame to the rocket frame. The sensor frame
               of reference is defined as to have z axis along the sensor's normal
diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py
index f5733dfab..e7b53754a 100644
--- a/rocketpy/simulation/flight.py
+++ b/rocketpy/simulation/flight.py
@@ -706,7 +706,7 @@ def __simulate(self, verbose):
                     callback(self)
 
                 if self.sensors:
-                    # udot for all sensors
+                    # u_dot for all sensors
                     u_dot = phase.derivative(self.t, self.y_sol)
                     for sensor, position in node._component_sensors:
                         relative_position = position - self.rocket._csys * Vector(
@@ -3229,7 +3229,7 @@ def export_sensor_data(self, file_name, sensor=None):
 
         with open(file_name, "w") as file:
             json.dump(data_dict, file)
-        print("Sensor data exported to", file_name)
+        print("Sensor data exported to: ", file_name)
 
     def export_kml(  # TODO: should be moved out of this class.
         self,

From 3c759f72a86061ca8e57dd6d92c17c4738503c27 Mon Sep 17 00:00:00 2001
From: Gui-FernandesBR <guilherme_fernandes@usp.br>
Date: Thu, 12 Sep 2024 02:16:11 -0300
Subject: [PATCH 120/120] TST: Add a test for sensors draw

---
 tests/integration/test_sensor.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/tests/integration/test_sensor.py b/tests/integration/test_sensor.py
index 2998b5f99..744a4178b 100644
--- a/tests/integration/test_sensor.py
+++ b/tests/integration/test_sensor.py
@@ -1,5 +1,6 @@
 import json
 import os
+from unittest.mock import patch
 
 import numpy as np
 import pytest
@@ -86,6 +87,15 @@ def test_gnss_receiver(self):
         assert np.allclose(np.array(altitude), sim_altitude, atol=1e-12)
 
 
+@pytest.mark.parametrize("plane", ["xz", "yz"])
+@patch("matplotlib.pyplot.show")
+def test_draw(
+    mock_show, calisto_with_sensors, plane
+):  # pylint: disable=unused-argument
+    """Test the drawing of the sensors."""
+    calisto_with_sensors.draw(plane=plane)
+
+
 def test_export_all_sensors_data(flight_calisto_with_sensors):
     """Test the export of sensor data.