diff --git a/CHANGELOG.md b/CHANGELOG.md index 1137336a0..771e8ca36 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -35,6 +35,7 @@ straightforward as possible. - ENH: Shepard Optimized Interpolation - Multiple Inputs Support [#515](https://github.com/RocketPy-Team/RocketPy/pull/515) - ENH: adds new Function.savetxt method [#514](https://github.com/RocketPy-Team/RocketPy/pull/514) - ENH: Argument for Optional Mutation on Function Discretize [#519](https://github.com/RocketPy-Team/RocketPy/pull/519) +- ENH: Air Brakes [#426](https://github.com/RocketPy-Team/RocketPy/pull/426) ### Changed diff --git a/data/calisto/air_brakes_cd.csv b/data/calisto/air_brakes_cd.csv new file mode 100644 index 000000000..ad081a468 --- /dev/null +++ b/data/calisto/air_brakes_cd.csv @@ -0,0 +1,134 @@ +deployment_level, mach, cd +0.0, 0.0, 0.000 +0.0, 0.1, 0.000 +0.0, 0.2, 0.000 +0.0, 0.3, 0.000 +0.0, 0.4, 0.000 +0.0, 0.5, 0.000 +0.0, 0.6, 0.000 +0.0, 0.7, 0.000 +0.0, 0.8, 0.000 +0.0, 0.9, 0.000 +0.0, 1.0, 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0.3, 0.275 +0.5, 0.4, 0.257 +0.5, 0.5, 0.284 +0.5, 0.6, 0.349 +0.5, 0.7, 0.340 +0.5, 0.8, 0.360 +0.5, 0.9, 0.340 +0.5, 1.0, 0.288 +0.5, 1.1, 0.253 +0.6, 0.1, 0.245 +0.6, 0.2, 0.288 +0.6, 0.3, 0.382 +0.6, 0.4, 0.360 +0.6, 0.5, 0.382 +0.6, 0.6, 0.457 +0.6, 0.7, 0.445 +0.6, 0.8, 0.447 +0.6, 0.9, 0.434 +0.6, 1.0, 0.403 +0.6, 1.1, 0.360 +0.7, 0.1, 0.320 +0.7, 0.2, 0.392 +0.7, 0.3, 0.487 +0.7, 0.4, 0.476 +0.7, 0.5, 0.476 +0.7, 0.6, 0.564 +0.7, 0.7, 0.527 +0.7, 0.8, 0.531 +0.7, 0.9, 0.527 +0.7, 1.0, 0.520 +0.7, 1.1, 0.487 +0.8, 0.1, 0.426 +0.8, 0.2, 0.507 +0.8, 0.3, 0.568 +0.8, 0.4, 0.538 +0.8, 0.5, 0.538 +0.8, 0.6, 0.617 +0.8, 0.7, 0.613 +0.8, 0.8, 0.624 +0.8, 0.9, 0.613 +0.8, 1.0, 0.520 +0.8, 1.1, 0.591 +0.9, 0.1, 0.507 +0.9, 0.2, 0.568 +0.9, 0.3, 0.613 +0.9, 0.4, 0.600 +0.9, 0.5, 0.609 +0.9, 0.6, 0.684 +0.9, 0.7, 0.684 +0.9, 0.8, 0.702 +0.9, 0.9, 0.708 +0.9, 1.0, 0.624 +0.9, 1.1, 0.674 +1.0, 0.1, 0.932 +1.0, 0.2, 0.932 +1.0, 0.3, 0.932 +1.0, 0.4, 0.882 +1.0, 0.5, 0.798 +1.0, 0.6, 0.925 +1.0, 0.7, 0.882 +1.0, 0.8, 0.916 +1.0, 0.9, 0.810 +1.0, 1.0, 0.839 +1.0, 1.1, 0.798 \ No newline at end of file diff --git a/docs/notebooks/air_brakes_example.ipynb b/docs/notebooks/air_brakes_example.ipynb new file mode 100644 index 000000000..213f3dc30 --- /dev/null +++ b/docs/notebooks/air_brakes_example.ipynb @@ -0,0 +1,485 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "nvAT8wcRNVEk" + }, + "source": [ + "# Air Brakes Example\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "XGK9M8ecNVEp" + }, + "outputs": [], + "source": [ + "from rocketpy import Environment, SolidMotor, Rocket, Flight, Function\n", + "from datetime import datetime" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "uRa566HoNVE9" + }, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "5kl-Je8dNVFI" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Gravity Details\n", + "\n", + "Acceleration of gravity at surface level: 9.7913 m/s²\n", + "Acceleration of gravity at 10.000 km (ASL): 9.7649 m/s²\n", + "\n", + "\n", + "Launch Site Details\n", + "\n", + "Launch Site Latitude: 32.99025°\n", + "Launch Site Longitude: -106.97500°\n", + "Reference Datum: SIRGAS2000\n", + "Launch Site UTM coordinates: 315468.64 W 3651938.65 N\n", + "Launch Site UTM zone: 13S\n", + "Launch Site Surface Elevation: 1400.0 m\n", + "\n", + "\n", + "Atmospheric Model Details\n", + "\n", + "Atmospheric Model Type: custom_atmosphere\n", + "custom_atmosphere Maximum Height: 10.000 km\n", + "\n", + "\n", + "Surface Atmospheric Conditions\n", + "\n", + "Surface Wind Speed: 4.69 m/s\n", + "Surface Wind Direction: 219.81°\n", + "Surface Wind Heading: 39.81°\n", + "Surface Pressure: 856.02 hPa\n", + "Surface Temperature: 279.07 K\n", + "Surface Air Density: 1.069 kg/m³\n", + "Surface Speed of Sound: 334.55 m/s\n", + "\n", + "\n", + "Earth Model Details\n", + "\n", + "Earth Radius at Launch site: 6371.83 km\n", + "Semi-major Axis: 6378.14 km\n", + "Semi-minor Axis: 6356.75 km\n", + "Flattening: 0.0034\n", + "\n", + "\n", + "Atmospheric Model Plots\n", + "\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "env = Environment(latitude=32.990254, longitude=-106.974998, elevation=1400)\n", + "env.set_atmospheric_model(\n", + " type=\"custom_atmosphere\", wind_u=[(0, 3), (10000, 3)], wind_v=[(0, 5), (10000, -5)]\n", + ")\n", + "env.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "Vx1dZObwNVFX" + }, + "outputs": [], + "source": [ + "Pro75M1670 = SolidMotor(\n", + " thrust_source=\"../../data/motors/Cesaroni_M1670.eng\",\n", + " dry_mass=1.815,\n", + " dry_inertia=(0.125, 0.125, 0.002),\n", + " nozzle_radius=33 / 1000,\n", + " grain_number=5,\n", + " grain_density=1815,\n", + " grain_outer_radius=33 / 1000,\n", + " grain_initial_inner_radius=15 / 1000,\n", + " grain_initial_height=120 / 1000,\n", + " grain_separation=5 / 1000,\n", + " grains_center_of_mass_position=0.397,\n", + " center_of_dry_mass_position=0.317,\n", + " nozzle_position=0,\n", + " burn_time=3.9,\n", + " throat_radius=11 / 1000,\n", + " coordinate_system_orientation=\"nozzle_to_combustion_chamber\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "D1fyK8u_NVFh" + }, + "outputs": [], + "source": [ + "calisto = Rocket(\n", + " radius=127 / 2000,\n", + " mass=14.426,\n", + " inertia=(6.321, 6.321, 0.034),\n", + " power_off_drag=\"../../data/calisto/powerOffDragCurve.csv\",\n", + " power_on_drag=\"../../data/calisto/powerOnDragCurve.csv\",\n", + " center_of_mass_without_motor=0,\n", + " coordinate_system_orientation=\"tail_to_nose\",\n", + ")\n", + "\n", + "rail_buttons = calisto.set_rail_buttons(\n", + " upper_button_position=0.0818,\n", + " lower_button_position=-0.618,\n", + " angular_position=45,\n", + ")\n", + "\n", + "calisto.add_motor(Pro75M1670, position=-1.255)\n", + "\n", + "nose_cone = calisto.add_nose(length=0.55829, kind=\"vonKarman\", position=1.278)\n", + "\n", + "fin_set = calisto.add_trapezoidal_fins(\n", + " n=4,\n", + " root_chord=0.120,\n", + " tip_chord=0.060,\n", + " span=0.110,\n", + " position=-1.04956,\n", + " cant_angle=0.5,\n", + " airfoil=(\"../../data/calisto/NACA0012-radians.csv\", \"radians\"),\n", + ")\n", + "\n", + "tail = calisto.add_tail(\n", + " top_radius=0.0635, bottom_radius=0.0435, length=0.060, position=-1.194656\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def controller_function(\n", + " time, sampling_rate, state, state_history, observed_variables, air_brakes\n", + "):\n", + " # state = [x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz]\n", + " altitude_ASL = state[2]\n", + " altitude_AGL = altitude_ASL - env.elevation\n", + " vx, vy, vz = state[3], state[4], state[5]\n", + " \n", + " # Get winds in x and y directions\n", + " wind_x, wind_y = env.wind_velocity_x(altitude_ASL), env.wind_velocity_y(altitude_ASL)\n", + " \n", + " # Calculate Mach number\n", + " free_stream_speed = (\n", + " (wind_x - vx) ** 2 + (wind_y - vy) ** 2 + (vz) ** 2\n", + " ) ** 0.5\n", + " mach_number = free_stream_speed / env.speed_of_sound(altitude_ASL)\n", + "\n", + " # Get previous state from state_history\n", + " previous_state = state_history[-1]\n", + " previous_vz = previous_state[5]\n", + "\n", + " # If we wanted to we could get the returned values from observed_variables:\n", + " # returned_time, deployment_level, drag_coefficient = observed_variables[-1]\n", + "\n", + " # Check if the rocket has reached burnout\n", + " if time < Pro75M1670.burn_out_time:\n", + " return None\n", + "\n", + " # If below 1500 meters above ground level, air_brakes are not deployed\n", + " if altitude_AGL < 1500:\n", + " air_brakes.deployment_level = 0\n", + "\n", + " # Else calculate the deployment level\n", + " else:\n", + " # Controller logic\n", + " new_deployment_level = (\n", + " air_brakes.deployment_level + 0.1 * vz + 0.01 * previous_vz**2\n", + " )\n", + "\n", + " # Limiting the speed of the air_brakes to 0.2 per second\n", + " # Since this function is called every 1/sampling_rate seconds\n", + " # the max change in deployment level per call is 0.2/sampling_rate\n", + " max_change = 0.2 / sampling_rate\n", + " lower_bound = air_brakes.deployment_level - max_change\n", + " upper_bound = air_brakes.deployment_level + max_change\n", + " new_deployment_level = min(max(new_deployment_level, lower_bound), upper_bound)\n", + "\n", + " air_brakes.deployment_level = new_deployment_level\n", + "\n", + " # Return variables of interest to be saved in the observed_variables list\n", + " return (\n", + " time,\n", + " air_brakes.deployment_level,\n", + " air_brakes.drag_coefficient(air_brakes.deployment_level, mach_number),\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "air_brakes = calisto.add_air_brakes(\n", + " drag_coefficient_curve=\"../../data/calisto/air_brakes_cd.csv\",\n", + " controller_function=controller_function,\n", + " sampling_rate=10,\n", + " reference_area=None,\n", + " clamp=True,\n", + " initial_observed_variables=[0, 0, 0],\n", + " override_rocket_drag=False,\n", + " name=\"AirBrakes\",\n", + " controller_name=\"AirBrakes Controller\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "air_brakes.all_info()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "v__Ud2p2NVFx" + }, + "outputs": [], + "source": [ + "test_flight = Flight(\n", + " rocket=calisto,\n", + " environment=env,\n", + " rail_length=5.2,\n", + " inclination=85,\n", + " heading=0,\n", + " time_overshoot=False,\n", + " terminate_on_apogee=True,\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "8SjrGQqzNVF0" + }, + "source": [ + "## Analyzing the Results\n", + "\n", + "Now we can see some plots from our air brakes:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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RT0sRyVZhYSF++OEHbNq0CcXFxZgxY4bUJZGJfPPNNzh69Cg+/vhjTJ8+XT8Bm4jqMdwQydTRo0cxfvx4BAQEYPHixejevbvUJZGJPPfccygoKMDw4cMbvcknka3jnBsiIiKSFc65ISIiIllhuCEiIiJZsbk5N1qtFhcuXIC7u7vZbzBHREREpiGEQHl5OVq1atXgxsF/ZXPh5sKFCw3uXktERETW4ezZs2jduvVN17G5cKO7ouzZs2fh4eFh0n2r1Wps374dQ4YMgUqlMum+6dY4/tLjeyAtjr+0OP7mVVZWhtDQ0AZXhm+MzYUb3akoDw8Ps4QbFxcXeHh48IMtAY6/9PgeSIvjLy2Of8toypQSTigmIiIiWWG4ISIiIllhuCEiIiJZYbghIiIiWWG4ISIiIllhuCEiIiJZYbghIiIiWWG4ISIiIllhuCEiIiJZYbghIiIiWZE03OzcuRMjRoxAq1atoFAosGXLlltuk5mZiTvvvBOOjo6IiIjA6tWrzV4nERERWQ9Jw01lZSW6deuGJUuWNGn906dP4/7778eAAQNw8OBBzJw5E0888QS+//57M1dKRERE1kLSG2cOGzYMw4YNa/L6y5cvR3h4ON59910AwB133IGffvoJ7733HuLj481VJhHJVFVtHUoqa6Uuw2Tq6upQUgOcL70Ke3u11OXYHI7/nxzs7RDg7iTZ61vVXcF3796NuLg4g2Xx8fGYOXPmDbepqalBTU2N/nFZWRmA+ru3qtWm/fDp9mfq/VLTcPylZ03vQWF5DYYu3oXy6jqpSzExe6Qe+FHqImwYxx8AeoR6YsOTMSbdpzG/V6wq3OTn5yMwMNBgWWBgIMrKynD16lU4Ozs32Gb+/PlITU1tsHz79u1wcXExS51paWlm2S81DcdfetbwHvyUr0B5tRIKCNgrpK6GSF7Kr5Ri69atJt1nVVVVk9e1qnDTHHPmzEFSUpL+cVlZGUJDQzFkyBB4eHiY9LXUajXS0tIwePBgqFQqk+6bbo3jLz1reg+2fH4AQBGS4iLxdL92UpdjEtY0/nLE8Tcv3ZmXprCqcBMUFISCggKDZQUFBfDw8Gj0qA0AODo6wtHRscFylUpltg+fOfdNt8bxl56lvwfVag1+OXUZADCoU7BF19oclj7+csfxNw9jxtSqrnMTGxuL9PR0g2VpaWmIjY2VqCIiskZ7c0twVa1BoIcj7gh2l7ocIjIxScNNRUUFDh48iIMHDwKob/U+ePAg8vLyANSfUkpISNCv//TTT+PUqVN46aWXcOzYMSxduhQbNmzArFmzpCifiKxUxrFLAID+UQFQKDjhhkhuJA03+/btQ48ePdCjRw8AQFJSEnr06IHk5GQAwMWLF/VBBwDCw8Px3//+F2lpaejWrRveffddfPLJJ2wDJyKjZB4vBAD07+AvcSVEZA6Szrnp378/hBA3fL6xqw/3798fv/32mxmrIiI5yyuuwqlLlbC3U+DeSD+pyyEiM7CqOTdERLdLd9SmZ1tveDhx0ieRHDHcEJFNycy+Nt+mQ4DElRCRuTDcEJHNqFZr8PPJIgDAgI6cb0MkVww3RGQzfj1dgmq1FkEeTugQyBZwIrliuCEim5FxrH6+zYCO/mwBJ5IxhhsishlZx+vn2/SL4nwbIjljuCEim5BbVInTRddawCN8pS6HiMyI4YaIbEJmdv0pqbvCfODOFnAiWWO4ISKbkHlc1wLOLikiuWO4ISLZq1ZrsPtkMQBgQEfOtyGSO4YbIpK93aeKUVOnRStPJ0QGuEldDhGZGcMNEcle5rUW8H4deBdwIlvAcENEsqebbzOA822IbALDDRHJ2umiSpwproJKqcA9EbwLOJEtYLghIlnTXZW4d7gP3BztJa6GiFoCww0RyZq+BZxXJSayGQw3RCRbV2s1+OVUfQs4r29DZDsYbohItnafKkJtnRYhXs6IYAs4kc1guCEi2crM/vOqxGwBJ7IdDDdEJEtCCGRcu5/UgA6cb0NkSxhuiEiWThVV4mzJVTgo7XAP7wJOZFMYbohIlnQt4DHtfODiwBZwIlvCcENEspR1rQW8XxS7pIhsDcMNEclOVW0dfj1VAgDoz/k2RDaH4YaIZOfnE8Wo1WgR6uOM9v6uUpdDRC2M4YaIZCfzeP18m/5RvAs4kS1iuCEiWRFCIOPYtbuAd+R8GyJbxHBDRLJy8lIFzpdehYO9HWLb8S7gRLaI4YaIZEV31CYm3AfODkqJqyEiKTDcEJGs6Obb8KrERLaL4YaIZKOypg57TutawDnfhshWMdwQkWzsOlEEtUagra8Lwv3YAk5kqxhuiEg2Mq9dlbh/FO8CTmTLGG6ISBaEEMi8dj8pXpWYyLYx3BCRLOQUVuDClWo42tvh7na8CziRLWO4ISJZyMyuP2pzdztftoAT2TiGGyKSBf1VidklRWTzGG6IyOqVV6ux7wzvAk5E9RhuiMjq7TpRDLVGIMzXBWFsASeyeQw3RGT1so6zS4qI/sRwQ0RWTQiBzOxr17fhfBsiAsMNEVm57IJyXLxSDScVW8CJqB7DDRFZNd1Rm9h2vnBSsQWciBhuiMjKZVy7KvGAjpxvQ0T1GG6IyGqVV6ux/8xlAED/KIYbIqrHcENEVmvXiSLUaQXa+bmija+L1OUQkYVguCEiq6W7KjFbwInoegw3RGSVhBDI1F/fhi3gRPQnhhsiskp/XCxHQVkNnFVK9A73kbocIrIgDDdEZJV0R23uac8WcCIyxHBDRFYp8xivSkxEjWO4ISKrc+WqGvvzrrWAczIxEf0Fww0RWZ1dJ4qg0Qq093dFqA9bwInIEMMNEVkd/VWJedSGiBrBcENEVqW+BZzXtyGiG2O4ISKr8r8LZbhUXgMXByXuCveWuhwiskCSh5slS5YgLCwMTk5OiImJwZ49e266/qJFi9ChQwc4OzsjNDQUs2bNQnV1dQtVS0RSy7p21Oae9n5wtGcLOBE1JGm4Wb9+PZKSkpCSkoIDBw6gW7duiI+PR2FhYaPrf/HFF5g9ezZSUlLwxx9/4NNPP8X69evxyiuvtHDlRCSVzGxelZiIbk7ScLNw4UJMnToViYmJ6NSpE5YvXw4XFxesXLmy0fV//vln3HvvvXjssccQFhaGIUOGYNy4cbc82kNE8nCl6rq7gDPcENEN2Ev1wrW1tdi/fz/mzJmjX2ZnZ4e4uDjs3r270W3uuecefP7559izZw969+6NU6dOYevWrZgwYcINX6empgY1NTX6x2VlZQAAtVoNtVptop8G+n1e/7/Usjj+0jP3e5B5LB9aAUT4uyLQTcX3+i/4HZAWx9+8jBlXycJNUVERNBoNAgMDDZYHBgbi2LFjjW7z2GOPoaioCH369IEQAnV1dXj66advelpq/vz5SE1NbbB8+/btcHExz/Ux0tLSzLJfahqOv/TM9R6sPWEHwA6h9uXYunWrWV5DDvgdkBbH3zyqqqqavK5k4aY5MjMz8dZbb2Hp0qWIiYnBiRMnMGPGDLz++uuYO3duo9vMmTMHSUlJ+sdlZWUIDQ3FkCFD4OHhYdL61Go10tLSMHjwYKhUKpPum26N4y89c74HWq3A6//IAlCLxKF3Ibadr0n3Lwf8DkiL429eujMvTSFZuPHz84NSqURBQYHB8oKCAgQFBTW6zdy5czFhwgQ88cQTAIDo6GhUVlbiySefxN///nfY2TWcQuTo6AhHR8cGy1Uqldk+fObcN90ax1965ngPjpy/gqKKWrg6KHF3+wCo7CVv9rRY/A5Ii+NvHsaMqWS/HRwcHNCzZ0+kp6frl2m1WqSnpyM2NrbRbaqqqhoEGKWyvhVUCGG+YolIcrqrEt8b4QcHBhsiuglJT0slJSVh4sSJ6NWrF3r37o1FixahsrISiYmJAICEhASEhIRg/vz5AIARI0Zg4cKF6NGjh/601Ny5czFixAh9yCEieeJViYmoqSQNN2PGjMGlS5eQnJyM/Px8dO/eHdu2bdNPMs7LyzM4UvPqq69CoVDg1Vdfxfnz5+Hv748RI0bgzTfflOpHIKIWUFpVi9/y2AJORE0j+YTi6dOnY/r06Y0+l5mZafDY3t4eKSkpSElJaYHKiMhS7MwpglYAHQLd0crLWepyiMjC8cQ1EVk8XpWYiIzBcENEFk2rFcjK5nwbImo6hhsismhHLlxBcWUt3Bzt0SuMdwEnoltjuCEii5ZxrP6oTZ8IP6iU/JVFRLfG3xREZNEyj3O+DREZh+GGiCxWSWUtDp4tBQD0Y7ghoiZiuCEii/VjziUIAXQMckewJ1vAiahpGG6IyGJlskuKiJqB4YaILJJWK5B17ZYLA3hKioiMwHBDRBbp8PkrKKmshbujPe5syxZwImo6hhsiski6u4D3iWQLOBEZh78xiMgiZepPSXG+DREZh+GGiCxOcUUNDp8rBcAWcCIyHsMNEVmcnddawDsFeyDQw0nqcojIyjDcEJHF+bMFnEdtiMh4DDdEZFE017WA8/o2RNQcDDdEZFEOnStFaZUa7k72uLONl9TlEJEVYrghIouiOyV1X6Q/7NkCTkTNwN8cRGRRMrN5F3Aiuj0MN0RkMS6V1+DwuSsA2AJORM3HcENEFmPntYnEXUI8EODOFnAiah6GGyKyGLqrEvePYpcUETUfww0RWQSNVuiP3HC+DRHdDoYbIrIIB89expWrang6q9A91EvqcojIijHcEJFF0LWA9430Yws4Ed0W/gYhIouQca0FnHcBJ6LbxXBDRJIrLK/GkfNlAID7ojjfhohuD8MNEUku69opqegQT/i7O0pcDRFZO4YbIpKcrgV8ALukiMgEGG6ISFJ1Gi1+vBZu+nG+DRGZAMMNEUnqt7OlKKuug5cLW8CJyDQYbohIUrobZd4X6Q+lnULiaohIDhhuiEhSGcd4VWIiMi37pqz08MMPN3mHmzdvbnYxRGRbCsuqcfRiGRQKtoATkek0Kdx4enqauw4iskG6LqmuIZ7wc2MLOBGZRpPCzapVq8xdBxHZIN18m/7skiIiE2rWnJu6ujr88MMP+Oijj1BeXg4AuHDhAioqKkxaHBHJl1qjxY85RQA434aITKtJR26ud+bMGQwdOhR5eXmoqanB4MGD4e7ujgULFqCmpgbLly83R51EJDMHzlxGeXUdvF1U6NraS+pyiEhGjD5yM2PGDPTq1QuXL1+Gs7OzfvlDDz2E9PR0kxZHRPKlm2/TL4ot4ERkWkYfufnxxx/x888/w8HBwWB5WFgYzp8/b7LCiEjeMrN1LeCcb0NEpmX0kRutVguNRtNg+blz5+Du7m6SoohI3vKvVOMPtoATkZkYHW6GDBmCRYsW6R8rFApUVFQgJSUFw4cPN2VtRCRTWcfru6S6tfaCj6vDLdYmIjKO0ael3n33XcTHx6NTp06orq7GY489hpycHPj5+eHLL780R41EJDO8KjERmZPR4aZ169Y4dOgQ1q1bh8OHD6OiogJTpkzB+PHjDSYYExE1Rq3R4qcT9S3gAzjfhojMwOhwU11dDScnJzz++OPmqIeIZG5f7mVU1NTB19UB0SG8+jkRmZ7Rc24CAgIwceJEpKWlQavVmqMmIpKxzGvzbfpF+cOOLeBEZAZGh5vPPvsMVVVVePDBBxESEoKZM2di37595qiNiGQo61oLeD/OtyEiMzE63Dz00EPYuHEjCgoK8NZbb+Ho0aO4++67ERUVhXnz5pmjRiKSiQulV3Esvxx2CuC+SIYbIjKPZt1bCgDc3d2RmJiI7du34/Dhw3B1dUVqaqopayMimcm6dlXi7qFe8GYLOBGZSbPDTXV1NTZs2IBRo0bhzjvvRElJCV588UVT1kZEMpNxjHcBJyLzM7pb6vvvv8cXX3yBLVu2wN7eHqNHj8b27dtx3333maM+IpKJ2jotdrEFnIhagNHh5qGHHsIDDzyANWvWYPjw4VCpVOaoi4hkZt+ZElTWauDn5oDOrTykLoeIZMzocFNQUMB7SBGR0XQ3yuwXFcAWcCIyK6Pn3Li7u+PkyZN49dVXMW7cOBQW1p9D/+677/C///3P5AUSkTxkZuvm27BLiojMy+hwk5WVhejoaPz666/YvHkzKioqAACHDh1CSkqKyQskIut3vvQqjhdUwE4B9I30k7ocIpI5o8PN7Nmz8cYbbyAtLQ0ODn+2cg4cOBC//PKLSYsjInnQHbW5s403vFzYAk5E5mV0uPn999/x0EMPNVgeEBCAoqIiowtYsmQJwsLC4OTkhJiYGOzZs+em65eWlmLatGkIDg6Go6MjoqKisHXrVqNfl4hajm6+DU9JEVFLMDrceHl54eLFiw2W//bbbwgJCTFqX+vXr0dSUhJSUlJw4MABdOvWDfHx8fp5PH9VW1uLwYMHIzc3F5s2bUJ2djZWrFhh9OsSUcupqdPoW8B5fRsiaglGh5uxY8fi5ZdfRn5+PhQKBbRaLXbt2oUXXngBCQkJRu1r4cKFmDp1KhITE9GpUycsX74cLi4uWLlyZaPrr1y5EiUlJdiyZQvuvfdehIWFoV+/fujWrZuxPwYRtZB9uZdRVauBv7sjW8CJqEUY3Qr+1ltvYdq0aQgNDYVGo0GnTp2g0Wjw2GOP4e9//3uT91NbW4v9+/djzpw5+mV2dnaIi4vD7t27G93m66+/RmxsLKZNm4b//Oc/8Pf3x2OPPYaXX34ZSqWy0W1qampQU1Ojf1xWVgYAUKvVUKvVTa63KXT7M/V+qWk4/tJr7D1IP5oPAOgb4Yu6ujpJ6rIV/A5Ii+NvXsaMq9HhxsHBAStWrEBycjJ+//13VFRUoEePHoiMjDRqP0VFRdBoNAgMDDRYHhgYiGPHjjW6zalTp7Bjxw6MHz8eW7duxYkTJ/Dss89CrVbfsFNr/vz5jd7zavv27XBxcTGq5qZKS0szy36paTj+0rv+PfjvQSUABTwqz2Lr1jzpirIh/A5Ii+NvHlVVVU1e1+hwoxMaGorQ0FD948OHD6NXr16ora1t7i5vSavVIiAgAB9//DGUSiV69uyJ8+fP4x//+McNw82cOXOQlJSkf1xWVobQ0FAMGTIEHh6mPUSuVquRlpaGwYMH88rNEuD4S++v78G5y1dRsPtHKO0UeG50HDyc+b6YE78D0uL4m5fuzEtTNDvc/JUQAhqNpsnr+/n5QalUoqCgwGB5QUEBgoKCGt0mODgYKpXK4BTUHXfcgfz8fNTW1hq0pus4OjrC0dGxwXKVSmW2D5859023xvGXnu49+OnUBQBAzzbe8PUwz5FSaojfAWlx/M3DmDFt9l3Bb5eDgwN69uyJ9PR0/TKtVov09HTExsY2us29996LEydOQKvV6pcdP34cwcHBjQYbIpJW1rXr2/RjCzgRtSDJwg0AJCUlYcWKFfjss8/wxx9/4JlnnkFlZSUSExMBAAkJCQYTjp955hmUlJRgxowZOH78OP773//qJzgTkWWpVmuw60QxAF7fhohaVpNPS93qXFd5ebnRLz5mzBhcunQJycnJyM/PR/fu3bFt2zb9JOO8vDzY2f2Zv0JDQ/H9999j1qxZ6Nq1K0JCQjBjxgy8/PLLRr82EZnX3twSXFVrEODuiE7BbAEnopbT5HDj5eUFheLGd/IVQtz0+RuZPn06pk+f3uhzmZmZDZbFxsbyNg9EViDj2J9XJW7O7wYiouZqcrjJyMgwZx1EJDOZx+vn2wzgVYmJqIU1Odz069fPnHUQkYzklVTh1KVK2NspcC/vAk5ELUzSCcVEJE87c+rvJdWzrTc8nNgSS0Qti+GGiEwu6zhvlElE0mG4ISKTUmuBX06XAGALOBFJg+GGiEzqRJkC1Wotgjyc0DHIXepyiMgGGR1uJk+e3Og1bSorKzF58mSTFEVE1uuPy/Vt32wBJyKpGB1uPvvsM1y9erXB8qtXr2LNmjUmKYqIrNfRUl244XwbIpKGUVcoFkJACIHy8nI4OTnpn9NoNNi6dSsCAvjLjMiWnSmuwqVqRX0LeISv1OUQkY0y+grFCoUCUVFRDZ5XKBRITU01aXFEZF2y9C3gXnBnCzgRScSoKxQLITBw4ED8+9//ho+Pj/45BwcHtG3bFq1atTJLkURkHXZeawHvF8UL9xGRdIy+QvHp06cRGhpqcENLIqJqtUbfAt6PVyUmIgk1OdzotG3bFqWlpdizZw8KCwuh1WoNnk9ISDBZcURkPXafKkZNnRZeDgKRAW5Sl0NENszocPPNN99g/PjxqKiogIeHh0Grp0KhYLghslFZ2fV3Ae/kJdgCTkSSMvrc0v/93/9h8uTJqKioQGlpKS5fvqz/V1JSYo4aicgKZGTX3wX8Dm8hcSVEZOuMDjfnz5/H888/DxcXF3PUQ0RW6HRRJc4UV0GlVCDKk+GGiKRldLiJj4/Hvn37zFELEVmpzGtHbXq19YaTUuJiiMjmGT3n5v7778eLL76Io0ePIjo6GiqV4bUsRo4cabLiiMg6ZFybb9Mvyg+4UihxNURk64wON1OnTgUAzJs3r8FzCoUCGo3m9qsiIqtxtVaDX04VAwDui/RDDg/sEpHEjA43f239JiLbtvtUEWrrtAjxckaEvytypC6IiGzebV2Jr7q62lR1EJGVyrx2Sop3ASciS2F0uNFoNHj99dcREhICNzc3nDp1CgAwd+5cfPrppyYvkIgslxBC3wLOu4ATkaUwOty8+eabWL16Nd555x04ODjol3fp0gWffPKJSYsjIst2qqgSZ0uuwkFph3va8y7gRGQZjA43a9aswccff4zx48dDqfyz57Nbt244duyYSYsjIsumOyXVO9wHro5GT+EjIjKLZl3ELyIiosFyrVYLtVptkqKIyDpk6k9J+UtcCRHRn4wON506dcKPP/7YYPmmTZvQo0cPkxRFRJavqrYOv56qv+UK59sQkSUx+jhycnIyJk6ciPPnz0Or1WLz5s3Izs7GmjVr8O2335qjRiKyQD+fKEatRovW3s5o7+8qdTlERHpGH7l58MEH8c033+CHH36Aq6srkpOT8ccff+Cbb77B4MGDzVEjEVmgzOP1p6QGdAhgCzgRWZRmzQDs27cv0tLSTF0LEVkJIYTB9W2IiCzJbbU3VFRUNLhisYeHx20VRESW7+SlCpy7fBUO9naIZQs4EVkYo09LnT59Gvfffz9cXV3h6ekJb29veHt7w8vLC97e3uaokYgsjO6oTUy4D1wc2AJORJbF6N9Kjz/+OIQQWLlyJQIDA3muncgG8arERGTJjA43hw4dwv79+9GhQwdz1ENEFq6ypg57T18GAAzgfBsiskBGn5a66667cPbsWXPUQkRW4OeT9S3gbXxcEO7HFnAisjxGH7n55JNP8PTTT+P8+fPo0qULVCqVwfNdu3Y1WXFEZHl0p6QG8C7gRGShjA43ly5dwsmTJ5GYmKhfplAoIISAQqGARqMxaYFEZDmEEMjSt4Bzvg0RWSajw83kyZPRo0cPfPnll5xQTGRjcgorcL60vgX87nZsASciy2R0uDlz5gy+/vrrRm+eSUTyprtRZmw7Xzg7KCWuhoiocUZPKB44cCAOHTpkjlqIyMLxqsREZA2MPnIzYsQIzJo1C7///juio6MbTCgeOXKkyYojIstRUVOHvbn1dwEfwPk2RGTBjA43Tz/9NABg3rx5DZ7jhGIi+dp1oghqjUCYrwvC2AJORBbM6HDz13tJEZFtyORViYnIShg95+bUqVPmqIOILBjvAk5E1sTocBMREYEBAwbg888/R3V1tTlqIiILk11QjotXquHIFnAisgJGh5sDBw6ga9euSEpKQlBQEJ566ins2bPHHLURkYXQHbW5p70vnFRsASciy2Z0uOnevTvef/99XLhwAStXrsTFixfRp08fdOnSBQsXLsSlS5fMUScRSYjzbYjImhgdbnTs7e3x8MMPY+PGjViwYAFOnDiBF154AaGhoUhISMDFixdNWScRSaS8Wo19ubq7gDPcEJHla3a42bdvH5599lkEBwdj4cKFeOGFF3Dy5EmkpaXhwoULePDBB01ZJxFJZNeJItRpBdr5uaKNr4vU5RAR3ZLRreALFy7EqlWrkJ2djeHDh2PNmjUYPnw47Ozqc1J4eDhWr16NsLAwU9dKRBLIOFZ/qrkfu6SIyEoYHW6WLVuGyZMnY9KkSQgODm50nYCAAHz66ae3XRwRSUsIgazj9eGGp6SIyFoYHW5ycnJuuY6DgwMmTpzYrIKIyHIcyy9Hflk1nFVK9A73kbocIqImMTrcAEBpaSk+/fRT/PHHHwCAzp07Y/LkyfD09DRpcUQkrYxrXVJsAScia2L0hOJ9+/ahffv2eO+991BSUoKSkhIsXLgQ7du3x4EDB8xRIxFJhFclJiJrZPSRm1mzZmHkyJFYsWIF7O3rN6+rq8MTTzyBmTNnYufOnSYvkoha3pWrauw/U98CzuvbEJE1MTrc7Nu3zyDYAPXXvHnppZfQq1cvkxZHRNLZdaIIGq1Ae39XhPqwBZyIrIfRp6U8PDyQl5fXYPnZs2fh7u5ukqKISHq8KjERWSujw82YMWMwZcoUrF+/HmfPnsXZs2exbt06PPHEExg3blyziliyZAnCwsLg5OSEmJiYJt+rat26dVAoFBg1alSzXpeIGnf9XcDZAk5E1sbo01L//Oc/oVAokJCQgLq6OgCASqXCM888g7ffftvoAtavX4+kpCQsX74cMTExWLRoEeLj45GdnY2AgBv/Us3NzcULL7yAvn37Gv2aRHRzRy+WobC8Bi4OStwV7i11OURERjH6yI2DgwPef/99XL58GQcPHsTBgwdRUlKC9957D46OjkYXsHDhQkydOhWJiYno1KkTli9fDhcXF6xcufKG22g0GowfPx6pqalo166d0a9JRDd3/V3AHe3ZAk5E1qXZ95ZycXFBdHQ0oqOj4eLSvMmGtbW12L9/P+Li4v4syM4OcXFx2L179w23mzdvHgICAjBlypRmvS4R3Rzn2xCRNWvSaamHH364yTvcvHlzk9ctKiqCRqNBYGCgwfLAwEAcO3as0W1++uknfPrppzh48GCTXqOmpgY1NTX6x2VlZQAAtVoNtVrd5FqbQrc/U++XmobjbxrXt4D3ae9t1HjyPZAWx19aHH/zMmZcmxRuLOXKw+Xl5ZgwYQJWrFgBPz+/Jm0zf/58pKamNli+ffv2Zh9xupW0tDSz7JeahuN/e34rUkArlAhyFjj0cwYONWMffA+kxfGXFsffPKqqqpq8bpPCzapVq5pdzM34+flBqVSioKDAYHlBQQGCgoIarH/y5Enk5uZixIgR+mVarRZA/bV2srOz0b59e4Nt5syZg6SkJP3jsrIyhIaGYsiQIfDw8DDljwO1Wo20tDQMHjwYKpXKpPumW+P4m0bW5iMALuD+O8MwfGgHo7bleyAtjr+0OP7mpTvz0hTNurcUABQWFiI7OxsA0KFDh5t2Nt2Ig4MDevbsifT0dH07t1arRXp6OqZPn95g/Y4dO+L33383WPbqq6+ivLwc77//PkJDQxts4+jo2OhEZ5VKZbYPnzn3TbfG8W8+rVZgZ04xAGDgHUHNHke+B9Li+EuL428exoyp0eGmrKwM06ZNw7p166DRaAAASqUSY8aMwZIlS4w+hZWUlISJEyeiV69e6N27NxYtWoTKykokJiYCABISEhASEoL58+fDyckJXbp0Mdjey8sLABosJyLjHb1YhqKKGrg6KNErjC3gRGSdjO6Wmjp1Kn799Vd8++23KC0tRWlpKb799lvs27cPTz31lNEFjBkzBv/85z+RnJyM7t274+DBg9i2bZt+knFeXh4uXrxo9H6JyHgZx67dBTzCjy3gRGS1jD5y8+233+L7779Hnz599Mvi4+OxYsUKDB06tFlFTJ8+vdHTUACQmZl5021Xr17drNckooYyj/OqxERk/Yw+cuPr69voqSdPT094e/MwNpG1Kq2qxW95uruA+0tcDRFR8xkdbl599VUkJSUhPz9fvyw/Px8vvvgi5s6da9LiiKjl7MwpglYAHQLd0crLWepyiIiazejTUsuWLcOJEyfQpk0btGnTBkD9vBhHR0dcunQJH330kX7dAwcOmK5SIjKrP69KzKM2RGTdjA43vAM3kfxotQJZ1+4n1Y/hhoisnNHhJiUlxRx1EJGEjly4guLKWrg52qNXWx+pyyEiui3NunFmaWkpPvnkE8yZMwclJSUA6k9BnT9/3qTFEVHL0N0F/N4IXzjYN/t+ukREFsHoIzeHDx9GXFwcPD09kZubi6lTp8LHxwebN29GXl4e1qxZY446iciMMq7Nt2ELOBHJgdH/iZaUlIRJkyYhJycHTk5O+uXDhw/Hzp07TVocEZlfSWUtDp4tBcD5NkQkD0aHm7179zZ6JeKQkBCD9nAisg4/5lyCEEDHIHcEe7IFnIisn9HhxtHRsdE7cx4/fhz+/vyvPiJro5tv05+npIhIJowONyNHjsS8efOgVqsBAAqFAnl5eXj55ZfxyCOPmLxAIjIfrVYg67gu3PA/TohIHowON++++y4qKioQEBCAq1evol+/foiIiIC7uzvefPNNc9RIRGZy+PwVlFTWwt3RHj3b8vYpRCQPRndLeXp6Ii0tDT/99BMOHz6MiooK3HnnnYiLizNHfURkRrqrEveJ9INKyRZwIpIHo8ONTp8+fQzuDE5E1icjm6ekiEh+jAo3Wq0Wq1evxubNm5GbmwuFQoHw8HCMHj0aEyZMgEKhMFedRGRixRU1OHyuFAAnExORvDT5OLQQAiNHjsQTTzyB8+fPIzo6Gp07d8aZM2cwadIkPPTQQ+ask4hMbOe1FvA7gj0Q6OF06w2IiKxEk4/crF69Gjt37kR6ejoGDBhg8NyOHTswatQorFmzBgkJCSYvkohMT9cCPoCnpIhIZpp85ObLL7/EK6+80iDYAMDAgQMxe/ZsrF271qTFEZF5aLQCO4/z+jZEJE9NDjeHDx/G0KFDb/j8sGHDcOjQIZMURUTmdehcKS5XqeHuZI8723hJXQ4RkUk1OdyUlJQgMDDwhs8HBgbi8uXLJimKiMxLd0rqvkh/2LMFnIhkpsm/1TQaDeztbzxFR6lUoq6uziRFEZF56a5vwxtlEpEcNXlCsRACkyZNgqOjY6PP19TUmKwoIjKfoooaHD53BQDQP4rhhojkp8nhZuLEibdch51SRJZPN5G4cysPBLAFnIhkqMnhZtWqVeasg4haSIa+BZxdUkQkT5xJSGRDDFvAeUqKiOSJ4YbIhhw8exlXrqrh4WSP7qFeUpdDRGQWDDdENkTfAh7FFnAiki/+diOyIZnZvCoxEckfww2RjSgsr8bv5+tbwPuxBZyIZIzhhshG7DxeBACIDvGEv3vj16siIpIDhhsiG5Fx7arE7JIiIrljuCGyAXUaLX7kXcCJyEYw3BDZgINnS1FWXQcvFxVbwIlI9hhuiGyA7pTUfZH+UNopJK6GiMi8GG6IbMCfLeCcb0NE8sdwQyRzhWXV+N+FMgD1F+8jIpI7hhsimcu8NpG4W2tP+LmxBZyI5I/hhkjmMq/Nt+nHLikishEMN0QyVqfR4sec+ov3DeB8GyKyEQw3RDJ2IK8U5dV18HZRoWtrL6nLISJqEQw3RDKmbwGPYgs4EdkOhhsiGdO1gA/gfBsisiEMN0QylX+lGn9cLINCwRZwIrItDDdEMpV1vP6UVLfWXvBxdZC4GiKilsNwQyRTvCoxEdkqhhsiGVJrtPjpWgs47wJORLaG4YZIhvafuYzymjr4ujqga4in1OUQEbUohhsiGbq+BdyOLeBEZGMYbohkKIvzbYjIhjHcEMnMxStXcSy/HHYK4L5Ihhsisj0MN0Qyo+uS6h7qBW+2gBORDWK4IZIZ3V3A2SVFRLaK4YZIRmrrrm8B5ykpIrJNDDdEMrLvTAkqazXwc3NAl1ZsASci28RwQyQjui4ptoATkS1juCGSEd31bXgXcCKyZRYRbpYsWYKwsDA4OTkhJiYGe/bsueG6K1asQN++feHt7Q1vb2/ExcXddH0iW3G+9CqOF1TATgH0jfSTuhwiIslIHm7Wr1+PpKQkpKSk4MCBA+jWrRvi4+NRWFjY6PqZmZkYN24cMjIysHv3boSGhmLIkCE4f/58C1dOZFl0XVI92njDy4Ut4ERkuyQPNwsXLsTUqVORmJiITp06Yfny5XBxccHKlSsbXX/t2rV49tln0b17d3Ts2BGffPIJtFot0tPTW7hyIsuiu77NAHZJEZGNkzTc1NbWYv/+/YiLi9Mvs7OzQ1xcHHbv3t2kfVRVVUGtVsPHx8dcZRJZvJo6DXad4F3AiYgAwF7KFy8qKoJGo0FgYKDB8sDAQBw7dqxJ+3j55ZfRqlUrg4B0vZqaGtTU1Ogfl5WVAQDUajXUanUzK2+cbn+m3i81jS2P/y8ni1FVq4G/mwMi/ZwlGwNbfg8sAcdfWhx/8zJmXCUNN7fr7bffxrp165CZmQknJ6dG15k/fz5SU1MbLN++fTtcXFzMUldaWppZ9ktNY4vjvyXXDoAdwp2rsW3bd1KXY5PvgSXh+EuL428eVVVVTV5X0nDj5+cHpVKJgoICg+UFBQUICgq66bb//Oc/8fbbb+OHH35A165db7jenDlzkJSUpH9cVlamn4Ts4eFxez/AX6jVaqSlpWHw4MFQqVQm3Tfdmi2P/+LFuwBUYvyA7hgeffPvjjnZ8ntgCTj+0uL4m5fuzEtTSBpuHBwc0LNnT6Snp2PUqFEAoJ8cPH369Btu98477+DNN9/E999/j169et30NRwdHeHo6NhguUqlMtuHz5z7pluztfE/W1KFk5cqobRToH/HIIv42W3tPbA0HH9pcfzNw5gxlfy0VFJSEiZOnIhevXqhd+/eWLRoESorK5GYmAgASEhIQEhICObPnw8AWLBgAZKTk/HFF18gLCwM+fn5AAA3Nze4ublJ9nMQSSXzeH2X1J1tvODpwl+oRESSh5sxY8bg0qVLSE5ORn5+Prp3745t27bpJxnn5eXBzu7Ppq5ly5ahtrYWo0ePNthPSkoKXnvttZYsncgiZPEu4EREBiQPNwAwffr0G56GyszMNHicm5tr/oKIrER9C3gxAN4FnIhIR/KL+BFR8+05XYKrag0C3B3RKdi0E+SJiKwVww2RFdNdlbh/B38oFLwLOBERwHBDZNUyON+GiKgBhhsiK3W2pAqnrrWA9+FdwImI9BhuiKyU7i7gPdt6w8OJLeBERDoMN0RWKkN/F3CekiIiuh7DDZEVqlZr8PNJ3V3A2QJORHQ9hhsiK/Tr6RJUq7UI8nBCxyB3qcshIrIoDDdEVihT3yXFFnAior9iuCGyQlnXXd+GiIgMMdwQWZkzxZU4VVQJezsF7o1gCzgR0V8x3BBZGd1ViXuFecOdLeBERA0w3BBZGV6VmIjo5hhuiKxItVqD3Sfr7wLO69sQETWO4YbIiuw+VYyaOi2CPZ0QFegmdTlERBaJ4YbIivzZJRXAFnAiohtguCGyItdf34aIiBrHcENkJU4XVSK3uAoqJVvAiYhuhuGGyErojtrcFeYDN0d7iashIrJcDDdEViKDVyUmImoShhsiK3C1VoNfTrEFnIioKRhuiKzAL6eKUVunRYiXMyIC2AJORHQzDDdEVkB3VeJ+vAs4EdEtMdwQWTghhP5+UjwlRUR0aww3RBbuVFEl8kqq4KC0wz3tfaUuh4jI4jHcEFk43VGb3uE+cGULOBHRLTHcEFk4XpWYiMg4DDdEFqyqtg6/nioBUH8/KSIiujWGGyILtvtkMWo1WrT2dkZ7f1epyyEisgoMN0QWLOO6U1JsASciahqGGyILxRZwIqLmYbghslAnL1Xg3OWrcFDaIZYt4ERETcZwQ2ShdEdtYtr5wMWBLeBERE3FcENkoTL1dwHnKSkiImMw3BBZoMqaOuw5rWsB5/VtiIiMwXBDZIF+vtYC3sbHBe382AJORGQMhhsiC8QWcCKi5mO4IbIwQghksQWciKjZGG6ILMyJwgqcL70KB3s73N2OLeBERMZiuCGyMLpTUne384Wzg1LiaoiIrA/DDZGF+fOqxOySIiJqDoYbIgtSUVOHvbm8CzgR0e1guCGyILtOFEGtEQjzdUE4W8CJiJqF4YbIgvCqxEREt4/hhshC1N8FvH4ycT/OtyEiajaGGyILcbygAhevVMPR3g6xbAEnImo2hhsiC6FrAY9t7wsnFVvAiYiai+GGyELoTknxqsRERLeH4YbIApRXq7Ev9zIA3gWciOh2MdwQWYBdJ4pQpxVo5+eKtr5sASciuh0MN0QWQNcCzi4pIqLbx3BDJLH6FnBe34aIyFQYbogkdiy/HPll1XBS2SEm3EfqcoiIrB7DDZHEdC3g97T3Yws4EZEJMNwQSYx3ASciMi2GGyIJlVWrsf+MrgWc822IiEyB4YZIQj/lFEGjFWjn74pQHxepyyEikgWLCDdLlixBWFgYnJycEBMTgz179tx0/Y0bN6Jjx45wcnJCdHQ0tm7d2kKVEpkWr0pMRGR6koeb9evXIykpCSkpKThw4AC6deuG+Ph4FBYWNrr+zz//jHHjxmHKlCn47bffMGrUKIwaNQpHjhxp4cqJbo9hCzjn2xARmYq91AUsXLgQU6dORWJiIgBg+fLl+O9//4uVK1di9uzZDdZ///33MXToULz44osAgNdffx1paWn48MMPsXz58hat/Xo1dRpcLL2KkhrgfOlV2NurJavFVtXV1VnV+J8uqkRheQ2cVUr0Zgs4EZHJSBpuamtrsX//fsyZM0e/zM7ODnFxcdi9e3ej2+zevRtJSUkGy+Lj47Fly5ZG16+pqUFNTY3+cVlZGQBArVZDrTbdH8BDZ0vx6Md7ANgj9cCPJtsvGcv6xj+2nQ/shBZqtVbqUm6b7jtlyu8WNR3HX1ocf/MyZlwlDTdFRUXQaDQIDAw0WB4YGIhjx441uk1+fn6j6+fn5ze6/vz585Gamtpg+fbt2+HiYroJnLnlgErBa5SQcRyUQJQiX3bzxtLS0qQuwaZx/KXF8TePqqqqJq8r+Wkpc5szZ47BkZ6ysjKEhoZiyJAh8PDwMOlrTVWrkZaWhsGDB0OlUpl033Rrao6/5PgeSIvjLy2Ov3npzrw0haThxs/PD0qlEgUFBQbLCwoKEBQU1Og2QUFBRq3v6OgIR0fHBstVKpXZPnzm3DfdGsdfenwPpMXxlxbH3zyMGVNJu6UcHBzQs2dPpKen65dptVqkp6cjNja20W1iY2MN1gfqDwHeaH0iIiKyLZKflkpKSsLEiRPRq1cv9O7dG4sWLUJlZaW+eyohIQEhISGYP38+AGDGjBno168f3n33Xdx///1Yt24d9u3bh48//ljKH4OIiIgshOThZsyYMbh06RKSk5ORn5+P7t27Y9u2bfpJw3l5ebCz+/MA0z333IMvvvgCr776Kl555RVERkZiy5Yt6NKli1Q/AhEREVkQycMNAEyfPh3Tp09v9LnMzMwGy/72t7/hb3/7m5mrIiIiImsk+RWKiYiIiEyJ4YaIiIhkheGGiIiIZIXhhoiIiGSF4YaIiIhkheGGiIiIZIXhhoiIiGSF4YaIiIhkheGGiIiIZMUirlDckoQQAIy7dXpTqdVqVFVVoaysjHeElQDHX3p8D6TF8ZcWx9+8dH+3dX/Hb8bmwk15eTkAIDQ0VOJKiIiIyFjl5eXw9PS86ToK0ZQIJCNarRYXLlyAu7s7FAqFSfddVlaG0NBQnD17Fh4eHibdN90ax196fA+kxfGXFsffvIQQKC8vR6tWrQxuqN0YmztyY2dnh9atW5v1NTw8PPjBlhDHX3p8D6TF8ZcWx998bnXERocTiomIiEhWGG6IiIhIVhhuTMjR0REpKSlwdHSUuhSbxPGXHt8DaXH8pcXxtxw2N6GYiIiI5I1HboiIiEhWGG6IiIhIVhhuiIiISFYYboiIiEhWGG5MZMmSJQgLC4OTkxNiYmKwZ88eqUuyGa+99hoUCoXBv44dO0pdlmzt3LkTI0aMQKtWraBQKLBlyxaD54UQSE5ORnBwMJydnREXF4ecnBxpipWpW70HkyZNavCdGDp0qDTFysz8+fNx1113wd3dHQEBARg1ahSys7MN1qmursa0adPg6+sLNzc3PPLIIygoKJCoYtvEcGMC69evR1JSElJSUnDgwAF069YN8fHxKCwslLo0m9G5c2dcvHhR/++nn36SuiTZqqysRLdu3bBkyZJGn3/nnXewePFiLF++HL/++itcXV0RHx+P6urqFq5Uvm71HgDA0KFDDb4TX375ZQtWKF9ZWVmYNm0afvnlF6SlpUGtVmPIkCGorKzUrzNr1ix888032LhxI7KysnDhwgU8/PDDElZtgwTdtt69e4tp06bpH2s0GtGqVSsxf/58CauyHSkpKaJbt25Sl2GTAIivvvpK/1ir1YqgoCDxj3/8Q7+stLRUODo6ii+//FKCCuXvr++BEEJMnDhRPPjgg5LUY2sKCwsFAJGVlSWEqP+8q1QqsXHjRv06f/zxhwAgdu/eLVWZNodHbm5TbW0t9u/fj7i4OP0yOzs7xMXFYffu3RJWZltycnLQqlUrtGvXDuPHj0deXp7UJdmk06dPIz8/3+D74OnpiZiYGH4fWlhmZiYCAgLQoUMHPPPMMyguLpa6JFm6cuUKAMDHxwcAsH//fqjVaoPvQMeOHdGmTRt+B1oQw81tKioqgkajQWBgoMHywMBA5OfnS1SVbYmJicHq1auxbds2LFu2DKdPn0bfvn1RXl4udWk2R/eZ5/dBWkOHDsWaNWuQnp6OBQsWICsrC8OGDYNGo5G6NFnRarWYOXMm7r33XnTp0gVA/XfAwcEBXl5eBuvyO9CybO6u4CQ/w4YN0///rl27IiYmBm3btsWGDRswZcoUCSsjksbYsWP1/z86Ohpdu3ZF+/btkZmZiUGDBklYmbxMmzYNR44c4Rw/C8QjN7fJz88PSqWywUz4goICBAUFSVSVbfPy8kJUVBROnDghdSk2R/eZ5/fBsrRr1w5+fn78TpjQ9OnT8e233yIjIwOtW7fWLw8KCkJtbS1KS0sN1ud3oGUx3NwmBwcH9OzZE+np6fplWq0W6enpiI2NlbAy21VRUYGTJ08iODhY6lJsTnh4OIKCggy+D2VlZfj111/5fZDQuXPnUFxczO+ECQghMH36dHz11VfYsWMHwsPDDZ7v2bMnVCqVwXcgOzsbeXl5/A60IJ6WMoGkpCRMnDgRvXr1Qu/evbFo0SJUVlYiMTFR6tJswgsvvIARI0agbdu2uHDhAlJSUqBUKjFu3DipS5OliooKgyMAp0+fxsGDB+Hj44M2bdpg5syZeOONNxAZGYnw8HDMnTsXrVq1wqhRo6QrWmZu9h74+PggNTUVjzzyCIKCgnDy5Em89NJLiIiIQHx8vIRVy8O0adPwxRdf4D//+Q/c3d3182g8PT3h7OwMT09PTJkyBUlJSfDx8YGHhweee+45xMbG4u6775a4ehsidbuWXHzwwQeiTZs2wsHBQfTu3Vv88ssvUpdkM8aMGSOCg4OFg4ODCAkJEWPGjBEnTpyQuizZysjIEAAa/Js4caIQor4dfO7cuSIwMFA4OjqKQYMGiezsbGmLlpmbvQdVVVViyJAhwt/fX6hUKtG2bVsxdepUkZ+fL3XZstDYuAMQq1at0q9z9epV8eyzzwpvb2/h4uIiHnroIXHx4kXpirZBCiGEaPlIRURERGQenHNDREREssJwQ0RERLLCcENERESywnBDREREssJwQ0RERLLCcENERESywnBDREREssJwQ0RERLLCcENEkps0aZKkt2eYMGEC3nrrrSatO3bsWLz77rtmroiIbgevUExEZqVQKG76fEpKCmbNmgUhBLy8vFqmqOscOnQIAwcOxJkzZ+Dm5nbL9Y8cOYL77rsPp0+fhqenZwtUSETGYrghIrPS3VgQANavX4/k5GRkZ2frl7m5uTUpVJjLE088AXt7eyxfvrzJ29x1112YNGkSpk2bZsbKiKi5eFqKiMwqKChI/8/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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "time, deployment_level, drag_coefficient = zip(\n", + " *test_flight.get_controller_observed_variables\n", + ")\n", + "\n", + "# plot deployment level by time\n", + "plt.plot(time, deployment_level)\n", + "plt.xlabel(\"Time (s)\")\n", + "plt.ylabel(\"Deployment Level\")\n", + "plt.title(\"Deployment Level by Time\")\n", + "plt.grid()\n", + "plt.show()\n", + "\n", + "# plot drag coefficient by time\n", + "plt.plot(time, drag_coefficient)\n", + "plt.xlabel(\"Time (s)\")\n", + "plt.ylabel(\"Drag Coefficient\")\n", + "plt.title(\"Drag Coefficient by Time\")\n", + "plt.grid()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And of course, the simulation results:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Burn out State\n", + "\n", + "Burn out time: 3.900 s\n", + "Altitude at burn out: 658.678 m (AGL)\n", + "Rocket velocity at burn out: 279.367 m/s\n", + "Freestream velocity at burn out: 279.392 m/s\n", + "Mach Number at burn out: 0.842\n", + "Kinetic energy at burn out: 6.338e+05 J\n", + "\n", + "Apogee State\n", + "\n", + "Apogee Altitude: 4413.436 m (ASL) | 3013.436 m (AGL)\n", + "Apogee Time: 23.416 s\n", + "Apogee Freestream Speed: 11.706 m/s\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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BEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiAIgiAIgkiARDJBEARBEARBJEAimSAIgiAIgiASIJFMEARBEARBEAmQSCYIgiAIgiCIBEgkEwRBEARBEEQCJJIJgiAIgiAIIgESyQRBEARBEASRAIlkgiCIXoIoiuB5HqIoqh0KQRBEn0endgAEQRBEW0RRlEWxIAjgeR6xWAyiKMJgMECj0YDjOGg0Gvn/OY5TO2yCIIg+A4lkgiAIBhAEQRbDkiAWBEEWywBkQSyKovw7pTCWfq8UzSScCYIgugcn0ns7giCIrJIoiKV/SkEsZYkThS7HcdDr9fLP0vbK/5JwJgiC6DmUSSYIgsggUslEMkEs/V5ZNgGgSyJW2lb5N8rvlsS4cjtlqQYJZ4IgiOSQSCYIgkgTyhriWCzWYYa4O4I4VToTzjzPt9mehDNBEEQ8JJIJgiC6QeKkOuXEOmXJA8dx0Gq18v+rRXeFc6JoJuFMEER/gWqSCYIgOkFZtqD8lzh5ThKW0v9ngsSa5HSTWOOc2DYJZ4Ig+gskkgmCIBQkE8SNjY0QRREOhwMA2gjETIrESCQCr9cLj8eDYOMB8I07EHCNhMPhgNPphNPphMPhkLPVmaA94VxTU4OcnBxYrVYSzgRB9Dmo3IIgiH6LUhAr64gFQZB/z3EcGhoaAAC5ubkZFX/RaBRer1cWxV6vF5GAB5X+9ahs/AL25s2IuQah9sT34Ha70djYiJ07dyISicBms8mi2el0wm63y1ntntJeqcbOnTsxYsQImEwmufZaEsjKjHOms+sEQRCZgEQyQRD9AkkQKxfmSCaIk1mvcRzXxlqtp8RiMfh8PlkMezweBINBmEwm2O12OGwWjPB+g5xtC6EJNMh/p9EbUZiXg8LCQjnuUCgEj8cDt9uNuro6bNu2DbFYDHa7PS7bbLPZMiKcpe9MrHGOxWLyNiScCYLobZBIJgiiz5EoiJWLc0i/b08QZwKe5+Hz+eIyxH6/HwaDAQ6HA3a7HcXFxbDb7TAYDAAALtAI6wcvgIt4IdhKED3mekRHXwE4B0KvPVKTzHEczGYzzGYzioqK5P0LBoNwu91wu904cOAANm/eLJeMSKLZ6XTCarX2aN8TPZwTP1MKZ0k0S9uQcCYIgmVIJBME0atpTxArbdeA9hfnSAUpk5wKgiDA7/fHZYj9fj90Ol1rhtjhQEFBARwOB4xGY/v7ZclD+JT7AFFA9JjrAO1h8ZxivBaLBRaLBSUlJa3fJ4rw+/2ycN63bx+qqqrAcVxcfbPT6YTZbE6bUO2JcKbltgmCUBMSyQRB9Bok4ausIZYEsSAIcYJMKYozGU8gEIgTxD6fDxzHyYK4srISdrsdJpOp41hCbpg+ugvRCXeALz0RABA99qa0xcpxHGw2G2w2GwYOHAigVdD7fD643W54PB7s2rULXq8XOp2ujXA2Go1ZF87S75WZZhLOBEFkCxLJBEEwSaIgDoVCshCWyiaUTgo6nU4VQSyKIux2O+x2O0pLS2G322GxWLq2ap57H8z/ug7a5h3QHqqC/5av5MxxJtFoNHA4HLJrB3CkNETKOG/btg0+nw8GgyFONDscjpSz66mQKJyV3y1Z7Sl/z/M8NBoNDAYDCWeCIDICWcARBKE6iYJYWUMs/W7Dhg0oKipCSUlJxgWRKIoIh8OyIK6rq0M4HAYA2Gw2uY7Y4XDAYrH0aDIc17QTlsVXQeOrgWArQfCSv0IoGtv+9hn2SU5GLBaD1+uVhbPb7UYgEADHcXC5XMjPz5fFczY8nAHgxx9/hN1uR2VlJWWcCYLICJRJJggi67Q3qU5ZR9zeMsnpcmdQEg6H4ybVeTwexGIxWK1W2O12mM1m2O12HHXUUWltX9NQDfPiX0ATOAQ+dxiCV/4fRFtx2r4/Xeh0OuTk5CAnJ0f+LBqN4uuvv4bVaoXH48H+/fsRDAZhsVjaeDjrdOm51SQKXuXy3lLJTaILSbL6ZhLOBEGkAolkgiAySqIglv4pa1ATs3+ZJBqNxolhr9eLcDgsi7vc3FxUVlbCZrPJC3Rs375dfr2fLjj3PpiXXNMqkAtGI3jFWxAt+Wn7/kyj1+uh1WpRUlKCvLw8AK0Ln0j1zc3Nzdi9ezfC4bCcfVd6OKdr8ZPO6pulcy9ZvToJZ4IgOoJEMkEQaSNxUl1nghhI3e6rOyJGKhNQiuJQKASTyQSHwwGXy4WysjLY7fa0ZTtTxfDdn6Dx14HPG4HAlf8EzDmd/xHjGAwGFBQUoKCgQP5M6eF86NAhbN++HbFYLG7xE6l8JdOLn0j/lc7TRK/nZG8uCILov5BIJgiiWySrIZYEsXKSFcdxctawp6KjoykU0oQzj8cji+JAIACj0SiLsJKSEjgcji7XzWZCLIXP+n+AzoTI8b/sEwK5PUwmE0wmU9ziJ8FgUBbONTU1qK6uhiAI8uInUtbZZrO12/ddXdylM+HM83yb7ZNlm0k4E0T/gUQyQRCdkiiIE72IlQIkXYI4EeX3SdZlkhiWFueQrMvsdjuKiopgt9s79CJWFZ0R4bMeUzuKrKP0cC4ubq2/lpxDEhc/ASC7b0hZ5646h3QWi/K/UizSf6VzXbk9CWeC6D+QSCYIIg5lHafyX0NDA3w+H8rKytKeIe4IQRAQCAQQCoVQW1uLgwcPwufzQavVxnkRS4tzsCxY9D+8Cs5Xj8gp9wGa9NTkqkm6zJE4joPVaoXVasWAAQMAHFmURapx3rNnDzweD7RaLRwOB0KhELRaLQKBQFYXP5Guhw0bNmD48OEwmUwknAmij0IimSD6Me0J4kRfWo7jZAeITFt8BQKBuDpir9crx2AwGGQv4nQKo1Rj6wnavd/AuPwxcCIPofgYxIZPTVNk6pKpY6DRaGT/aQlBEGQrup07d6KxsRE1NTXQ6XRtPJxNJlPaYkkmnGtrazFkyBDKOBNEH4ZEMkH0E5SCWDmxTlqYQyqbaG/55nTf4EVRlCd1KUWxKIqyG8KAAQNkL+KffvoJeXl5KCoqSmsc2YALNML04a/AiTyioy9HbNgFaofUK9FoNLIQbmhoQF5eHkpLS+M8nGtra+H3+2E0GuNEs9PphMGQ3gValBNQgeQZ58TrSjlBEMjsWxiCIHoGiWSC6INIgjhxUl2qgjgZPbmZS4tzJDpN8DwPm80Gu92O4uJiDBs2DFarNanLQa8VE6II08d3tzpZ5A5D6Jw/AL11XxhEq9XC5XLB5XLJn8ViMXlioFTjLJVlKEVzdyZxdkQqpRrKJbdJOBME25BIJoheTqIgTpxU1x1B3FFbqRCJRNpkiCORiLw4R35+PgYPHgyr1dolv1y1FgjtiWjR//h36HYug6g1IDR1PqA3pzGy/ktH7hY6nQ65ubnIzc2VP5POSUk47927F6FQCBaLJa5UI1U7wFTdNToTzpJolrYh4UwQ7EAimSB6EUqP12SCWCJRFKcDjuOSitRoNNomQywtzmG325GTk4OKigrYbLasexGrjaZxK4xfzgUAhE97AELhaJUjSi9qPbR0B4PBgPz8fOTnH1mwRVp63O12o7GxETt37kQkEonzcJaEc7Kyiu6SqnBO9HGm5bYJIrv0rzsWQfQilIJYcngQBAFarVYum0hcrjnTN05RFNHc3CxPqPN4PAgGgzCZTLLTxMCBA2G329M+wU9tUdAdYaRpqAagQazyDESPvTX9QTGA2selJxiNxrjFT6SyICnbXFdXh23btiEWi8V5ODscDgDp3feuCudIJAK9Xg+DwUDCmSAyBIlkgmCAREEsZYilMgoA2Lp1K0wmEwYNGgSdTpfxG6K0OIckhpuamhCJRFBVVSV7ERcXF8Nut6d9QlRfITbiIviLjgZ0RqpDTjOZyGJzHCcvfiJNEJUWP5GE88GDB7FlyxYAwA8//ACXyyVnnK1Wa0aFs3Kf169fj7KyMhQXF8u/V5ZokHAmiJ5DIpkgsowkiBNriCXbNelGKN3kJEGcWKOYTiRPWmXJhLQ4h5QhLiwshMfjwYQJE9Lefqr0ptf7EqKrQu0Q+izZEIDKxU9KSkoAtD5ALlu2DAMHDkQgEMC+fftQVVUFjuPiFj5xOp0Z8XAGWq8FrVYrjwfSmJJYK51Y30zCmSBSh0QyQWSYxEl1SmsopRex8maWjPZqgruKKIrw+/1xdcQ+n0++wdvtdlRWVsJut8NkMsnx1NbWwufz9bj97tJrbuyiCOOyexEbdRn4sklqR9NnUfOBSToXS0pK5LcoylUg3W43du3aBa/XK68CmejhnK3FT6SxJ5lwTvRxJggiHhLJBJFGOhLEwJEZ8Up/1VRvTt25iUmvipUZYp/PB1EU5QxxaWkpHA5HShmv3pjJTQdd6XvdpiUwbPg/6Df/B747vgfMORmMrH+jlrBLdh1oNBq5Xrm0tBRA/OInbrcb27Ztg8/ng8FgaOPh3NXl0zty1+iqcE7mqkHCmSBIJBNEt1HWEEs+xOkSxB212dHvQqFQm9XqJC9ih8OBkpISeXGOTJRtZBrmRXrYA+NXjwMAIpPm9HmBzPzxUBnl4icSsVgsTjjX1NTA7/fDZDLFiWan09nh5NdULegkOhPO0niW6KiRWKZBwpnoT5BIJogUSJxUl8x6TbqBSL6/6b6ZJH5fssU5YrGY7EVcWFiIIUOGwGazpUUQp6vco7eSyr4bVz4HTaABfM4QRMbfloWo1Kc/iiblNd9VdDodcnJykJNz5AEqGo3C4/HIpRr79+9HMBiExWJpU6qRThvFVBY/Sdyeltsm+hMkkgkigWSC2O12w+PxoKioKO7GkilBnEg0GkUoFEI0GsVPP/0Er9crexE7HA7k5uaisrISNputS4tzdAW1b4Rqt98ZmoYt0K97HQAQPmsuoCXHj0zCwgNbus5JvV6PvLw85OXlyZ9FIhF53Glubsbu3bsRDodhtVrhdDoRDofh9/vB83xar/lUhLM0Pu7atQuDBg2CXq8n4Uz0SUgkE/2aRJcJ5Q1AmS3y+/2ora3FwIEDMz74S69jlRniUCgEnU4HvV6PgoIClJWVpbwyWDpRW5io3X67iCKMnz8ETuQRHXoe+MrT1Y6oX8BSTXK6MRgMcR7OABAKheRsM8/z2LFjB7Zu3SovfiJlnRMXP+kpyYSz1H55eTk0Gk1c1pkyzkRfgUQy0W9IVRAns0rSarVdrgFMBZ7n4xbm8Hq9CAQCMBqNstPEgAEDYLfbsWfPHgiCgPLy8rTGQPQc7e7l0O1bCVFnRPiMh9UOp1/A7ANTBpE8nAsLC1FbW4uRI0fCZrPFLX6ydetW8DwvC2bpvzabLSMiNdGGTvqvco5GRxMDSTgTLEMimeiTSIJYuTCHJIil37cniJORjnpcpUWU0otYr9fLgrioqAgOh6PdxTlYsL3qr+13BF95OoJTXwIXaoboLFM7nH6D2plkNc9JURSh0WhgNpthNptRXFwsfx4IBGThfODAAWzevBkAZPcNqcbZYrF0ex+S9UEqpRrKlQMThXO6JjgTRLogkUz0etItiJPR1e2lZaQTrde0Wq1svTZ48GDY7XYYjcaUvp+FG4fa2Tu12u+07zkNYiN/lp1gGCITb1d6E2qL5GRwHAer1Qqr1YoBAwbI2/p8PrnGec+ePfB4PNBqtW0mBqa6+EmqDwqdCWdJNEvbkHAmWIJEMtGrSBTEiS4T6RDEHbXd3ufJBDHHcbDb7bDb7SgvL4fdbu/R6ltqu0vQTSoJEX/rfw1WdeMgsoraD4sSXfFYl8YiCenNlpRx3rFjB3w+H3Q6XdyKgdLiJ4n0JJtOwpnoLZBIJphF6d2ZKIgFQUhqhJ+pQVMSqJIXsVIQe71eiKIoexEPHDhQ9iJOdzxq35z7s0hPtu+G7/4M/cZ/InzWY4iNuFCFqPov/T2L3dP9Vy5+UlbWWiIkzZFQ1jj7fD4YjcY2Hs7pHgtSFc7S75WCmZbbJjIFiWSCCZSCWLk4hyAI2LdvH7RaLUpKSuSBUKfTZXxAFEVR9iKur69HKBTCihUr5MU57HY7iouLMWzYMFit1owvzqH2DUDt9gH1HxKUcN6DMPzwCrhYGNC2v+gD0fdgpSY53Wi1WrhcLrhcLvmzWCwmO2p4PB4cPHhQnlwMALt27ZIFdEeLn3SHROGs3GdpwvXmzZtRXFyM3NxcEs5E2iGRTGSdREEsZYilQU8aCKVBLhQKQa/XZ9zuLBKJtMkQRyIRWK1WGI1GaLVaHHPMMbBarRnzIu4MtUWi2u2zhGHls+BiYcQGnojYkMlqh9PvoHMxOyJdp9MhNzcXubm58mfRaBT19fXYsGED3G439u7di1AoBIvFEleqkW6bymSTBD0eD/Lz88FxXBunIoAyzkTPIJFMZBRJ9CbWELcniJOVTGSiFjcajbbxIpYW57Db7cjNzUVFRQXsdju0Wi2am5uxefNmOByOtMbRFdQe2NVunyW45p3QVy0GAIRPewDop32jtlDt7+4WarWv1+vhcrmg0Whw7LHHAmhdAVTKODc2NmLnzp2IRCKyh7OUbZbG1HQhuXwoxa+yTEO61yj7KrG+mYQz0R4kkom0kjipTumVqbyxKAepzuipSJYW51CK4mAwCJPJJDtNSHXE7WU91J40J8FCDGqh5k0ssW3jty+AEwXEBp8DYcB4laJig/4oLli4DtWOIVF4Go3GuMVPpHI1ZX3ztm3bEIvF5HFXEs82m63b5WrJHhY6q2+W7lHJhHOijzPRvyGRTHSbjgQxcGTwkgYeoPszoVO9IfA8D5/PFyeI/X4/DAaDnMUoKSmB3W5v14u4pzFkChZi6O/tA4CmcTt0m98FAIRPukvlaAi1YEFAqZ3J7giO4+TFT4qKiuS/CQaDsnCuqanBli1bIIoi7HZ7XKmG1WrtkhVdZ3RVOCdz1SDh3P8gkUykRLJJdR1liKWf04FUa5aIIAjw+/3weDxxglin08mZioKCAjgcDnmSSU9iUBu1Y1BbpKu9/9K+a/csBycKiA6ZAqHoaFVj6s+Qu4X6+98dv3mLxQKLxYKSkhIArfshjeNutxv79u1DVVUVOI5r4+GczDFIKrfoSfztCWfpvqfcLlmZhtrHgcgcJJKJNiROqkv0IlYOGFJtWSYHCUkkJ2aIJS9iKUNcWVkJu90Ok8mUkXhYyGKyEEN/J3rcbeBLJ0HUtfWOJfoHLAhUtceCdPUBx3Gw2Wyw2Wzy4idSAkTKOO/atQterxdarTZONDudzqQJlJ7Go/wv0HbVwMTtabntvguJ5H5OR4K4rq4OLS0tGDFiRNYEsRRTMBiUxXB9fT0ikQjq6urkDHFpaWmXVofqKWpnUaUY1G5f7T5Qu30JofAotUMgVISV81DtcotMta/RaOTFT0pLSwG0Cmelh7O0+Ikoiti2bRuamppkAd3TN4eJpCKcv/zyS4wfP16+J5Fw7huQSO5HJLpMSP8SbXOkCxxonfSWSes1aXEOZYbY6/WC53l5kLTb7RBFEWPHjs24F3F7sCAQWYihv8JxHIyBWnBuJ0RnmdrhMIOaGVW1s7lqCx619z/b7Ws0GlkES/A8j+XLl8PpdCIYDKK2thZ+vx8mkyku2+xwOLo0ByUVEoVzMBiU75/KRbCU25Nw7n2QSO6jdFUQJ7tY26sF7gmSTZBSFMdiMVitVtjtdhQWFmLo0KFxi3Ps3r0bgUBANYEMqH9DlOjPNcFqt1++7XVYv1mJ8DlPIDr2alVjIQi1H5jVFulA6+InHMdhwIABsniOxWLywidutxv79+9HMBiE2Wxus9x2uhJAUilisntpYsZZmsvT0cRAtfuVOAKJ5D6AJIiVC3NIglj6fWeCOBk9zVxGIpE2XsTS4hx2ux35+fkYNGgQbDZbh76ZrGRQ1Y6BhYFT7T5QC4N3H/JqV4CDAL74GLXDIaDuuciCQATUL7dggcRjodPpkJeXh7y8PPmzSCQiC+fm5mbs3r0b4XAYVqu1Tca5Ox7OHflmp1KqoVxyO1E4p3siPNE1SCT3MhIFsXJxDun33RHEyeiKOJW8iJWCOBQKwWw2w263w+VyoaysrFsrMLEgklmIAejfmWRAvf3Pr34THATEBp8NoWC0KjEQbWHhnFQLtYW62u13JQ6DwRDn4QwAoVBIzjY3NDRgx44diMVi8uInknC22+2dvsXs6uIynQlnSTRL25BwVg8SyQzTniBW2q4BSIsgToZGo0kqSnieb7M4RyAQgNFolJ0mBgwYALvdDr1e3+M4WBCoFEMr/VGkc94aOHf/DwAQOWGmKjEQbKG2QFR7HJBgQaR191hIHs6FhYXy94RCobjFT7Zu3Qqe5+FwOOLs6JTlgNLfAj3rDxLObEIimRGUnoySF7EkiAVBiLuAlKI4k0g1yUofYo/HIy/OITlNFBUVZWRihBK1bwpSX6t5c1R78FO7fbUwrP0LNGIM7pwx0Aw8XrU4pNXLvF4vDAYDXC4XnE5nRifWdoba12V/R22hzsKYkK5zkOM4mM1mmM1mFBcXy98dCATkUo0DBw5g8+bNABC3+InFYpG/I52kKpyl3ysFMy23nR5IJKtAoiBWlkwIgoCNGzdi4MCByMvLA8dx0Ol0WTnRJW9KSQw3NzcjGAxi/fr1coZ48ODBsNvtMBqNWbv4WMigsjLQqN0P/a79YDP0Py0CABwYdBWy5Wshva2RXgd7PB6Ew2HYbDY4HA6Ew2Hs27cPoVAINptNFswulws2my2r52t/dLdQWyCmI3OZjhhYGBd7sphIZ3AcB6vVCqvVKns4i6IIn88nX5t79uyB1+sFAKxdu1a+FjNlUZoonJVjoiAI2Lp1K3Q6HQYPHgyAhHNPIZGcYToSxMqyCenk1el08uzX7kwg6EpcgUAgLkMsLc6hXK3u0KFDmDhxoupWS2qLMwnKJKvbfrbPA23dTwCAoGs4WvLGZ0QkK69F6Z/P54Ner5df85aWlsr1/BzHyWVM0uvhlpYWeYlfAHKGy+VyweVypd03lmADEsnZf3CW7pF2ux0DBw4EAAQCAXz11VcoKSmBx+PBzp074fV6odPp2ix+YjKldxEi5THgOA7RaFR2/QDQxtEKIOHcFUgkp5n2JtUlE8TtlUykWwxIi3MkehGLoihnpgYOHNhm2c+mpiY0NDSofvGwIJKTPbWrgdrt9zf4ytPhu/071O/4ERDTcx1Eo9G4DLHH44EgCPLDaXl5ubwgQmfXnlRXWVRUBOBIlqulpQUtLS3Ytm0bfD4fTCaTLJh7MoufJfqzuwUL44DafSDFAEBVe1DgyP2hrKxM/n/pbZCyxtnn88lzd5R2dOksVVRa0SljU5ZpSJpEefwkwUzLbcdDIrkHJApipQei8slNeeKlQk9EoSiKCIfDsiCWRDHP87IgLi4uxrBhw9pMPkhnHOmEhThYGCxY6Id+2b45B2HnEKClpct/Ki2nLl2Lbrdb9mx1OBzIz8/H4MGDYbPZ0nKjV2a5yspa896Sb2xLSwsaGxuxc+dORKNR2XVGEs7KB+TeQm+LN12wUG7BAmqPRxJKVykJrVYrX18SsVgsbiw4ePAgAoGAvPiJMuvc3Unv7T28dFbfLGkZEs7xkEhOEaUReKIgln6vFMRA9wcwjUaT8iIekUikzeIckhexVDIxZMiQbt2EWRBlrMTBQiZZ7cFJ7fazihCDpvZHCCXHASkee+kBVZkh9nq90Gg0ctmENMk1Ha4vqZLoGyu9WZKE8549e+DxeKDT6eJqm51OZ1bj7E2wkEUFqNyClUxyqn2h0+mQm5uL3Nxc+TPlmyW32429e/ciFArBYrHEieZUFz9RTvTvjK4K52SuGn1dOJNITkKiy0R7GWKO4+RXluk8SdoThdFotI0XcTgchsVigd1uR25uLioqKmC329PyKpUFccpSHID6mYv+3H42B2Ldtv/B/MF0xAafg+ClbyTdRvIGV4riaDQqv7EZMGBAmxImFuA4DhaLBRaLBSUlJQAgu9i0tLTA7XbjwIEDCAaD8mILUkYs8WFb7fOxv8JCv7MkktWmJ32h1+vbLH4irUzrdrvR2NiIXbt2yRN3Ez2cE+/1PT0unQlnSTwrt08sIe1Lwrnfi+TESXWJXsTKEyYTgjgZHMeB53k0NzfHieJgMAiTyZR0Mk+m4mBhEGLhYqNMsvrtZw1RhGHNywAAvnDM4Y9a7ZYOHjwYN7lOqi90uVwoLy9P2wNqttFoNG1eDUciEVk0S56xoijK++t0Ovutw4TaApGFcgu1+0CKAWAjk5zOGIxGY9ziJ8q3VG63G4cOHcL27dsRi8XkuQxS1lkQhLT3R2fCmef5Ntv3leW2+61IfvPNN6HT6XD++ee3KWLPpiAGWgv8pbpFr9eL5uZmNDQ0wGg0yvWFJSUlsNvtGfUiToQlkax2HCxc3Cz0Q39oX3NwLbS16yFoDNjmOh1N69bB7XbL2ROHw4HKykp5cl1fxWAwoLCwMG6xBb/fL08K3LFjB0RRxHfffYecnJy4SYFqejf3J9QWyWrDQgxA10ocugPHcUkn6UplUx6PR3a34Xkefr8fPp8vbvGTdMeXinBWimdJOOt0OtUfarpCvx3JvvnmG2i1Wpx33nlZtUCRvIiVNYt+vx86nU72IpaeDIcOHZrxeDqC47iUa6MzHQcrgyErcaiB2g8KmWpfEIS4ia6V3z8JK4Ca/FPh56woLGx9ren3+3HMMcdkJIbeAMdxsNlssNlsKC0tBQB8/PHHGDFiBMLhMFpaWrB7925EIpE23s2ZuEmTu4W6qN0HUgwAG5nkbPdFsrIpURTx7bffwm63g+M47Nu3D1VVVeA4Ts42S//NRBlYKsK5t71p67ciWa/XIxKJZNyLWBLESi9irVYri+HKykrY7XaYTCb5xNq0aRMTJxIr4pSFOFgpt1C7H3p7+6J4ZOlZ5YOq9JCar/WhqHk1AMB1/gNw5I8AAOzfvx+BQKDH8fc1OI6TRTAQ378tLS3Yv38/Nm3aBI1GE1fbnC7bK7VFmlqwUG7BQvus9AMLDwzAkWxtbm6uvPiJlJiTSjV2794Nr9cLrVYbJ5olD+dMCmcWkm5dpd+KZIPBAJ/Pl7bvk159JDpNSNkXh8OBsrKylFbhYUEMsRQHoL44Y0Eks9B+byPRcsnj8SAWi8kTYEpLS+OuSeMXD4MTBcQqT4dwWCBLUN+3JbFPOK7t0r5Spl656EkgEJBn70vC2W63q54RTBVWRJGasNAHrFyTLPSFRGLph0ajkZNy0hsg5TXp8XiwY8cOeQGjROHcbknZnj2AyQQUFQF1dUAoBFRUtBuX0vigN9FvRbJer5fXPe8qUrYkcXEOnuflk3HAgAGw2+3des2o0WiYOJlYEckUx5H21UT5oKBGLJ21Kb25UWaJ/X6/PNk1NzcXlZWVsNlsyd/UiAK0+1YCACLj78jELvRJOjsuUhbZ6XSivLwcQOukQEk0S5OQeJ6Xb86ScO4os8XCmKAWLGRQWRCGyfyJ1YyDBVKZRKi8JiV4no9LJtTW1saNn0o7OuNPP0F/3nmAxYLYK69Ad/vtQCCA6EcfQZwwIdO7mFX6rUg2GAyIRqMpbSvZsShFcSwWk72ICwsLMXTo0E4X50gVtcWYhLQvag8ArPQHC4NgfxbpQPz+K22SpOsSgOz+Mnjw4K691uc0CFz3EbS7l4OvOC0T4ROHMRgMbWbvBwIB2U1j165d8Hq90Ov1bbyblZMC+7O7hdrXIysxsEAmHCW6S3eOiyiKaI40Y190Hxo1jWgwNeCowhE4QTMCnvp61DQcwLLNS6AJicirC+LnT/0ViEaBYBD6iy+GeDjpoD/vPETWru0wo9zb6LciWa/XJxXJkUikjRextDiH3W5Hfn4+Bg0a1H42Kg2wUrujduZQGQcrg6HaIpWFflDjfOB5HqFQCH6/Hxs3boTb7UY4HJYfVIuLizF8+PCeTxDTaMEPPrvNx2qLgb4Ox3GwWq2wWq0YOHAggCOZLclNY9++fQiFQvKkQJ7nEQgE4HQ66fiogNr3BSkGFsQpC30hkYrTBu/x4GDVd1i9/kO07NsGse4QnM0R5PhE2INASQgwR4ADh7e3AZh8+P+1sRgQ4wFBBIdW9wqO5yFoNOD1euw7dAi2w4kKFuZW9ZR+LZJ9Ph8++OADrF69GhMnToTT6UQoFJKXjHW5XCgrK8uoF3EyWBTJasehdgwsxKH2IJyt9hOtjaQJr5J9UEFBgbxQR7quS85bA9GSB2izZ7FIdIxWq0VOTg5ycnLkz5STAnmex8aNG1FVVdVmUmCmrfnUFkVqty/FoDYsxACwcTwklA8OoiAgunMnwhs3wrNpA6I7d4LbvR/8oUMAgHHd+H5ep8PB4hKUH9gf97lGELD38cdRz3HYtm5d3MJKUpmGzWbr4d5ln34jkv1+P9atW4c1a9Zg9erVWLZsGQ4dOoR169Zh9OjRmDhxIkaOHAm73a76UqxqizFlHID6AxFL/aF2HGq3nwmkZVmVpROCIMiT68rLy+FwOFBbW4tgMIjKysq0x2D6aA40jVsROv8F8BWnpv37ifSg9Io9cOAAjjvuOGg0Glk4b926FT6fD2azuc2kwL6Q1ZJgRZSpHQNlkuMRAkEYNm5E6NvvcHDbNoSrqiD6/al/gU4HrdMJjdMJjcMOrcMJzmwGp9OB0+tbfx8MonDhAogcB05xPxK1WlQ88ghKVq+GeNxxcS5C0mJERUVFOO644zKw55mjX4jkWbNm4aWXXkJhYSGOP/54TJgwAQ6HAxs3bsSHH36odnhtYEGMSXEA6gsz1vqjv7Yv0ZNjobQjkoRxIBCQ397k5+dj8ODBbZY/BjJ3Hmgat0G392uInAZCzqB2t2PhHGQNtftE8n+V3IOA1ocuye6qsbERO3bsQCwWazMpsDOXoY5gRRSpCQt9oPb5J6FWX4ixGMJVVQh++x2C332H0I8/ojAWQ7iDv9G4XDAMGQL94MHQl5VBV1IMXUkJdCUl0ObmguvsoWPPHmj+8jKg0UBEa6mFVJOMQAAIhdp1uemuWYKapF0kL1iwAAsWLMDu3bsBAEcddRQeeughnH/++QBaX5f95je/wdtvv41wOIwpU6bgpZdekleRAYC9e/di+vTp+OKLL2Cz2XDjjTfiySefjHu1unz5ctx1112oqqpCWVkZHnzwQdx0001JY5o1axbuv/9+DBgwQD6RX375ZWzatCndu58WNBoNlVskiYMF1C63ULv9riAtpZo4uU6j0cjCprCwEA6HI6srSSaiX/8GACA25FyIjlLV4iC6RnvXgl6vR35+PvLz8+XtgsGgPClwz5492LBhA3Q6XZtJgWq/RUwVVgQqCzH0t0yyEAgiuGoV/F98jsBXKyC43e1u22QDdpUZYB47FmNOugSlR5/UKoR7EmtFBaIffSS7W0QT3C3am7THcVyvXIkz7RGXlpbiD3/4A4YNGwZRFPG3v/0NF198MdatW4ejjjoKc+bMwdKlS7F48WI4nU7MnDkTl112Gb755hsArZM1pk6diuLiYqxcuRI1NTW44YYboNfr8cQTTwAAdu3ahalTp2LatGlYtGgRPvvsM9x2220oKSnBlClT2sQ0fPjwNp91xd0i26gthpRxAGyIZLVjYCUOtdvvKAZpopWydCIajcJqtcLpdMp1xN1d6SkjN6GwF/qqJQCA6Lib0//9/QC1J/Wmso20Mpm0wALP8/B6vfKkwAMHDiAYDMJqtcYJ52RvNAD1BaLa7bMUAwtk2t1CCAYRWL4cvo8/RnDVtxBDoaTb6crK8FOxiI8HHoR3+EBcMvFWXFRxHkw6U1rjESdMaHWxOOyTHFm9ulOf5N5K2kXyRRddFPfz448/jgULFuDbb79FaWkpXnvtNbz11ls466yzAACvv/46Ro0ahW+//RYTJ07EJ598gk2bNuHTTz9FUVERxo0bh8ceewz33XcfHnnkERgMBixcuBCDBg3Cs88+CwAYNWoUvv76a8ybNy+pSE4GieTU4gDUH4hY6w9q/4hlV+LkOoPBIE/SkBbqSGctaLrPA/2mJeCifvC5Q8GXn9zudmr3PZFetFqtXHYhEQ6H5drmuro6VFdXA4A8iVsSziZTegVHb4UVkax2DJmKQ+R5BL//Hr6lS+H/7HOISVb85KxWBI4bDt2JEzD4rEugHzgQP3z8H5xZIeBnw38GnSaDmVulIFZUAvQ1Mpr75nkeixcvht/vx6RJk7B27VpEo1Gcc8458jYjR45EeXk5Vq1ahYkTJ2LVqlUYO3ZsXPnFlClTMH36dFRVVeHYY4/FqlWr4r5D2mb27Nkpx8aySGZlMRGADYHKQgysxKFW+5FIBM3NzQCAn376CT6fD4IgwG63w+l0orKyEg6Ho3cJCFGEft0bAIDouJsABm62hHoYjUYUFhaisLAQQOu15vP5ZOG8fft2+Hw+mEwmGI1GhMNhNDc3q2J1xYo4VJu+WG4R3X8A3n/9C97//ld2oVCizcuD5YwzwJ86AX/mvsDHtZ9jTJ6Ivw6YDgCwcBacXHZyZgVyPyIjvbhhwwZMmjRJ9rR89913MXr0aKxfvx4GgyHu6R0AioqKUFtbCwCora2NE8jS76XfdbSNx+NBMBiE2WzuNEadTsesSGZBjEmwYkfHSn/0pprg7iIIgiwOpLIJyRoRAPLy8jBs2LC0LZ6TKunef03tOmibd0A02BA96opOt2flHCRaybRQ5DiuzXK+sVgMbrcb+/btg9/vx/r16xGJROSHRSnj3GO/7k5gQSSzEgML9LQvRJ5HYMUKeBYvRvCblUDCfmnsNljPPRe2qVNhPPZYfLj3f3hu3R/hiXig5bQ4Jv8YxIQYDFoDE8elL5ERkTxixAisX78ebrcbS5YswY033ogvv/wyE011G4PBgEgkonYYSWFFmAJsCHZa+S9z7UtLrCdOrtNqtXLZRHFxMRwOBzQaDb788kuUlJSoOtEuXQglx8F//SfQNG4FDL3Pv5MV+tMNWafTIS8vD+FwGOFwGCeccAJCoVDcgidVVVXy9aMUzn3hmlGi9ngsxdCbM8m8xwPv4iVwv/MO+MNJQBmdDpZTT4HtwgthOfVUaIxGtIRb8ODKe/HlgVY9Ndw1HA+d8BBG5o6U42DhuHQEy7ElIyMi2WAwYOjQoQCA8ePHY/Xq1XjhhRdw1VVXIRKJoKWlJS6bXFdXJ9uEFBcX4/vvv4/7vrq6Ovl30n+lz5TbOByOlLLIUoyxWIzJE0ptMaaEpVjUPlYs9EVP24/FYm0m18ViMdn0XaojTmaPxfN8j9pOB+nuf6FwNITC0Wn9zv5Cb78W0oHS6qqkpARA65sYaVKg2+1GTU0NAoEALBZLXG2z3W7vtsBTeyxkKQYW6GpfRA8cgHvRInj//S7EYDDud7oBJbBffjnsl1wC3WGHFgDY592HOz+/E/XBeug0Otw55k5cP/L6uLIKqT9YeHDoK2SlaEUQBITDYYwfPx56vR6fffYZLr/8cgBAdXU19u7di0mTJgEAJk2ahMcffxz19fVybdiyZcvgcDgwevRoeZtEf+Nly5bJ35EKrGeSWbn4WYiFpQmEval9URTbeBL7/X4YjUb5Rl1RUZHyEuu9bf87hI8C2t5h90W0j1rnZEeiSKPRyFlkiUgkItc2Hzp0CNu2bYMgCEknBaayT2qPhSzFwIIgTNXdIrx5C1reeAP+ZcsAZdKB42A59VQ4fn4lzCedBC7JeFxiLUGxpRgmnQlPTHpCzh4nxtH6dWwl/nozaRfJv/3tb3H++eejvLwcXq8Xb731FpYvX46PP/4YTqcTt956K+666y7k5ubC4XBg1qxZmDRpEiZOnAgAmDx5MkaPHo3rr78eTz/9NGpra/Hggw9ixowZ8lKj06ZNw4svvoh7770Xt9xyCz7//HO88847WLp0acpx6vV6Zo2taeJe2xgAdgZlVtuXPImlDLHX6wUAuV5y8ODBcDgcPV6yV+0+6DF8BNbXTgVfNgmhMx4GzDmd/w1B9ACDwYCCggIUFBQAiH+AbWlpwa5du+D1emV3GEk4O53Odr1l1RZCLAhUVsaizjLJ4c2b0bzwZQSWL4/7nDOZYL/4Z3Bedx305eVt/s4X9cGkNUGn0UGn0eHpU56GRWeBRW9pNw5A/XOjL5F2kVxfX48bbrgBNTU1cDqdOProo/Hxxx/j3HPPBQDMmzcPGo0Gl19+edxiIhJarRYffPABpk+fjkmTJsFqteLGG2/E3Llz5W0GDRqEpUuXYs6cOXjhhRdQWlqKV199NWX7N6BVJLM8cY9qkuNjANQfENXuC+XAx/N83OQ6j8eDUCgEq9UKh8OBoqIiDB8+PK0TiFgYeNPR/7ptH0HjPQDsXQEY7Sn9DQv7TrBDT0sNOI6DzWaDzWbDwIEDAbRe09JKgS0tLdi7dy9CoVCbSYE2m42JUgdA/euClX5oL47wli1oXrgQgS+Wx32uycmB8xe/gOOqn0Obk/whfbdnN36z4jc4dcCpmH3sbABAvjk/6bbKOAA2yy3Uvn93l7SL5Ndee63D35tMJsyfPx/z589vd5uKiopOl4s+44wzsG7dum7FCLBtAae2GFPCQiz9XSRLK4Y1NjZCFEWsXr0aPp8POp1OnlwnLdSRjRWN1DoO6boZ6n96EwAQHfMLgGySei2sCKR0odVqkZubi9zcXPkzaVKg2+3GgQMHsHnzZrkOOhqNor6+Hk6ns8dvh7oDC/3PQgzJ4ojs2IGmF+cj8PnncdtpCwvhuvUW2C+5BJoO7DK/rfkW96+8H76oD6G9Idxy1C1wGBydxkHlFumn394hSCSnBgulH6xc8NmKIxqNxk2u83g8iMVisFqtAICysjI4nc6U6xfTBSvHoSdwTTuh27cSIqdBdOw1Xfpbta8D1ujP/ZEtcWYymVBcXCxPWpfsGffv34+DBw+iuroafr8fZrM5rrZZcqPJJCwIVBZiUMYRO3QIzQsWwPvufwDF22BtQQFct94K+2WXQtPJA80Huz7AY98/Bl7kMS5/HJ465amUBLIUB9A3xmpW6LciWa/XMztxjwVhKsGCYGclk5yJGARBaDO5LhAIwGQywel0Ijc3F4MGDYLNZkM0GsU333yDoqIi1ZfE7a1tGzYsAgDwg86E6BiYjpD6PWpOnutvaDQaOBwOFBQUoKmpCaeccgqi0ahcotHY2IgdO3YgFou1mRSYzLGmJ7AgUFmIAQCEQAC6/36AfR9+GOdWoS0ogOuWW2C//LJOxbEoinh90+t4aUNr+en5FefjoRMegr4LE4yl/mChT5LBcmzt0W9FssHQarrN83xWXlF3BapJTo7acaSjLyRPYuXkOo7j4HA44HQ6UVhYCIfDkdRTVfmwoNZA09sGuDhiYeiqFgMAImOvVTkYIh2w6G6R7fb1ej3y8/ORf9guTLlkfEtLC/bs2YMNGzZAr9e3mRSo13ff4UXtPmAhBlEQ4P3Pf2B4/gVwbjekuwNntcJ16y1wXnMNNCna0j677lm8vfVtAMCNo27EjKNnQMN17W2AIAiqH5O+BlvqMItIIiQcDjMpktUWhBIsxCI9fbIQR1di4Hm+TdlEOByWPYlLSkowcuRIWCyWXjWw9daaZN22/0ETbIJgKwY/+Kw0RUUQbMFxHKxWK6xWKwYMGADgyFgkCef9+/cjGAzCZrPJwtnlcsFms6V8nak9HksxqDVJLbRhAxqf/APCVVWQe0yng+PKK5Fzx+3QKmrLU2FM3hhoOS3mHDsHvxj+i27FpPZDQ1+ELXWYRSSRzGJdMguCUIKVWFiIo6MYpOyNMkvs9/vl7I20UIfdbu/2QxkLZSe9eQDmy09G+JT7IRrtXZ6w15v3u6+idtkPK5nkVNBqtcjJyUGOwkkhHA7LormmpgZbtmwBALlMQ8o4m9qZYKZ2H0gxZBu+uRlNf/pTa92xon1x4okof+AB6CsquvW951Wch3H541BsLe52bCzY8vU1+q1Ill4zsSiSqSaZ3TgkIpFImyyxIAiw2+1wOByorKyUPYnTfSNRux/UFifd/ltrASInzkxjNASg7gOE2iJNLdIhUI1GIwoLC+VFu0RRhM/nk900tm3bBp/PB5PJ1GZSoLT4kNr9n01RKPI8PEuWoPnF+RA8Hvlz/ZAh8Fx1FYzjj+uSQI7wEbyw/gXcOOpGFFpaj0FPBDLAfrkFy7G1R78VyZJlDosimSVByFJ9tFp9Is0oD4fDOHDgAPbs2YNgMAiLxQKHw4H8/HwMGTIEVqs1owM2CwNMfxZErFyTrNCf+4OFLGq64TgOdrsddrsdZWVlAFqXsZeyzc3Nzdi1axei0Sjsdjui0Sg4joPf71etZCxb52B461Y0PPIowlVV8meczYbc6dPguOoqbDhszZcqET6Ce7+5F18f/Bo/HPoBb05+E1pN56uedkZfPC/Vpt+KZOlJmEWHC5aEKSuCPVtxiKLYZnKdz+eDRqOR/Umllet6MumlpzGqSa/LJMdCMC2dgdiIixEbfgF5IxO9nmyJIZ1Oh7y8POTl5cntBoNBuN1ubN26FS0tLfjmm2+g1WrbTApMNvk43WS6H4RwGC2vvIKW198AFCv02i66ELmzZ0N3eLJkVzK4MSGG3636Hb4++DWMWiN+Pe7XaRHIAJVbZIJ+e7fgOA4Gg4HJpalZEaYAO7FkKo5YLNambCIajcqT6wYOHAin0wmz2YwNGzYgNzdXvmFkG8oQdA/dtv9Bv/1jaOs2IDZ8qtrhEGlAbT9YtTN2arXPcRwsFgssFgsOHjyI/Px8lJWVwev1oqWlBS0tLTh48CACgQAsFktcbbPdbk+7gMtkPwR/+AENj85FdPdu+TP94MEo+P3vYTru2DZxpLJvgihg7vdz8cX+L6DX6PHcqc/hxOIT0xYz6+UWvZF+K5IBdr2SpYtN7YEY6FsiWRRF+P1+OUPs8Xjg9/thNBrlLEh5eTnsdrv8piHdMfSE/j5xr7ttyyvsjb0aSFPGhiCI1mtSo9HI2eOKwzW5kUhErm2uq6vD1q1bIQiCvJ1yUmBPxpRM3CMFvx9Nzz8PzzuLj3yo08F16y3Iue02cEky5KnEIYoi/rj2j/hw94fQclo8edKTaRXIUhssZ5LV1jPdoUsimQXRli44joNer2e2Jhlgo7/VFoY9iSMSicQt0uE5PNlCmlwnlU10ZUlXFvpC7Rh6U7kF17QTuv3fta6wN6Z7tkoEe7BwDfTHTHKqMRgMhjaTAv1+vyycd+zYAZ/PB4PB0GZSYFfcf9LdD8G1a3Howd8jdvCg/Jlx7FgUPPwwDMOG9iiONza/gcXbF4MDh0dPfBRnlJ6RrrC7FAfRNeSz8S9/+QsmT56MysrKpBuGw2G8/PLL+NWvfpWt2DIOq5lk6SQXBEH1p8LeIpJ5nofP54vLEodCIVitVjgcDhQWFmLo0KE9mlyndl+wMPixEENX0Ff9E8DhFfbsJd3+nt6239mAlXGhP8KCGOpKDBzHwWazwWazobS0FMCRUjfloifhcBh2uz1OOFut1nbbSVc/COEwmufPh/vv/5Bt3TizGbmzZsHxi6vAJXmz2NU4zq84Hx/t+QhXDbsK51We1+OYk0HlFulHFsm//OUv4XK58NZbb+Hss89u87o5EAhg9uzZmDZtWlYK8rNBb8gkq43awjBZHNLkkcTJdTqdDg6HAw6HAwMGDOhyVqIrMaiJ2jGo3X7KCDHoq5YAAKJjrurx1/Wa/c4y/fGmzIJIVZue9oFOp0Nubi5yFYtuhEIhubb5wIED2LRpk1zOoRTOkgZJx3EIb96C+t/9DtEdO+TPTMcdh4LH5kJ/WNB3RipxFFuL8ebkN7u0zHRXofMy/cgKwmg04qyzzsKll16KBx98EDNnzoTdbpc31Ov1sqgkkZxZSCTHE41GIQgCamtrsW/fPng8HsRiMblsoqysLC31bazDwnnRm2qStbu/hMZfB8Gci9jgczIUFUFkHxbEUCZiMJlMKC4uRnFxq1+wZL8pCefa2lr4/X6YzWa4XC6Ew2Ho9fpuvXUVeR4tr7+O5gULjzhX6PXInTUTzuuu6zR7rKS9DO5PDT+hPliPc8pax59MCmSA/Zrk3ohOOtGj0Sj++Mc/4he/+AVuueUWrFmzBs8//7zsl6jRaMDzPJOisjtI7hYs7o9y4p7aZHthE0EQ2kyuCwQC4DgOoVAIBQUFqKyszMhM6c5g4YFB7Rsj0ItqknUmxAaeAKH4GEDbNx7siVbI3YINkZxpNBqN/HawvLwcQGvSRKptbm5uRiQSwbJly9qsFGg2m9vto1hdHep/+wBCa9fKnxlGDEfh44/DMGxYl+NMJk73evdizldz4Il4oDtFl5Ea5ERYLrdQ+97ZXeRMsk6nQ3NzMy677DKMHTsWV1xxBc455xy89tprOOWUU2A0GqHRaJis4e0uvaEmWW0yLQylpVGVk+s4jpMHxqFDh8LhcGD9+vUoLy9H/mFfSjVgQSQD/TeT3FX48pMRLD8ZEPgef1dv2m+CyAZqCXW9Xo+CggIUFBQgEomA4ziUl5fLtc27du2C1+uFXq+XyzMk4azT6eBf/iUOPfQQBLe79Qs1GrhuuRk506aB66b3fWJfuMNu/PrLX8MdcWN07ui0u1h0FAfLmeTeOI7KmWQpUwwAw4YNw5o1a3DjjTdi6tSp+OMf/4irr74aWq2Wycxrd9Hr9Uz6JAPsCLJ0xsHzPLxeb1yWOBwOy57ExcXFGD58eNKJGiz0Bysx9Fe6ve9k+9bnUPs6VDuTq3b7EmrHIIoitFotrFYrrFYrBgwYAKD1XuPxeOSM8759+xD2+VDy6aewfbFc/nttcTGKnnyyje9xd+KQ+iImxPDblb/FPt8+lFhKMO+0eTDrzD36/u7EQaSHuEyyMquq0+nw1ltv4emnn8acOXOwceNGhMNhZkVld2A1kwywIch6EocoiggEAnGT6/x+P/R6vZwlLi0thd1uT3lyndr9wcLgw8J5wXy5hShCt/Gf4IdMhmjJ7Xz7XoJ04/d4PDAajXC5XLDb7aqWHAC9q069r8CCGGI5Bq1Wi5ycHOTk5AAAonv2oPaeexCt3ipv4xszBod+fiXqYlE4q6vljHNXLEGTxfH8+ufxfd33MOvMeO6055Bnyt7iUyyXW/RWZHWSWErBcRx4nse9996LY489FrNmzVIlwEzCak0ykP1a4PZIVZRFo9G4DLHH44EgCPLkuoqKCjidThiNxm5dxCyIQ0B9oa42rByHjtDUroP5k7shGh3wTfsB0JnUDqlbSKVIUjbM5/PJr5AFQUB1dTUAyDf3nJwcuFyutDq6EMlhQSCqDQt9kEoMvg8/xKHH/h/EQAAAwBkMyL37N6i88krZu7mlpQXbtm2Dz+eDyWSKK9FwOBxJF5dKFsd/dvwHb299GwAwd+JcDHN1vb65J7BebtEbkUfT0aNHt3Gt0Gq14Hke5557LpYtW4Z58+bBZOqdN5xksJ5JZqUmOTEOacaxUhQHg0GYzWY4HA7k5+dj8ODBsNlsabtgWRBnFIO6pHpD1m9s9UaODTk3rQI5k/0uTVh1u93yv1AoBJvNBqfTGefgotFo5Bn9Pp8Pzc3NsmVWKBSSfWYl0dzRBKbeCgtZbDXpLQJVzRjEaBSNzzwLz9tvy5/pKytR+PRTMI4YAaB1YSm73S4bFMRiMfnBtLGxETt37kQ0GpWvKUk4WyyWuHalDO5uz24AwJ1j7sSZpWdmaK/bh+VMMsdxzMbWETpJxHz99ddJN9BqtRBFEWVlZXjuueeyGVvGYdUCDmBLDEWjUdTV1ckZYq/XGzfruLi4GA6HA/puTnpIBRb6g4UYAJq41yHRIPRb3mv93zR4I2cK6WYs/ZNWg5Rm6JeUlHTq8628BqXlgCWf2ebmZuzZswcbNmyQVzWTRLPD4aBsUw9hQSCqDStjYbLjEKurQ9099yD840/yZ7afXYT83z4AjaX9+mCdToe8vDzk5eXJ3x8MBuW3OXv27IHH44FOp4vzbpbE6exjZ2Ni8UScUHxC+nc2Bei8TD8pvZdjaQW4dEIiuS2xWAxer1e+cTc3N4Pnefj9fjidTnmRjsQn6UzDgkBlJQa1YbkmWbdtKbiID4KzAnzpxCxF1TGiKCIUCsWJYum1rtPpREFBAYYOHQqbzdbj45voM8vzvGyV1djYiB07doDnefkGLwnnvuJ9319gQQyxGkNw9WrU33sf+KYmAK3lFXm/vR+Oyy7r8vdzHAeLxQKLxSJPChQEIW5S4N79exEKhrBhwwbk5uZigGsAfF5fWt+kpgqVW6SfLhWv9bXOZ7kmORuCTBRF2ZNY+ufz+WA0GuWMlvRa96ijjspoLJ3BgkAF1M+eqN0PrE/SkkotomN+DnDpG6+6st+CIMgPmtI/6ZWt0+lEZWWlXJ+fabRabdyqZtI1L5VobNmyBYFAAFarNU40d7QUsATLD0vZaJ/cLdR/aFf2gyiKcP/tb2j605+Bw05dupISFD37DIxpvH9pNBq59AIAnvnhGaxpXIP7h9wPM2dGXV0dtm7dCkEQ4HQ642zoMl2uynK5hdrXbHfp1zM8WM4kazSatNckRyKRNpPrRFGUX9kmu3nv3r0bfr8/rXF0B7XFISsxsACrfcC17IZu3yqI4BAdfWXW2o1EInGCWCpHkm6QZWVlsNvtnU7+yQYcx8Fms8Fms8l1mJFIRC7RkJYC1mq1caLZ6XS2Gz/rD05EZmBBqEsxCIEADv3+Ifg//VT+nXnSJBQ++QS0hx0uMsGyvcvkiXr1XD0mD5ssx6WcFLhjxw54vV7ZlUY5KTCdE21ZOCZ9jXaPjrTcY1/LHithWST3VJBJ2SylKA6FQrBYLHA4HCgsLMTQoUNhtVo7PMasCEMWLnwW+kLtGNQ+Dh3tu/bgWogaHfjykyE6BmSs/UAgECeKA4EALBYLnE4nSkpKMHLkyKyXI/UEg8GAwsJCFBYWAjjyOlnKNu/evRvRaFR+uyQJ5758b+gMtccBFsQQKzGgvh4H774HkW3b5M9dd9yBnGl3dmlp6a6y27Mbj33/GADgTPOZmFh0pLxL+TBaWloKoLWUUSrTkK6rSCQCm80mi+ZU3+K0B5VbpJ92RfIzzzyDCy64AMceeywTF0MmMBgMTLtbpDoQK2selZPrdDqdnCUeMGAA7HZ7lyfXqS3KWIqDlWtA7X5Qq/3O+j82+nL4K88Ewi1pa1PyJq6vr0cgEMCKFSsgCAIcDgecTieGDh0Kp9OZ0Umr2SbxdbJy8lJzc7OcFZNeHe/btw+5ublZ9Wxmwd2iv5dbqD0OAYB2SzWEhQsROTzxVWO3oeDxJ2A9/bSMthuMBXHvN/ciEAtgfOF4nB07u9PjodPp2pQ+SfftlpYW7N+/H5s2bZLfQikzzqnOGSCRnH7aFclvv/02Bg0a1KdFcm/NJEtPpEpRHIvFZLuo0tJSOByOtFg/sSBOWYpD7RjUvg7Vbr8zREsu0IMFRCRvYunGJXkTm0wmaLVaHH300apMyFGTZJOXotEoGhoa8OOPP6K+vh7bDmfxlJnmvuzZTGKkFTXHA8+//w37s8/K9cf68nIU/flPMFRWZrztp9Y8hZ3uncg35ePxSY/jhxU/dLkvOI6D2WyG2WyWJ9oq5zO0tLSgpqYm7k2VdF3Z7fak558gCMxec73WAq69XxgMBoRCoWzGknVYFslSTbLkn6qcXOf3+2EymeBwOJCbm4vKykrYbLaM1Dz2tkVN+noMgPpCnckJW8FmwNy12kNRFOHz+VLyJm5oaMCuXbvgcDjSsBe9H71eL9tkjR8/HhzHxXk279+/X/ZsVormvujZrAYsJK7UikGMxVr9j//v/yC1bp44EYV/fBraLFyfH+35CB/s/gAaToMnTnoC+eb8tD00KecylJeXAzgy56GlpQWHDh3C9u3bwfO8/DZLyjabzWZ6eMsA7YrkAQMGZGX2tZoYDAYEDq/CwwrhcFiuH969e7e8qpZUNjF48OAuvX7pKawIQ0B9cchCX6gdg9o35qREA7C9Ogl8wWiEfvYKREvyZWA78iaW6onbm0jD5H6rjLLkIduezWpfhyy0r/Y5qUYMvNuN+nvvRfDb7+TPtJdcjOLf/x5cljKogxyDUGGvwOTyyTiu8DgAme0Lg8GAgoICFBQUyG0FAgHZgm7Xrl3wer3Q6/VyLXRjYyOcTiezWeXeRLs9uHjxYrnOrq8+maidSeZ5Xp5cJ5VPhMNhWK1W2XWivLy8R4X8PUVtUcZSHGrflFiJQS3a23fdtv+Bi/ig8dVBNLet98u0NzGRnK54NiuzzV1JAPTXmmQWyLZIju7di9oZMxHdu7f1A50OnmuuRuHVV2dNIAPAiJwReHPKm9BrWvVRtuvjOY6D1WqF1WrFwIEDARyZO7Fp0yaEw2Fs2LBBfiumnBSo1ngniqLq9+/u0u6Z1ZeWn26PbIpkafKLso5YqndUTq6TMlnr16+H0+mEzWbLSnztwYI4ZSkOikH99hPRb/oXAMA75ELs37dPdW9iIjld8WxWimY1kwTtoXYmV+32sx1DaP161P56NoSWFgCAJicHxc89h7pwKGsxNIYakWdqfUtl1h1ZtY+FSaRarRY5OTmwWCzIyclBZWVl3KTAgwcPYsuWLQDQZlIgjYkd069z8UajMWPuFtFotM3kOkEQ5HrH8vJyOBwOmEympBcX1QKzFwcrMfTn9qX+lzy//TXbcNSeFQCAtdGhMDQ3x01eTWedvtrHvq/RE89mFoSJmrAikrOB75NPcOh3D0I8fK/WDxmC4hf/DP2AARBXrsxKP6ytX4tfffkrTBs7DdeNuC6uTWk9A7WPBxC/mIjJZILJZEJRUZH8O5/PJ5dpbN26FT6fD2azOa62Od3jZm+nX4tknU6HWCzW4++RTj7l5LpAIACz2QyHw4G8vDwMHjy4S7PiOY5L+2Ii3YEFYchKHBRDK9luX6rBa2pqQjgcxrfffivP+B7R8DE4iIgUj8eEc69g4kZFdJ9UPZulN2y1tbVZWcksEbWvQRbItFAXRRHuN95A0/MvyJ+ZJ56IomeegcZuz0oMAOAOu/HQqocQ5sPY6d7Zpj3pXGChLLWj/lDOG5CIRqPymzepBCoWi8VNCuzvE25lkSzVjLBwoLNFd5alFkVRnlwnZYmlFbakE7CwsBAOh6NHk+tYEEMUR9sYWKCvT9yT6uuU9cSCIMgD9dChQ1uvL70elr89AAAQxv6cmePTX8jGedieZ3N9fT22bNmC7du3y9kwKdOck5OTldpLtcstWLhXZ6oPxFgMDU/+Ad4lS+TPbBdfjILfPwhO4UmeDZH89NqnUResQ7m9HPccd0/bWBl6q9HV80Kv1yM/Px/5+fny30ue6G63W55wq9Pp4mqbu+MN32st4KST7N///jfWrVuHO++8E/n5+TCbzZ3/dS8nFZEs3bCVk+ui0SisViucTqdcR5zuFbZYEIUUR1vUjoGFQSbdfaD0JpaWddbr9fKErsrKStjtdrS0tKC6uloe0DV1G6Bt3ApRa0R0xEVpjYlInWyek5Jnc2FhIbZs2YJTTjkF0WhUXsWsrq4O1dXV4DiuzYTAvrT8r9rtZzIGwe9H3T33IvjNN/JnOTNmwHX7bUmzuJnsh0/3fYqP934MLafF3IlzYdFb2mzDkkhWllt0h2Se6JLBgHSNHThwAMFgEFartc2kQBYe3NKNPGqEw2E8++yzmD9/Ps4880xce+21mDBhAvLz82G1WtWMMWMkTtxTLjmrnFxnMBjkWp1M1DomgxVRSHGwFQPQuzPJnXkTl5aWyt7EiW0l/izkDkXwgheh8R4AjJn1R2XhBkjEIx0TvV4fZ5Ellb+RZ3PmyJQwjDU2onbGTEQ2b279QK9HwaOPwD51artxZOoYNoYa8Yc1fwAA3DTqJozJG9NuDAAbY0Qm+kOaEyC9zQGOJDaUD6YA5KXrJeHcFwwgdFKHXnPNNbjmmmvw9ddf44EHHsCVV16JUaNG4ZxzzsHkyZMxatQoDBw4sE/NhAyFQjhw4AB+85vfYN26dbjwwgtx3HHHxc2IlybXZRtpMRG1YUUYshAHKzGoTVf6oCfexJ2iNyM26pKu/x3Rp2nPs1lZ1+z1envk2ax2JpeF9oH0jkfR/ftRM206Yvv2AQA0DgeK5j0H84QJHcaRiX4QRRFPrn4SLeEWDHcNx21H3dbhtgA7Y3M2srlGozFu7oAy+dHS0iKXQUmWm06nE3l5eb1SP7a5M51yyik46qijUFRUhGeffRb33nsvfv3rX2P48OGYPHkyJk+ejNGjR6sRa48Ih8P48ccf8e233+K7777Dt99+i127dsFgMGDIkCG44IILcMEFF2D48OFMvDJgQZBJcZBYpxiU7bdHNryJ1e5/gg26eh6YTCaUlJSgpKQEwJGHt5aWFjQ2NmL79u0QBKFHns3ZpK+J5HB1NWp/OQN8QwMAQFtUhJIFL8EwZEincWREJEPE0flHY3Xdajw68VHote3X3/a0xCGdqBULx3Gw2+2w2+0oLS0FEJ8gaWlpgUajkUvlehPtpm8EQUB5eTnefvttiKKIBQsWYNasWbj00kuxZMkSCILAhJhMlXvvvRdvvvkmTjzxREycOBE33HAD9u7di4ULF+Ltt99WO7w2qC2GKA52UbsfpPYFQYDX640TxdnyJjZ++RhEUw6iY38B0ZKdgVftfifi6YkY0Ol0yMvLk5fW7qpns9oiVW3SeS0E16xB7a9nQ/T5AAD6wYNRsuAl6A4vQtNZHJk4DhpOgxtG3YBLh1wKu8HeaQysaCGWzkvlNdbnFhOxWCwIBoMAgFWrVmHlypVYsWIFTjzxRFx66aUAOh6gnnzySfz73//Gli1bYDabcdJJJ+Gpp57CiBEj5G3OOOMMfPnll3F/d+edd2LhwoXyz3v37sX06dPxxRdfwGaz4cYbb8STTz4Z92p2+fLluOuuu1BVVYWysjI8+OCDuOmmm5LG9Pzzz8fFvWTJkrRYwGUCVkQhK3EA6osUFvpCzQEwGo0iEomgvr4eNTU1squL9Dot0/X68r4Hm6Ff9zo4PoLYoLOyJpKJeFh6zdxTOvNs3r9/f5xnczAYhF6vB8/zqnjKsiKGehqD/9PPUP/b38oeyMajj0bxn/8EraL+NdMxKBFFEREhAqO29cG+M4Es/Q0LxwJgS7D3FdqIZJ7nwXEc1q9fj9mzZ+Odd97B0KFDMWvWLFx55ZUA0GkW+csvv8SMGTNw/PHHIxaL4YEHHsDkyZOxadOmuEmAt99+O+bOnSv/bLEcmTnK8zymTp2K4uJirFy5EjU1Nbjhhhug1+vxxBNPAAB27dqFqVOnYtq0aVi0aBE+++wz3HbbbSgpKcGUKVPiYlJ+t4Rer8/YYiI9RaPRMCHgaVETtmIAsvOwoJzEKv0LBALQaDTQ6XQoKSnByJEj0+7qkkpc+q0fgOMj4AtGQSjsfaVfRM/JhjBJ5tksvTrevXs3Dh48iP3798PhcMTZz2Wj7lJtYZaOByTPkiVoePwJ4HA5n/nUU1D09B+hsaTurJXu8oL3dr6Hf2z5Bx6d+Gi7E/USUftYKGGp9KOvIIvkaDSKb7/9Fv/3f/+HTz75BEajEVqtFt988w0GDRok/0EqZRYfffRR3M9vvPEGCgsLsXbtWpx22mny5xaLBcXtvFL55JNPsGnTJnz66acoKirCuHHj8Nhjj+G+++7DI488AoPBgIULF2LQoEF49tlnAQCjRo3C119/jXnz5rURyckwGAxMCNFkUC0we3GwMPhkKob2vIml0gnJm3jz5s3Iz8+X7YGyibTvuk3/BgBER12e9baJ/otGo0FOTg5ycnLQ0tICl8uFoqIiuURDTc/mbNMTkSyKIlpeeRXN8+fLn9kuuhAFDz8c54Gc6nelq28bgg14fv3z8EV9WHdoXa8Uyaxnklnpp64g+yR/+umnmDp1Ks466yw89dRTuPzyIzcgnueh0WjAcVy3DoDb7QYA5Obmxn2+aNEivPnmmyguLsZFF12E3//+93LGd9WqVRg7dqy8pCIATJkyBdOnT0dVVRWOPfZYrFq1Cuecc07cd06ZMgWzZ89OKS6DwYBIJMLUSS7BgiikONiLAUhPJjlVb2LWBlxzqB66g6shgkNs5MVqh0P0U6R7huQpO3DgQADImmez2ves7opkURTRNG8e3H/7u/yZ88YbkDt7NrhujDXp7Ien1j4FX9SHUTmjcPXwq1WJoaewFEtfQbaAmzBhAtauXYtjjz22zUY9qbkSBAGzZ8/GySefjDFjjjyZXXPNNaioqMCAAQPw008/4b777kN1dTX+/e/WLFFtbW2cQAYg/1xbW9vhNh6PB8FgsNMFUbqz4l62YEWQURzxqB1Dd/qhJ97E7X2fWhQ3tC4wwJefBNFeolochLqofR0CyQViR57NUm1zomdzTk5OyteehNpiqDv9LwoCGp54Et7Fi+XPcufMhivJHKKuxJGOfvh83+f4Yv8X0HJa/P6E30OnSf0hRu1joYTKLdKPfCbYD6+FvmbNGkSjUflfJBJBNBpFOBxGLBaD1+tFSUkJLrootRWuZsyYgY0bN+Lrr7+O+/yOO+6Q/3/s2LEoKSnB2WefjR07dmBIJ7Yv6SJxMRGWoFpg9uJgJYbOiMVi8Hg88tKiid7ExcXFcDqd3cpmqToAiyIGNLaOI7GRl6jQvPrXAUuo3R9qi8RU2k/Fs3nDhg0wGAxxopnFtzjJSPUYiLEYDj38CHwffCD9IfIf/B0cV1zRo/bTIVA9EQ+eWvsUAOCGUTdgeM7wLv09S05frJdb9Ebku+T69etx0kknwWQyIRaLQaPRQKPRQKvVQqvVQqPRwGg0wufz4ZxzzklJJM+cORMffPABvvrqK9k7rz1OPPFEAMD27dsxZMgQFBcX4/vvv4/bpq6uDgDkOubi4mL5M+U2DocjpWW1WRbJrNUkq/203FsEajZiUPZDNryJE1HrOGiEMLyWCthEH6LDLlAlBiIeFq6J3kY6PJvVHo+7Um4hRiKou/+3CHz2WesHWi0K/99jsF3Q82s4Hf3wp/V/QmOoERX2ig4XDclkDOmCpViUqH3v7gmySD7uuOOwZcsWGI1G6HS6OIGs0+mg0+nkA9BZBkoURcyaNQvvvvsuli9fHjfxrz3Wr18PAPLAMWnSJDz++OOor6+XZxcvW7YMDodDXsxk0qRJ+PDDD+O+Z9myZZg0aVJKO0/lFqnFwQKs9IfaMYiiiGAwiL1798Z5E9tsNrhcrox6EwMqZ+90Zvw0dBbsk04EOjD3J/o+aouBdI4D3fFsVvu+lWr/C8Eg6n5zN4LftJZJQa9H0dNPwXrWWWmJAejZmBTlozjoPwgAePD4B2Xrt67Gwcp9ksot0o+sdg0GA4YPT/6a4dChQ1i7di3OSvHEnjFjBt566y289957sNvtcg2x0+mE2WzGjh078NZbb+GCCy5AXl4efvrpJ8yZMwennXYajj76aACQV/a7/vrr8fTTT6O2thYPPvggZsyYIQuAadOm4cUXX8S9996LW265BZ9//jneeecdLF26NKU4SSSnFgeg/kDAQn+oEUM0Go3LEku+rTk5OVnxJk6GmsdBFEVVBDLdeIhEMnVOtOfZLInm/fv3o6WlBR6PB42NjXKJRjbHgVTuB4Lfj9pf/QqhNWsBAJzJhKJ5z8Fy0klpiwHo2XHQa/WYf8Z8bGjcgKPzj+52HKyMDyyXW7DSR10lLiUcDAZRVVWFXbt2IRQKyR7Cq1atwl//+lfMmzcPGo0Gs2bN6vDEWLBgAYDWBUOUvP7667jppptgMBjw6aef4vnnn4ff70dZWRkuv/xyPPjgg/K2Wq0WH3zwAaZPn45JkybBarXixhtvjPNVHjRoEJYuXYo5c+bghRdeQGlpKV599dWU7N+AI+UWLJ3kEiyIQikOQP0MKgvHJ9PHpD1vYovFItcScxyH3Nxcub4x26h1HLjmXdB7mlRpmyASyfY9w2AwoKioSJ6ovnr1ajgcDhgMBrm2ORqNZs2zubP9591u1P5yBsIbNwIAOKsVxS/+Gebjjkt7LD09DhzHdVsgA+yI5N6wuA/LsbWHLJJ9Ph9mzpyJv//973L9olRqIYoizGYznnnmGYwcObJTkdyZkCgrK2uz2l4yKioq2pRTJHLGGWdg3bp1nX5XMqQBJBaLxdV7sYBGo2GmJhlgQyT3tRgSvYk9Hg94nm/jTaw8N5uamlQfaNQ4DoY1C2H7aRGGD7gEwKlZbx9Q/xogjkDHArBarfJcH6kMK1uezR31P9/Sgpo77kSkuhoAoHE6UfzSfJjGpOY7nCrS/bE7+7PbsxuLty3GtLHTUlpVryNYEck96Q+ifWSR3NTUhA8++AArV67ExIkT4zZau3YtzjzzTOzbt0/+jNWUflfQHzYuD4fDzIlkFkShFAcA1QU7C/3R08EnXd7EavaDKgMwH4F+a+us+Ab7aBR1sjmRHXr79dgT1N73RDrzbK6trW3j2SyVbHXXszlZ//PNzai5805EqrcCALR5eSh5eSEMw4Z1f+e6EUdHiKKIp9Y8hdX1q+GNejF34tzO/6gDWHG3kM5JFmLpS8hXB8dxCIVCmDhxorw0tSiK0Gq1iMVictY1Go3K4rK3IwljFuuSWRCFUhyA+jcFVvoj1RjS7U0swUI/ZLt97a7l4EJu8JYCNNppGWqW6M9ZK7VFemftJ/Ns9nq98rwGybPZ4XDIDhqpejYna59vbm7NIG89LJDz81Hy6iswpDBxvzt0N3P68Z6Psbp+NYxaI+4Yc0fnf9AJrGSSe0O5RW9EFskulwt33nkngLaLh4waNQoPP/wwAPQZgQwc2RcSyR3HAagvklmIoaNjInkTS5Pr0ulNnBhDf0O/+V0AQHDIBQBHWRJCfWHSG9vXaDRwOp1wOp099mxObJ9vamoVyNu2AQC0BQWtArmysmc7mgJd6QdfxId56+cBAG4ZfQtKbR1b06aC2ueCBOvlFqzG1Rlxi4k8/fTT8Pv9iMVi8j+e58HzPH7xi18AaJ1lu2XLFtmFojfDciaZpcVEWBDsLMWQqjex1WrNyKsvtcststp+xAfdzk8AAMFhF0HcG85e2wTRx+nIs7mhoaFdz2alMOQbm3DwjjsQ3b4dgCSQX4WhMrOTi7sjChdsWIDGUCPK7eW4fuT1aYmDFZFM5RaZQRbJ4XAYkyZNgslkAs/zshgAWkWk0WjEd999h5qaGtxyyy1Ys2aNakGnC2mRFMnFgyVYWUwEYEugqoG0tGx9fT14nsc333wjexM7nc6MexMrYWEwzia6bR+Bi4Uh5AxGLP8oYO8PqsTR3/qd6Bi1x8NMCbNkns0+n08u0ZA8m6VFx/Zt3Ajhwd+D37ULAKAtLMSAV1+BPgvuO10tL9jStAWLt7cuiX3/+Pth0KZnHhIrIpn1THJvRRbJOp0OU6ZMgcFgkBcRUS4m4nK5AAA5OTmYMWOGWvGmHYPBgFgspnYYbWBBmEqwEEs2Y0j0JvZ4PNBoNPLM8KOOOirr3sRK1M4kZxPdjtYscnTUpeBUzpCofQ2whtp+2WqLgd5WbtEdOI6D3W6H3W6XPZvD4TD279+PPT/+iOCzz0FXUwMAEHJygEcehs/hgIPnMz4+dlUkv/jTixBEAVPKp+CE4hPSFgdLE/fUviY6guXYOkIWyVqtFk8++WS7GzY2NgJorbG8+eabMx9ZltDr9UxmklkptwD6tkhOxZt4xIgRsFgsCAaD+O6775CTk5P2OFKFhWORzfZDU19EdM8KCPkjs9YmkTq99cbXU1gXJJnEaDTCIQgYuPBl6OrqAABcYSE0jz6CFpMJu9ety4pnc1ePwdyJc7FgwwLcOeZOVePIFCwvJNKbaTOLyOfzyQuJxGIxRCIRHDp0CNdeey3+9a9/IRKJ4IQTTmDipOgpHMfJC4qwBgtiSIKFWNIVA8/z8gxvaaKd0pt4yJAhcDqdSS0BWTjn1Y4h6+1rDeAHn936/36/6uchQbCAmsKMb26G/+57oD8skHUlJSh59RXoFZ7NgUBALtHIlGdzV/sg15SL3x3/u263l644MgUrcfQ14kTyihUr8OCDD2Lv3r1xK9EJgoDa2lpcfPHFEAQBe/fu7TMHg9VMMtUkpyeGjryJXS4XKioqUvIm7kkM6UbtGLLWvigCinGmr4w5RM/pN9dAB6hxPfAeD2runAZh924AkkB+FfrSgXFxWa1WWK3WTj2bldZzXXX/SVUU7vbsRqWjskv72RVYEaeCIDARR18j7oycNWsWRo4ciZtuugkmk0muSQ6Hw7jpppvw5z//GWazuU8dCJ1OR5nkTmAhllTOOVEU4ff70dLSEudNbLVa4XK5MHDgQLhcri57EyfGoOagqPa1l632uZY9sCz+BaKjL0PkpLvjxLIaqN3vRFvUPiZq1yRnG8HnQ+206fJKerzLhbJX/hInkNsjU57NnR2D7S3bce3H1+KkkpPw1MlPpW2ynhJWRDKVW2SGOJFcXV2Nd999F4MSzL+j0Siuu+46nH/++cytTNdTDAYDieROYCGWZDEovYmlf0D6vYkTUVskq30sstG+vvq/0Hj2QXvwhziBrPa+E2zAwnmgtkjOZvtCIICaGTMRrqoCAHA5OWiYNRPDDk/m6yrJPJuDwaCcbU7Fs7mzzKkoinhu3XPgRR46jS4jAllqhwWRzHImmYXrtbvogCMH2WKxJHV64DgOJ554IgKBQJ8SyVSTnBqsxCKV/STzJs7Pz8eQIUMy5k0MsLWwilpkaxDWVb8HAIiN/FnW226P/nzck6F2f6gtUvsLQjCI2lm/Qnj9egCAJicHxqefgpDm+6bZbIbZbO7Qs1kURblUrjMtsvzAcnxf9z0MGgNmj5ud1liVkLtF30YHHBlsJAcLnucRjUYhCAIEQYAoili1apV6UWYQVmuSJXcLFk58NUSy5E0sDZItLS3geR779u2Tsw/Sss7ZQu3jIMWgdq16ps8FTeN2aA9thqjRITr0vIy2RRDdQW2RnK37ghAOo27OXQgdXhdBY7ejZOECtOTkgNuxI6Ntd+bZfODAAUSjUXz99ddxJRoWiwURIYLn1z0PALhu5HUYaOu8JKS7sHCPluJgQay3Bwt91B3i3kOLooj169fjk08+kU/AWCwGURRx6NAh/P3vf4fT6VQr1oyg1+uZ9UkG2LgAsyHM2vMmll7J5efnY8uWLTj++OMzGkcqsHCDVItsnIu66vcBAHzFaYA53m5P7b5XC0EQ4PF45Hp76TV0OlwCeoLaY5OaqJ3JznT7YjSK+rvvQfBwgoyzWlG84CUYR46EWFub9f1P9Gxubm7G+vXrMWzYMLS0tGD//v2oqqqCTqfDSmElDvgPIN+YjxtG3JDRuFi4RwNsl1v0ZuJE8jvvvINbb70VLpcLw4YNg8FggE6ng8FgQDAYZFJM9hSDwcBkJpmlV/vpziR35E3scDjivImlfggEAmlrv7uwcEz6/CAoitBV/xcAEFWUWvQ3pHp76S2Kx+OBVquFy+VCbm6uXHq0ZcsWaLVaWTDn5uam7NbSm1F7XFS7/UwjxmKou+9+BL76CgDAmc0omf8iTGPHtv6eAWEolTkUFRWhqKhI/mx73XZ8tOIjAMC5xnPxzfJv5BINqb45nZ7NrGRwWYmjr6EDjpxsTz31FH75y1/i6aefVjuurMFqTbJ0srMwGPdUJEvexEpRnKo3cbpiSAcsiOS+3r6mYQu0Tdsgao2IDZkS9zs1b8qZbltpkdXS0gKfzwej0Qin04mioqK4h0ZpLgXQOna73W40NzejqakJO3bsgCiKspiWrLXUWh0yk6gt0vpqJlkUBBx66GEEPvsMAMAZjSj+059gOvbYrLSfKsli0Gg0iBgiyDfnI9+cjzlnzZEnBDY3N2Pbtm3w+XywWCxxJRo9eRvDQl+wFEdfIy6T7Pf7cfLJJ6sViypQJrlzuipQk3kTS0ubd9WbWBkDoL6zhNqo/bCQ6fZFnQmRo68DRB4w2jPWjtqEw2E0NzfLNfd+v1++cZeVlclWhZ2h0WjkLDLQen14vV40NzejubkZe/fuRSQSkcWA9C/dji/ZRu1xkYX2MzEeiaKIxqeehm/p0tYP9HoUzZsH8wnHt9lObdrrgzF5Y/DOBe+gJdwCjUaTcc9mVsQpy+UW0sN9byRu4t61116LFStWYPz48SgpKZEXFBFFETzPq1r7lilYr0lWe5IW0LEw6sib2Ol0YuDAgXA6nT3212ZBJEuoLVLVJqMiOWcQwuf+IenvWDoHuoIoinH2Vi0tLQiFQrDb7XC5XBg8eHCnb1JSheM4OBwOOBwOVFRUyKVNUqZ506ZNCAaD8pLBUolGd9vuy9l9ltvP1DXY/NICeN5+u/UHrRZFTz8Fy8knJW1f7f7vKAaj1ogiS1HS33XXs9lsNif9PnK36NvEPSoNHToUc+bMwfLly3HyySfDaDTKQvnQoUN48sknUV5erlasGYFVdwtWM8mpeBM7HA75dXA6YwDYEKhqHxMW+qA/kmq/S7Pwlc4s0WhUvumOGDEiI/7dyVCuflZ6eNngUCiEpqamuCWDrVarLJg7EgRK1L4O1ISFfU/3tdjyj3+g5S9/kX8uePQRWM86K2vtdwdlDF8f/Bq1/lpcMuQS6DSpX1sdeTY3NzfLns1GozFONEtvQ1kRp1STnBnifJLff/992O12cByHFStWyCvumUwmNDc3MzF5Kt2wWpMsvZ5QczAWRRGhUAjRaBQ1NTXYt2+fXCvpcrmy4k0swYJAZSkGNcnU/mu3fwLRnAthwHEA1/75xMpNSUKZiZLeqEh+rtLbFIfDwUxdsMlkwoABAzBgwAAAQCQSkcsz9uzZIwsCSTDn5OTAarUy1ecsoHYmOZ3te//zHzQ986z8c96998J+0UVZa787KMsLonwUz/zwDPb79iMshHHtiGt79N1d8WwOh8PQaDSIRqNpTw51BZbLLVh4qOwuOuDIJLG3pdcs/QiDwcBkuQWQ/fpTpTexNCBEo1FoNBro9XpVvIklWLn41X5wAfqoSBcFmD7/PTTeAwhc/FfwQydnpp00wPN8XJZYcp5wOp3IycnBoEGDYLPZek1Wx2AwxDkExGIxOYt28OBBbN68GTqdLq6m2eFwqBozC9eg2iI5Xfg//QyHHp0r/5wzfRqc117TafssjMlSDEu2L8F+337kmfJw6eBL095OR57NO3bsQH19PQ4cOACbzdbGszlb/cTKMelrtHknITkR1NTUwOv1wmKxoLCwEAUFBX3yALBabgFk3p+4M29iKQNWVVWF3Nxc+SaqBixkcZVxqNm+2n2QifY1B3+AxnsAot4KvuLUpNuo1ffSdcLzPNasWQOv1wuDwQCXy9XGeaIvoNPpkJ+fj/z8fABHHDSamprQ0NCAbdu2geM42Gw28DyP5uZmOJ3OrD8U9JX+7i7p2P/At9+i7v77gcP3Gce118B1552d/h0LgkzKnHoiHrxa9SoAYPrY6bDoLRlvW+nZfOjQIeTl5aG4uDiurrmqqgp6vT5ONGfyjRKVW2SGNiJ58eLF+H//7/+huroaGo0GOp0OkyZNwty5c3HSSW0L+Hs7BoOByXILIL2CSDl5SOlNbDabk9pMZSqO7sKKSFY7BrVvTJlqX394AZHY0CmAvvN62EwSDofjSiek5c9FUcTAgQNl5wm1j0W2aM9B4+DBg3C73Vi3bh1isRicTqdcouFyuXq9g0ZHqD0OpUOkhn76CXWz5wCH73+2n12EvLvvTul71d5/CY7j8Neqv8IdcWOIcwguGtR+iUimkI6F0WiMeyPD87zsdS7VNkej0Yx5NrNcbtGbiatJfvPNN3HPPffg8ssvx6JFi+B0OlFXV4eHHnoIt99+OxYtWoRx48Yx8RSZLljPJHd3MEqHN3E64kgXrIhkFvqiz7Uv8NBtbbWcio7ofAGRdC9sEwqF4pwngsGg/Nq0srISTqcTkUgE69evl2sU+zOSg4Yoijhw4ADOPPNM+P1+ua75wIEDCIfDcQ4aOTk5aXHvkGDhHtSbyy0i27ahdsZMiMEgAMBy5pkoePhhcN2w5VQLQRDQGGvEP/f8EwDw63G/hlaT/br/9twtlIv8DBo0SHaayZRnM8uZ5F5vAScIArRaLRYvXoyf/exnePHFFwG0dnplZSXee+89jB8/HmvXrsW4cePA83yfyRKwagEHQJ45mwqZ8CaWYEEYSqgdh9oXutrtZwLtge+h8ddBNDrBV57W7nbp2HelZWGi84TT6cSwYcPgdDrbTMCJRCKqn3ssIt38bDYbbDYbysrKALS6A0i2c1u3boXf74fNZouznVNjbkM6Ufta7G770f0HUDP9lxA8HgCA6YQTUPjUH8B14Z7OwkMKALzX/B6iQhQnFp2IScWTVIkh1b5QOs0kejY3Nzf32LOZlWPS14jzSZZsgCSUHV5aWgqn09n6R31EIAOt5Raew4MFa7RXkyzd6KXJQ5nyJu4sjmzCgtuHFIfa5RZqt59udHKpxXmANn3ZRuDIZFSlKBYEQX7lyZrzRF9BcgeQHDSkxVOk184//fQTzGZznO1cb6rrVnsc6q4g4puaUDt9OvhDhwAAxjFjUPz8PGi6+MqfBUEmCAImuyZDa9Xi1+N+rVo8PemL9jybm5ub0dLSgv379yMcDsue6lKJRjKLRiq3yAxxIvnqq6/Gyy+/jPfeew/nn38+3G43TCYTnnnmGdhsNhQVFaG2thYtLS0YMGCA6jOc0wHLmWRJEKnlTZwYBwuwEIfaMfSp9kUR2pp1AIDoyM5LLTprX1kHKDlPKDMzPXmjQnQfo9GI4uJiFBcXA2h10FCWZ0iTnJS2c5IdaTLUFmm98RoUAkHUzvoVonv3AgD0gwaheP6L0Fit3WqfBUFWaa7ES6e8pGoM6ewL5cR5CaVn865du+D1epN6NrNabiEtSNdbiUsJB4NBbNiwAVdddRVGjBiBgQMHorq6Grt27cIJJ5yA5557DoFAAHV1dZg7dy5+9rPUbmosw9qy1FKNpNvtRjQaRXV1NYLBIIxGI5xOZ1a9iSVYEcksxKF2DGrfmNLePschcN2H0B5YDX7A+C63LdmVSW9VPB6PPKO8oKAAw4YNI49fBtHpdHEZNMlWr7m5GfX19di6dSs4jouraVbDQaMj1D6nutK+GI2i7p67Ed64EQCgLShAyYKXoHW5utW22uMwL/DMZE4z/cCQqmezTqeD0WjEoUOH4HK5VPVs7kvEieRwOIxx48bJT/scx2Ho0KEwGAzyiWCxWOD1elW1A0snartbJHoTu91uRCIRuXi/oKAApaWlqtbvqS0MWYqDlUG5T7XPacCXnpjy5ocOHZIX7/D5fDCbzXC5XCgpKcGoUaPSVmYUFyIDx51F0tUvWq0Wubm5yM3NxZAhQ+TXztLKgLt27QLP83LmDFD/OlA7k51q+6Io4tDcuQh+/Q0AQGO3oWTBS9D1YBKqmplkQRRw86c3Y5BhEM61natKDEqyncFtz7N506ZNiEQi2Lx5MwKBgDz5WCrR6E3lTCwRV25x/fXX4/rrr1c1oGyj0+myKpJT9SbWarVYvXq1aot3KGFBnLIUh9qZZLXbTxsC3/rfdmakJ3OeAIA9e/YgJycHFRUVabVQIrpGJs9D5ZgoOQP4/X5ZNDc0NCAajWLVqlVxJRrZyp6pvRJqV2j+05/he/+/AADOYEDRCy/AMGxYj+NQS3B9vOdjbGrahN3a3TjXrr5IVjujLXk222w26PV6DB8+XLaxbG5uxr59+7Bx40b5DZskmmkuRmq0mYEniiKam5uxbt06NDY2oqioCGVlZSgvL4dOpwPP8+A4jqnXXj0hkyvupeJNPHz48HZfB7MwYU6KgwVxykIcasfAQiYgXfuv3bsCpv/NRvToaxE5+Z44iyTpXyQSkSetDB48GFVVVRg/frwqrxLVPvf6M0oHjfLychw8eBC7du1CeXk5mpubsWXLFgQCAdjt9rgSjUwlGFg4F1IZC9yL3kLLX/8q/QEKn3wS5vEdlzWlglqZ5CgfxcINCwEAPyv+Gew6e9ZjSISV+mxlHJ15Nu/atSujns2J9HoLOOBIB3/11VeYOXMmNm/eLAu04447Dvfffz+uuOKKPvfkkc6a5GTexLFYTJ5g1xVvYkB9QaaMgxWxrjYsHJO+ItJ11R9AE2iA/9BebP7pJ9nL2+FwyOUTTqdTHnN4nk9b20TvR6vVYuDAgbKdluSg0dTUhJ07d8orxipt59JZiqOmm0Iq7fs++hiNf/yj/HP+A7+F9Zyz0xaDGvv/7s53ccB/AHmmPJxfdD74kPpjAisiuaOMdlc9myXR3F3P5r6ELJI5jkN1dTUeeOABjBgxAl9++SXuvfdeWCwWnHHGGXj00Udhs9lw3nnntWue3RvR6/XdLreIRCJxWeJ0ehMDbAgyioOtGFgYsHq6wE1LSwtamhpx4pYPAAAHnMfD6XSS8wTRJRKvhUQHDcmDtqmpSV4m2GAwxNnO9VUREPzue9Q/+CBw+Fp13X47HD//edq+Xw1hGIgG8FrVawCA24+6HQYYEOJCWY0hGayI5K7URnfm2VxTU4MtW7bIzkCSaE7Vs7kvEbfi3hdffAGdTocXX3wRubm50Gg0CAQCuOyyy/Df//4X7733Hs477zzVhUo6SVUkK72JpZmlmfQmBrq2mEgmUVsYshQHK4OhWnRl/5WzsJXOE06nE+XCbhhiPgjmXFSefg2g6dpCBgTRGYketDzPyyKgrq4O1dXVcUtu5+TkwOFwpCQ01BRGnWWSw1u2oHbOkeWm7ZdeipwZv8xIDNnk/7b+HxpDjSi1leKSIZdg145dzIzHfSGOzjyb9+7dG1f+1pFnc18i7s7kdruh1WrlJ3GTySRPljGZTPKiG33pJtWeu0Vn3sQjRozIqDcxwFaZAwvHnJU4eotIzTaRSCROFHu9XphMpqTOE8ZliwAAsWHnpyyQ1Z4cQ8TDwrXYFbRabZwrgCAI8Hg8cSUagiDIAkASAclKDFmYuJfUErGmBrUzZ0H0+wEAltNOQ/6Dv0v7+ZttR4eYEMPibYsBANPGToNOo1N9wpwEKyI53f2Rimezx+ORx3ilZ3NfehsYd3fKzc2FIAgIBAKwWCwwGAwIBoM4cOAAduzYgSlTpgBAn+oAg8GAcDiM7du3Y/ny5SgtLUVubi58Pp/sTZyXl5d1b2KAHVFIGW12YlC7feDITTrReSIQCMBqtcLlcqGsrAwulyv5xCmBh27b/wAAsWFTsxk6kWbUzqb2BI1GI9/cpTpNn88ni+Z9+/YhEonA6XTKJRpK/1kWhJESwetFzcxZR1bTO/poFD79VJeWm+4K2dx/nUaHN6e8if/s/A8ml09WJYb2YKX8NBsPLu15NkuOM5Jns3TN9IUSjTgLuCFDhsBms2Ht2rU49dRT4XQ68cUXX+Cqq65CTk4Obr31VgC9XyRHo1H8+OOPWLlyJf75z39i48aNmDBhAoYNG4bp06fj2GOPJes1ioPZGNRoX5roIdXer1y5EuFwWPbi7MqkVO2B76AJNkI0ucCXTepWLASRCS9su90Ou92O8vJy2Z1Isp2T/Gel1c0OHTqE4uLirFsQJsski9Eo6n5zN6LbtwMAdOVlKP7TC9Bk6FW4GtnTfHM+bjvqNvlnyiTHo0Z/tOfZLJVo1NTUIBAIYMSIERg+fHhWY0sXcfL++OOPx7Rp02QRfMwxx+DEE0/EpZdeiuuuu0510dhT3n//fcybNw/ff/89DAYDJk2ahMGDB2PPnj349ttv414rsIBGo6FyiwTUjkPtwTBb7UuDnTJTzPM8jEYjNBoNRowY0e0MgWAfgMiEaRB1RkCbermS2n2v9rlHHCEbx0JaPMtisaC0tBRA69uT5uZm/Pjjj9i7dy82b94Mi8US59WcicVslCSK5NbFQh5D8LvvAAAalwslL74I7eFFVzIVQ7auxwO+AxhoG5j0d2qPCQA7IpmFOBIfNIHWa4aF2LpLXErYbrfjwgsvxMknnwwA+NnPfoalS5fitttu67JAfvLJJ3H88cfDbrejsLAQl1xyCaqrq+O2CYVCmDFjBvLy8mCz2XD55Zejrq4ubpu9e/di6tSpsFgsKCwsxD333NPG13j58uU47rjjYDQaMXToULzxxhtJY8rLy8M111yD77//Ho2Njfjwww9x/fXXw2g0wuFwdGn/sgEr4pTiiEftGDLRviAIaGlpwe7du/Hjjz/iq6++wg8//IDGxkbY7XaMHTsWp512GioqKmCxWJCXl9ftV2iiqxLh0x9E5OR70rwXRH9CjZuuyWSS5+xMmDABZ511FkaOHAmdToe9e/dixYoV+PLLL2UR7fP5Mj5etLz8F/jefx9A62IhxS88D31FRUbbzJbo2e/bj8uWXoZfffkrhGLxThasCC+W4mDxLb/RaOzVCz51epeTUvhdPQm+/PJLzJgxA8cffzxisRgeeOABTJ48GZs2bYLVagUAzJkzB0uXLsXixYvhdDoxc+ZMXHbZZfjmm9blM3mex9SpU1FcXIyVK1eipqYGN9xwA/R6PZ544gkAwK5duzB16lRMmzYNixYtwmeffYbbbrsNJSUlcg21xMknnyw/AEjo9fq0+SSnG1ZEIcXBTgzpGoylialK5wmtVguXy4Xc3FwMHjy43Rp8tY+B2u0TBNB6LRoMBhQWFqKwsBDAkRrNpqYm1NbWYsuWLbJHrZRt7unEJmUm2fvf/6J5wQL5dwWP/z+Yxo3r0X51JYZM81rVa+BFHqIowqSLT9QJgsBErSsrIpmV8pO+RqdnWHcv5o8++iju5zfeeAOFhYVYu3YtTjvtNLjdbrz22mt46623cNZZZwEAXn/9dYwaNQrffvstJk6ciE8++QSbNm3Cp59+iqKiIowbNw6PPfYY7rvvPjzyyCMwGAxYuHAhBg0ahGeffRYAMGrUKHz99deYN29eG5GcjPbcLVhAbUGmjIPKPtiIobvtSx6Ykq+31+uFwWCAy+VCUVERRowYAYvF0ukg29NBWLf5PxBNDvDlpwDa1BbVSVfbPYFuPm1R+1pkkcQaTUEQ5IlNjY2N8sQm6WE0JycnbsGcVJAnzq5ejUOPPCp/nnvXHNgmT27vz9JOpq+JPZ49WLp7KQDgzrF3qhJDZ4iiyIxIZiWOvkbWHsMkC7Xc3FwAwNq1axGNRnHOOefI24wcORLl5eVYtWoVJk6ciFWrVmHs2LHy0ooAMGXKFEyfPh1VVVU49thjsWrVqrjvkLaZPXt2SnH1ZDGRTEOuEuzFwcIglEofhMPhuHpiv98vr6ZUWloqe3pnqv3kfyjA+NVj0PjqELj0b+AHp2f1L0I9erO7RU/bTmXflT7M0t9K3rNNTU3Ys2cPotFonO1cTk5OpxlSQ20d6h/7f8Dh0kPHVT+H84YberhnqZMNQfZq1asQRAGnDjgVY/LGtPk9C5lT6VxgocyB1XILte/ZPSXuSpRmsEvlEOlCEATMnj0bJ598MsaMaT3Za2tr5UyWkqKiItTW1srbKAWy9Hvpdx1t4/F4EAwGOxUClEmmOLqK2pnkRKRZ+EpRHAqFYLfb4XQ6MWjQILhcrpSXQ+9q+6miPbgWGl8dRIO9NZPcTVg4Bwj1UVsgdQeO4+BwOOBwOFBRUSHfcyXRvGnTJgSDQTgcjrgSDeW1Gzt0CANffx2Czweg1Qs57957s9ofmRbJO9078dGe1rfRd45JnkUG1D8HuvLAlGkok5wZ4kTypk2bcOGFF+K3v/0tJk+ejIKCgrQI5hkzZmDjxo34+uuve/xd6YblTDLHceB59demZ0WcshAHCzEIgtDGeSIajcLhcMDlcvXIeSIVurv/uq2tr05jQ84FdN2byKHmTUDt404cobdkkjtDuTyw0kFDsp3btm0bfD4frFZrq0+zyYTYffdDf3iRL8OoUSh86g8Z80Juj0wLslc2vgIRIs4sPRMjc0cm3YalTLLacQBs9EdfJO7KKi4uxhlnnIFHH30Ud999NyZPnowrr7wSJ554IvLy8mC327vcwMyZM/HBBx/gq6++kgcBqa1IJIKWlpa4bHJdXZ08e7i4uBjff/993PdJ7hfKbRIdMerq6uBwOFJ6ncy6SGbhxsxSHGqjRl9Iy4O2tLTg0KFDCIVCWLt2rSyKBw4cCIfD0aW6xqwjCrJIjg6/UOVgiL5AXy31MJlMGDBgAAYMGACgdSXL5uZmNDc2wv3wwzBt2wYAEPLyIPz2fgQEAdYsZxEz2QeBaACbmjYBAO4Yc0eH26p9T2BJJLNabgGw0T/dJU4k5+Xl4fXXXwcALFiwADNmzMDmzZsRi8Vw4YUX4vTTT8fo0aNRUVHR6XLMoihi1qxZePfdd7F8+XIMGjQo7vfjx4+HXq/HZ599hssvvxwAUF1djb1792LSpNYFBiZNmoTHH38c9fX18uzhZcuWweFwYPTo0fI2H374Ydx3L1u2TP6OzjAYDOB5HoIgMCcyWBKnFMeRGDINz/PyUujSRDtpdTC73Y5QKISTTjpJlQGxu8dAU7MOGl8NRL0VfOVpPYpB7XOAaKW/H4ds3fgNBgOKioqg+8ebcG/YCADgTSbgwd+hJhTClpUrodPp5Hrm3Nxc2O32jHs1Z+r7LXoLllywBGvq12CYa5gqMaQKSyKZ9Uwyy7F1RLvvaIqLizFgwABUVVVh2bJlWLJkCX73u9+hvLwcp512Gu67774OT9IZM2bgrbfewnvvvQe73S7XEEsThpxOJ2699VbcddddyM3NhcPhwKxZszBp0iRMnDgRADB58mSMHj0a119/PZ5++mnU1tbiwQcfxIwZM2TfvWnTpuHFF1/Evffei1tuuQWff/453nnnHSxdujSlDpBqvSKRSLcnMmUKWkyEzTjSHUM0GpUFcUtLS5zzREFBAYYNGwar1QqO49DS0oKGhgbVMgbdHej0W1sfZGNDzgF0vXtRIuIIfTWbyxqeJUvg/sc/Wn/QalF34w045bArlOSg0dTUhIaGBmzbtg0cx7Vx0Ej3mJHJY6/X6jGppONEFwsiWbo/qx0HwHYmuTfTrkjW6XQIhVrNu88991yce+652Lx5M2bPno358+d3KpIXHPZuPOOMM+I+f/3113HTTTcBAObNmweNRoPLL78c4XAYU6ZMwUsvvSRvq9Vq8cEHH2D69OmYNGkSrFYrbrzxRsydO1feZtCgQVi6dCnmzJmDF154AaWlpXj11VdTsn8D2BbJrIhCiiO9MYTD4ThR7PP5YDab5dIJl8sFk8mU9NpiYTDuDpqGzQCAWA9LLdTa/97a730ZtQV6ttoPfvc9Gp78g/yz/Td3IXj4zSrQ1kFDKs9qbm5Gc3Mzdu3aBZ7n4XQ6ZdHscrl6NGchUwL125pvMaFoAnSazmNjQSSzlElmoT/6Iu2eiTabDdFoFMFgEJ9//jmWLl2KVatWIScnB/PmzQPQse1JKkLCZDJh/vz5mD9/frvbVFRUtCmnSOSMM87AunXrOm0vGVLZSOIqfizAgigE2LGiA9TPIHX1mIiiiFAoFDfJLhgMwmazweVyobKyEk6nM+UViVg4J7rTfvDyRdA0VkNwZnYlMILINNm8/iK796DuN7+Rrd6c110Hw89+Bu7wEtTJ0Gg0cDqdcDqdqKyshCiK8Pv9smg+cOAAwuFwnINGV91vMiHIqhqrMPPLmaiwV+Ct896CUdvxmMiCKJRiUDsOgO1yC1bjSoU2IlmypDl06BC8Xi8uvPBCbNiwAVdccQVef/11jMvCaj7ZRJlJZg0WBBHF0bUYpBuScuGOSCQCu90Ol8uFYcOGwel0dlrT3xGsWdCl+IcQ8pPPUu8qau2/2ucecQQWjkWmb/x8SwtqZ82E4PUCACynnorcu+bA6/d3qW2O42Cz2WCz2VBWVgYACAaDsu1cdXU1/H4/bDZbnO2cydR+WVQmBOrLG18GAIzJG9OpQM5UDF2FhRgkWIqlLxEnknmex4IFC/D+++/ju+++w2mnnYZrr70WN998s9z5PM+D47g+U/siiWQWHS5YyeCyIE5ZikNJMjs2QRDgdDoz4jzBwiDYpWMgigAfTlsdMgv7T7BBXz4XxGgUdb+5G7G9+wAAhmHDWq3e0jSOmM1mmM1m2UEjHA7HlWf8+OOPMJvNcaJZuSJnugVZVWMVVtashJbT4vajbk/pb1gQhSzEIEE1yZkhTiRHIhHce++9uO222/Dcc8/JC38oYc0BoqdwHAedTsekSKbloNmMIxAIYNeuXWhpaYHH4wHHcbIorqiogN1uz+hg1ZsyyZr6KljeuQLRERchPPmPGYqKUAMWrkU1yHQdqiiKaHj8CYTWrAEAaHNzUfSnF6A5vGZBJoSZ0WhEcXGxbK0qLWPf3NyM/fv3o6qqCgaDQa59jsViaT3+r1a9CgA4r+I8lNpLO9m6FRYEKgsxSHGwEktfI04km81mNDY2wmw2QxTFuBIEQRDki0ISbulemU8tWPVKZkUU9uc4YrFY3CQ7t9sNrVaLvLy8Ns4T2YCFQbArx0C3/X/gIj5wwSZV2icyi9qT5/pi2+6//wPed98FAHAGA4peeB76wxlfqf1M97ter0dBQQEKCgoAHLGlbG5uRn19PbxeLzZt2oTa2lo52+xwOLqVHKhursaKgyvAgcPNo29O+e9YqMFlIQaArQmEyWA1rlRoU5P8l7/8BYIgIBwOIxKJIBaLIRaLQafTwe/3IxKJIBKJQBAEvPLKK2rEnFY4joNer6eaZIoDAOQFbpTOEyaTCS6XCyUlJTAajTCZTBg6dGhG42gPtY9FVwc73bbWpWVjw85Xpf100ZsH+b6K2sckE+37ly9H0+GJ8QBQMPdRmI4+Ou3tdBWtVovc3Fzk5uZiyJAhWLlyJYqLi8FxnFyiIZWZKR00Unnz/FrVawCAc8vPRaWjsktxqX0OsFLiIN0TWIilr9FGJD/55JOor6+H2WyGw+GATqdDMBhEU1MTRo0aBYfDAYPBkLElb9WA1Uwy1SRnPo5gMChniFtaWhAIBGC1WuXSCZfLFec84fV6VR+Y1SbVY8A17YS2sRqiRofY4HMyHBVB9G7CW7ag/v7fttbxA3BNuxO289s+XLLyWt1qtaKoqAiDBg2CKIrw+XxyXfO+ffsQiUTgcDhk0ZyTk9NmwnKUj8IT8QAAbhl9S5faZ6EfWIgBYMuvua/RRum++uqr+NOf/oQXX3wRw4cPB9C6zPOsWbNwySWX4Jprrsl6kJnGYDAwKZKpJrltHD1Bcm5RZoqVzhNDhgyBy+VKaTVJtVD7WHTlGOi3/w8AwJedBJhcaYuBhXOR6L9k4tV2rLERtb+eDTEYBABYp0xBzrRpHbavJonikOM42O122O12lJeXQxRF2UGjubkZW7ZsQSAQgN1ulwWz5KCx8KyF2OneicHOwT2KQQ1YiEGKA6BMciZoI5J/+ctf4l//+heGDx8OnuchiiKKiorkiXwXXXQRbDYbeJ7vM9lknU5H5RZ9MA7JeUJZU8zzPBwOh1w+Ib0tyVQMmUDt9lNFtz29pRYswMpNkQX6cl1wNtsWIxHU3XUX+MOr0hrHjEHB3Ec7PM/UPgc76wOO42CxWGCxWDBw4EAARxw0mpqasHPnTni9XlgsFrmmOaAPwGw2p7xvLFyLLMQgxQGof170RdqoA4/Hg7q6OgDxThbbt29HLBaTjbP7ikDmOA4Gg4EWE0khDrUHhM4y6zzPw+v1xk2yAwCXywWn04ny8vIeO0+oPQip3T6QmkjgvDXQ1qyDCA6xIZPT1jYL+08cQe3xoLe3LYoiGp54EuH1PwIAtIWFKHp+HjRZ9ijuDl2NIdFB4+NdH6NEXwLBL2Dfvn3YuHGj7KAhlWjYbLZ222GhH1iZuMdyuQULGqYntFG6l156Ke6++24AwDHHHINYLIatW7dizpw5uPTSS3u0CAKr0MS9zuMA1B+UEvtD6Tzhdrvh8Xig1WrhcrmQl5eHIUOGdDjIdjcGtUtg1C63SKl9rQHhk+8B594H0VaU+cAyDCs3H2nJYZPJlPZzuzfBwriYDjz/9/YRJwujEcXPz4PusKNEe7Cw7z29F+z37cdD3z8Eg9aAf0/9N0aMGAGe52Xbubq6OmzZsgVarVYuzcjNzY1Lcqh9P2IlBmUcLMSSDFbjSoU2Inn+/Pm4/fbbccUVV0Cv10Or1SISiWDKlCmYN29eysvn9iZYnrintiAD4kWymvA8j0AggG3btsnOE0ajES6XC8XFxRg5cmSXXtd1F7VFqhQDywOPaMlDZOKvM/PdDIiEbCEIAjwej1zbKT0ICoIAjUYjOw7k5ub2O9Gspv1cOtoOfvcdGp95Rv654JGHYTzqqJT+Vu3j3NM++Numv4EXeYzLH4cCc+tDgWStmZeXByD+3G9qasKOHTsgiiJcLldGvJq7AyvuFqxktPsibUSyxWLBokWL8Pzzz2Pr1q0QBAHDhw9HUVHvzwa1B6simcVMcjYJhUJxzhN+vx86nQ5msxllZWVwuVwdLp2aCdQ+JmoPhP29/Uw/nEjCQMqoSb7cOTk5KCoqwogRI2C1WqHT6eB2u9HU1IT6+npUV1dDp9PFieZs+nf3J9Jx/Uf370fdPfcCPA8AcN50E2wXXJBy+2of157EUOuvxX93/xcAcOtRt7a7nUajgcvlgsvlinPQaGpqQnNzMyKRCNauXQun0ylnmlOZeJ1OWDgWLMXRF0laWCyKIoxGI4YOHSr7Ivv9/j6zeEgiLLtbsCCSla+3MoU0G1rpPBEKhWTnicGDB8PtdiMSiWDkyJEZi6MzWDkmag6Kne2/dt8qcIEGxAadCRhsWYqqdyKVT0iZYkkUu1wuFBQUYPjw4XHLAQOt56BGo5FfQw8ZMgSCIMiiuba2Flu2bCHRnEF60o+C34/aX/0awuE5E+ZTT0Hur2al/Pe9ffz525a/ISbEMKFwAsYVjEv575QOGhUVFfj8888xevRoxGIxNDc3Y/PmzQgEAnA4HHEOGpl8+82KOGUlo90XSSqSly5dij/+8Y/46aefIAgC8vPzcfHFF+Ouu+5CaWlqS0b2JqgmufM4gPQOzlJWQDnJLhaLyaJ4xIgRcDqdcRNE/X4/wuFw2mLoDmoPiL2hfcOav0C3cxnCJ/0GkUlz0h4DC9dEd5EcV5SimOM45OTk9GgFx2SiuaWlJU406/X6ONGcKL67itoOE2pfC91BFATU/+53iO7YAQDQDxqEoiefBJfCohtK1N737h77hmAD3tvxHgDgtqNu63EcZrMZTqdT1iWhUEi+trZv3w6fzwer1RpX12w2m3vcrgQr5yErcSSD5VrpVGgjkt99913ccsstuOiii3DvvffCZrOhuroajzzyCGpqarBgwQK4XC4VQs0crJZbsLSYCNCzm6KUMVOKYlEU4XQ64XK5UFZWBrvd3uEKTaw8NLBQbqG2QGmXiB/aPV8BAGJDz0t7271tsBVFUc4US+c+x3Hy5NKhQ4dmJMOrrFcGIE+KampqwsGDB7Fp0yYYDAbk5eXJ23Wnnr+3HY900BNB0rxgIQJfLAcAaOw2FD3/PDR2e9baTyfdiWFR9SJEhAiOzj8a4wvH96j9ZP1gMplQUlKCkpISAEdWUG1qasLevXuxceNGGI3GONHck+uPlVpgVuLoi8giWZoI8vzzz2P69Ol44okn5I1OP/10nHrqqTjnnHOwc+dOHHfcccxcqOmAVZHMgpOCkq4IM57n4/yJlc4T/5+9Lw9vq7q2X1fzPFoeYzu2YzszSYGSQKABUqYWOtC+QnmUV9rS8qATpUAfZZ4KpaWUlvLaV2j7YygdgEIHZigBwkwG20nsOI6dxKMkS5Ysa7z394dzTu6VJVuSJd1jRev7/CWyZJ19p3PX3WfttR0OB5qammAymbJaImKBJLMQAyAfSZ7rmlf1vQIuEQFvWwy+Qj5ZTL6RjXerOFMsJsV2ux3Nzc2yFNglF0WJSfOBAwfQ2dkJrVY7I9PMKli4BrNF8IUX4Pv1r6dfKBSovPMuaBY3Zv09LGx7rvf/hJCASqHCxcsvzktzqLm+Q6PRoLKyEpWVlQCmHZGI3p+ssJCW24Q4Z2MTygoPKsstCocZmeSRkRHaaU+MJUuW0I5lpYayJnnuOOaKJRaLSUhxIBCARqOBzWajBUfzXd5lYX/IHQMrE3I6qHqmu+zFl5wBFChWuc8BMcSyIUKKxRX4TU1NMJvNTBw3McSkubW1lZKHZNKcnGlmCQvJ3SKyezfGfngdfe34zndgOOH4nGOQ+3zKlRxesfYKfGnpl+DUOWWJQaVSoaKiAhUVFQBAtfzj4+PweDzYs2cPBEGQaJqtVmvaFU5WyCkrZL0UMYMkf+QjH8E//vEPnHjiiWhqakI4HIZCocD999+PiooK2O12OeIsKFjWJANsXADJ5DASiUiK7CYnJ2EwGGC1WlFXVwebzZb3m6rc+4CVGABGM8nxCFR9LwEAYiXUZU+MVJliQoptNhsWL16c9QoJC0gmD6QYSrxMrdPp4HA4KHEuIzMkvF6MfOc7EMJhAIDpk5+E9UsX5vx9LNwP5hNDhb5C9hgIxFp+8p2BQIA6aPT39yMej89w0CC1MiwcC4BtuQVLSY1cQEkymdSvvfZa/Md//AfOOeccfPzjH4fRaER3dzeef/55XH/99WhvbwfADlnIB1jtuMeKaTo5yUdHRxEKheD3+zE1NQWTyUTteWw2GzQaTUHjkDuLS1DOJKfefuXA6+CiQfDGKvA1awsydrG3XxAETE5Owu12AwDefPNN8DxPtfSNjY3z7uLIIlQqFVwuF1yHGluISXN/fz+2b98OrVYLnucxODgIh8NRVDtGuTX5GctvYjGMfP8qxAeHAEy3nK64/rp5F0zKPQ9kG8NbQ2/BrrOj3d4uWwyZgOM4WCwWWCwWLF68mK6eE9Lc2dlJXZdY8WoG2MlolyJmZJJXrFiBV199Fffffz9eeOEFRCIRLFq0CE888QROPfVUOWIsOFjPJBO9eLFAiIE4U8zzPEZHR+F0OtHW1jbDeaIYYIEkyx2D3IV7s92UlMPTrXWnpRaFO18LbUUYCoVolnh8fByJRAIWiwXA9Pxos9mOuBtSMmmOxWLo6+vDgQMHsG/fPmzfvh0Gg0GSaS504ym5iWIm8PzsZwi/9x4AQOlyoeqen0JRAg25srkG43wct717G4ZCQ7h7w93YuGhjXsYvxsMCx3EwGo0wGo2or68HAExNTdGVpLGxMUSjUbz++usSiUaxpUksZ5IXOlKyHJfLhRtuuAE33HCD5PcHDx6EzWYrOb9kVjPJxSJEYucJoisWBAEWiwU2mw11dXXYsWMHli1bBnOWldj5hNwElZUYADaXsKLHX4HYis/LHUZWIKRYrCkmy6s2mw2LFi2CxWJBPB7H66+/DqvVesQR5FRQq9WwWq1wu904/vjjEYvFqK6zr68P27Ztg9FolBQClkq31kzJWfCf/8TEw49Mv1CpUPWTu6E6VEBWjPELiWxieH7geQyFhuDQOrCuel1e45BjP+j1euj1etTW1kKv18Pv96O2thZer5c+MOr1eomDxnzrceYCC+dEOrAaV6aYMxUYCATgdrvxzjvv4Fe/+hVuvPFGbNy4kemDki1YzyTnmxAlEgna1YsQY3F3o1S6SlZaZMtNDuU+5+UeH5j9GAjW+oKOnY+KeJIJIsQ4Ho/TBgR1dXVlIpwD1Gq1xEUgGo1SecbevXuxbds2mEwmCWmejzxL7nlgLkR27cLYTTfT1xXXXAPdUUfl5btZufdmEgMv8Pjdzt8BAM5vPx86VX4kOeT4y70feJ6HUqlEVVUV7UpMpEnj4+MYHBzEzp07oVKpJKQ538W8rMst5D5O80FKkpxIJBAKhbB161b87W9/wzPPPAOfz4cNGzagtrYWwMLe6GSUOklO5TyhVqtpV69MGhiwkEFlIQaAjRs0c3ILPgEosmuIkCuy2XZxJ0dCjKPRKM0U19bWwmKxzOrPDZTWfFcMaDQaCXGIRqPwer3wer20yQMhzU6nE3a7PWvSzKq7RcLvx8gV36OFeubPfAbmz51brPCKgkyJ+uuDr2Ovfy+MKiM+t+RzeR0fkP+6TEVOk6VJxA51fHwcbrcbPT09tIGQ2EFjPiS3LLcoHGaQ5KGhITz55JN47LHHsH37dqxatQpXXnklLrzwwqIWZhQTGo0GwWBQ7jBmQKxJzgaRSERCioPBIPR6PZVO2Gw26HS6rC4qFghqOQb5NckpxxYEGH+3Eby9GeFT74BgqZUnsENIzhRHo1GaKa6pqZnV0qmMwkCj0aC6uhrV1dUApKS5p6cHwWAQZrNZkmlWq9UyR509hEQCo1dfg/jBgwAA7YoVcP7gmrxnDVko5J4rBkEQ8Luu3wEAzl1yLsya/En1WCLJc8VAfJiJI0xyK/q+vj4kEglqG2m32yUOGvmKQw4Q7fhCxoxmIj/4wQ/whz/8AV/72tfw29/+VuKZHI/HoVQqmTwY84FarWZWkzwXKRMEAeFwWFJkJ3aeaGxshM1mm7cekIXuf3ITVJZiYGlsxch2KMb7wAVHIOgLaxGZanxxK1qfz4dIJEL19MuWLcsrKZb72LOE+eyLZNIciUQoae7u7sbk5CR9sCGZZjFplvshMd01OP7LX2JqyxYAgMJuR9VPf5L3Qj25CVGm+37r2FZs92yHRqHBF9u/WJAY5OYiuRwLhUIBq9UKq9VKHTQmJyepg8bBgwfpHCa2nZttpYV1ucVCxoxHldWrV0Ov1+P111+HQqHAmWeeiVWrVqGiokLWoq1CgtVmIsBMUkYuKHGmOBqNwmw2w2azobW1FVarNe9ZGFbIIQsxsAC5SYIYtIFI08mAuvBV3dFoFENDQzRTHIlEqCVTe3u7LM4rRyrydT1otVpJO2Hy4OPxeLBr1y6EQiFYLBaakZNzeTndtTf54kvw/fbB6RdKJaru/jFUhx4CShFz7X9f1IcKXQVOqjspb97IBAuZJCeD4ziYTCaYTCY0NDQAmF4NI6R59+7dmJycpPIkkm0Wr+yX5RaFwwyf5CuuuAJf//rX8fTTT+MPf/gDLrzwQtTU1OCUU07Bxo0bccopp1DD+VIBq22pCQKBADweDy2ySyQS9Em0WMvHrBBUuWMA5M8mspZJVu15DsAh67cCIBKJ0Ezx1NQUurq6yqS4xKHT6WaQZpJpJqRZo9FAoVBQ4lDMcyD5Ooj29mL0usMd9ZxXfBf6Y44pyNisZJLniuHkRSfjhJoTMBWfki2GQqNQx0Kv16Ourg51dXUApHMgcY8xGAyUMEcikbzHUMY0Us4qRqMR559/Ps4//3yEQiH8+c9/xuOPP47zzjsPP/vZz/Ctb30LiUSiZHR9LBXuJTtP8DyP3bt3U+cJuZoXsEBQyzGwEwMBN74XSm8PBIUK8aZT8vKdpJsjkU+EQiFKijUaDVpbW6mLQhlHBnQ6HWpra2nh+I4dOxAOhxGNRtHV1YVwOEwzzU6nM2tN53zABwIY+e4VEEIhAIDprDNhueCCgo23UEgyAGiUGmiU+W8yxQpJ5nm+KOeZVquVyJNisZikjbzP54NCocDWrVupRMNkMsm+fwD5j9F8MefRNRgMuOiii3DRRRfh4MGDCB+q2C0VggzI65Mcj8cl0omJiQmJ80QgEMDq1aths9lkiY+ABWLGwsXGwn6QE8nbr9rzPAAgsWg9oLPm9J3ELowQ41AoBJPJBLvdjiVLlkjkQx6PR5a5h4Vzr4zDUKlUMJlMWLZsGYDDy9NerxcdHR2IRCKwWq1UnmG32/OqS6cFtDyP0R9eh1h/PwBA096GiuuvL+nzZS6COjw5jA5vB06uOxnKAjnesEKS5dICq9VqiYNGd3c3/H4/TCYTRkdH0d3dTW1dyflvsVhk0y3LfZzmg7Qk2ev1Ytu2bRgdHUVlZSXq6uokRXylhGJmkqPRqMSfOBAIQKfTwWazoaamBsuWLYNer6cnVf+hyVdusEAOOY6T3auZhYudhWNBiIKqd5okx5eclvHfkmuAEGOit7PZbGhpaYHNZptVUy/3tpfBBsTXYvLyNGklLCbNhDCQQqhcSbP4/PP95v8QevVVAIDCYkHVT38KRYG7rbGeSX6s+zE8svsRnLX4LNy87uaUn8lHDCzMxazEwXEc9Ho9lixZAmA6wz0xMUElGnv37gXP8zMcNEop2VkoSEgyOeCvv/46LrvsMnR2dlILjzVr1uDKK6/EF7+Y3ypVFlDIwr1k54lQKASj0QibzYaGhoY5nSdYIESsxMHKZCT3fgDY8UmOt30SUCgRb0lPksnSIJmwJycnYTQaYbfb0dzcPCcpnm38YoOFY88K5C4ene1cMBgMMBgMWLRoEfXK9nq98Hg8OHDgAKLR6LxIM8dxCG3ejPFf/Yr8ApU/ugPqRYvmu2nMYzaSHIgG8GTvkwCAMxoLU6NAYpB7LmA5DnFzsKamJgiCgGAwSBv87N+/n/rFi/2aF6LtYqEhIckcx2HPnj249tpr0dTUhFdeeQU33HADwuEwPvOZz+Dqq6+GyWTCOeecQy3jSgH5KtwTt7gVO09kkyVLBgvWawAb5JCFGAD5iRILkzJB7CMXI/aRi6W/E5Fi4tNNHgybmprmtDMqo4xMkOl1wHHcDNIszjQfOHAAsVhsBmme7f6m9HgwevdPgENzgf3yy2A44YS8bNdckJuYzTb/Pdn7JELxEFqsLVhfvb6gMbAwD7ISx1zuFhzHwWw2w2w2o6GhQdJ5VFwMS2o/iESjVFrJzweUJJODvXnzZsTjcdx///1wOBzTT8yhEM466yw8/fTTePLJJ3HOOefIThTyiVwzyeTpTEyKE4kE9WitqamBxWKZl7CfBYkBiUPuY16O4TDkziSLbw6koyPJFAeDQVp53djYmFM3tdnAwv4vYxosEIRswXEcjEYjjEYj6uvrJT61Xq8XAwMDiMfjsNlscDqdcDgcko5ofCQC+//9FvzEBADAcPLJsH3lK0WLnxVilhxDLBHDH7v/CAC4oP2CgsbIyj5YqHGIHxyJREnsN9/b24tAIACDwSCxnRNLQY8UzGBvwWAQgiDQKmK9Xk/1ugaDAaOjowBK60aVKUkmOh+xphgAbDYbrFYr6uvr8y6OZ4WUsUDWWdgXLEwQLMTgHTkARecTGNCvgDeihMFgyGvzmjLKmA35nAeSfWqTSXN/fz/tiOZwOMA98AA0AwMAAFVDPSpvuZmJa7JYSCe3eH7geYxOjcKpcxZUakFiYGGfs+JPLAjCvPXFybaLsViMkuaBgQF0dHRAo9FISDMrDhqFxAySTFwUgsEgTCYT1Go1wuEwBgcH0dnZiZNPPhkASkZqAUxXSqciycR5grhPTExMQKlU0gxDS0tLwU8SFoghS3GUYyj+sSDXAVmaAwDf+09i7e67UWOqw8RF/4a2SC3r5ZqQS/1GsBBRqGOSijQHg0F4vV4EnnkGhudfAAAIGg3i3/0uJhIJWIooP5SbIKYaXxAEPLz7YQDAeW3nFcT2ba4Y5AArne4KYUWnVqtRWVlJ7TbJfcDr9WJ4eBi7du2CUqmkhNnhcMhiT1to0L1KTrjm5mY4HA688847OOWUU2C1WrF582acf/75MBgM+PrXvw6gtEiyRqNBNBrFyMgIXnrpJdjtdlRUVCAYDEKr1cJms6Gqqgrt7e0wGAxFvThZIacsxFGO4TAKGYPYlnB8fByBQABarRZ2ux11dXXYvXs3liv3TX+49fSiEeQy2AIL10ExQPSc2uFh8P/vYZCtVlz6DYzbbOh7/33wPE+JgtPpLChZkJsgphrfH/VDp9RBr9Ljsy2flSUGOXAkxaFSqeB0OuF0OgEcXlknKy69vb0QBCGl7RwL+yhXzHj0WLNmDS677DJaXLZy5UqceOKJOPvss3HhhRdCX2B7m2Li4MGDeO211/Doo49i3759aGtrQ319Pf77v/8ba9euhc1mk7R+lAMKhUJ2mQPABjksx3A4hnwikUhINMWEFNtsNtTV1UlaoMZiMezetRPqvpcAAPElp+c1lkwg9/4vQ34U+xzgAwGMXPE9CIf6BIQ2bMDKiy9G06FYAoEAJQt79+4FAEqaHQ4HLBbLgiYKYqQiZDatDQ99/CEMTQ7Bqs3NL32+McgBluIoduJS7KBBYiArLkSiEY1GsXz5crS0tBQ1tnxiBkk2Go0488wz6eszzzxT8nqh4+2338avfvUrbN68Gfv27cPatWvR1NQEs9mMN998k4rYWQELpIyVOMoxHMZ8YiCkmGSKJyYmoNFoYLfbUVtbSws0UoHjODgme6CY8kLQWZFYdFzOceQCuW9ILBx7liDn8SjW2IIgYPSGGxE7pEPmlixB4Av/IYnDYrHAYrFg8eLFEARhRoYNmCbNpBDQbDbnHL/cxGy2a6DGWFO0GOSeC1iKgwVttNhBo7GxkWr7F7oXc0aPHjzP53xzeO2113D22WejtrYWHMfhqaeekrz/X//1X+A4TvJzxhlS0b/X68UFF1xAXSO+8pWvIBgMSj6zfft2nHjiidDpdKivr8ddd92VMp5IJIK6ujrcf//9GB8fx3vvvYfvfve7UKvVtFiRJbBCyliIg5UY5Ea2+yGRSFBD+Q8++ACvvfYadu7ciampKdTU1GDdunU4/vjjsXz5ctTW1s65WlTjex8AEG86FVAUp/VvGWXIBf8f/h9CL02vnCjMZmh+eC24WdxaOI6D1WpFU1MTjj76aJx66qk49thj4XA44PF48Pbbb+Pll1/GBx98gH379iEQCGR1PbNAzMTjbz64GRPRiaKOz8I+YC0O1iSwxEVmoRdxZ3SHm8/On5ycxFFHHYWLL74Yn/1saq3SGWecgYceeoi+Tt6pF1xwAYaGhvDCCy8gFovhy1/+Mi655BI8+uijAICJiQmcdtpp2LRpEx544AHs2LEDF198MWw2Gy655BLJd5100kk46aSTJL8rZse9bFH2SZbGAMg/MbGyH9KB5/kZmWKVSgW73Y6qqiosXbo0ZysfDkC1/wMA2XXZyyfk3v9lyI9inQNTH3wA77330teu227DRHU1kEUnVEKaCXEWazndbjd6enqgUCioNMPhcDDtGiCef0dDo/j+G9+HWqHGX876C6oMVUWPQU6w0i+Clf2RjFKYq7NOA2V7MDKRa2i1WlRXV6d8b+fOnXj22Wfx7rvv4phjjgEA3HfffTjrrLNw9913o7a2Fo888gii0SgefPBBaDQarFixAlu3bsVPf/rTGSQ5FTQaDeLxeMbbVEywQE4BNsg6CySZleMhjkHcgpRYE6pUqoIUnCom9sMYHYOg0CC+eOO8vy9bsHgjKEMeFPpciLvdGL3qaiCRAADYvvoVGD92EvyDg/MaW6zlbG5upg+1Xq8Xo6Oj6O7ulpBmp9MJo9HIxPyXPP7jPY8jzsexyrmqaAQ5OQY5wUocLMgtShUZkeR4PA6O46BUKgtyIF599VVUVlbCbrfjlFNOwa233korKLds2QKbzUYJMgBs2rQJCoUCb7/9Nj7zmc9gy5YtOOmkkyQNC04//XTceeedGB8fh91un3X8Qralni9Y8CcmcchNDlmYBFiIAZheoQkEAhgfH4ff76dWPC6XC21tbQVzYRFsjXh21S9wQrMJnMaU9+9nFawc9zKKAyEex+jV1yAxNgYA0H30o7D/938XZCyFQkFttFpaWmaQ5t27d0OlUlHSHI1G8273lQ0IMZyMTeKve/4KYLp5iBwxyA2W4mAho12KmPVK6+/vx+bNm9Hb2wulUom2tjYcd9xxaGxszFsAZ5xxBj772c+iqakJvb29+J//+R+ceeaZ2LJlC5RKJYaHh6lPHw360IQxPDwMABgeHkZTU5PkM1VVVfS9uUgyy3ILFsgpK3GIMylyxlD0ynqep4TY5/MhFAqhr68PDocDLpcLra2tkkxToRFVmRFr2AC5GkvLfR6WMQ05j0Ohxx7/5f0Iv/ceAEDpcqHqRz8Cd6gAqdDEKBVp9vl81J/W6/VCqVQiGo3SQsBiWpOSff9M3zMIxoJoMDfgpLqT5vir/MfACjllIQ6WM8mk1myhIiVJjsfjePDBB/Gd73wHgiDAaDQCAAKBAGpra3Hffffhk5/8ZF4COO+88+j/V61ahdWrV6OlpQWvvvoqTj311LyMMRc0Gg0EQUAikZD1CT0VWCCnJA65M9oskORijM/zPILBICXFPp8PHMfR6vipqSm0tLTMeHgsJuQ+BnLhSN3udChFd4vJV1+F78EHp1+oVKj68V1QOh0FGSsTiKUXANDZ2YlYLAaj0YjBwUF0dXXRTmhEnlHo9sECBNqC+ottX4SCK24WkxVyWo6j9JGSET733HP4xje+gS9/+cu4/PLLaX/7rq4u3HXXXbjwwgvxxhtvYPny5XkPqLm5GRUVFdizZw9OPfVUVFdX01bYBPF4HF6vl+qYq6urMTIyIvkMeZ1O6ywGkWlEIpEySWY4DhZIciH2A/FZJYV2hBQTU/bm5mZJIc/w8LAsE6J6+6NQdf0FtepjAJxQ9PGBsuyhjMIidvAgxn54HX3t/O53oFu7VvIZFgiJwWBAa2srgGn3GpJpJqRZq9VKCgHzSZoFQcCu6C4cCB6AWW3GJ5o+kZfvzTYGuY8Ba3GU5RaFwQxGODExgXvvvRcXXnghfvvb30re+9jHPoaPfexjOPPMM3HHHXfg//2//5f3k+TAgQPweDy0f/j69evh8/nw/vvv4+ijjwYAvPzyy+B5Hscddxz9zLXXXotYLEaboLzwwgtob2+fU2oBHCbJLOqSy81EZkJukjxfENN1caaYdCqy2+0zSHG67yg2VHv+BdXBd2CsaSzppfYy2EchzgEhFsPo1deADwQAAMZNm2C5oLha21ygVColndAIafZ4PDhw4AA6OzslpJlkmnOFIAgYiY9AySnx6ZZPQ68qfoMxVshp2d2i9DGDJEciEXR0dODOO+9M+Qc8z+Mb3/gGvvWtb2U0QDAYxJ49e+jrvr4+bN26lV6wN910E84991xUV1ejt7cXV111FZYsWYLTT5/u5LVs2TKcccYZ+NrXvoYHHngAsVgMl19+Oc477zzqa/zFL34RN910E77yla/g6quvRkdHB+69917cc889GcVIiDWLJJkVclqWWxyOIdvxiak66WiXTIoXL16cVXMBWSbDaBDKgTcAAEO2j8BV/AjKYAxyz0v5vg689/4ckR07AACqRYvguvGGlGPITUjmGj+ZNMfjcZpp3r9/Pzo7O6HT6WZkmrMZf5NlEy47+TKoZPJJl/sYsBYH65rkhYwZZ7hCoYDX60VDQwP9XTAYxI4dO7B+/XooFArU1tYicOhpey689957OPnkk+nrK664AgBw0UUX4Ve/+hW2b9+O3//+9/D5fKitrcVpp52GW265ReKV/Mgjj+Dyyy/HqaeeCoVCgXPPPRc///nP6ftWqxXPP/88LrvsMhx99NGoqKjA9ddfn5H9G3DYl7lMktmOgxWSTGJId/GLSTHJFPM8D6vVSkmxyWTKOQMhx7FQ9b0KLhEFb29CUFsr2zGQ0/qvjNLF5CuvwP///t/0C7UaVT++CwqzWd6g0iBbYqZSqVBRUYGKigoA06R5fHwcXq8XAwMD6OjogF6vl5Bm0oZ+tvErDfLWRLBwTbIUBwsZ7VLEDJKs0WhgMpkQDAbpk+jevXtxwgkn0EyiIAjUPWKuE2Tjxo2z3lCfe+65OYN0OBy0cUg6rF69Gps3b57zu1KBtE1k0eFCoVAw4eFcJslSiCdHQRAQCoUkmeJEIkG9UBsaGmA2m/M6iRWdJPdOX6fxltPA8fJOxiwc/zKmIRdByOc5EDt4EGPXXU9fO6/8HrSz1NuwQoxyhUqlgsvlgss1vR5ESLPH48G+ffuwfft2GAyGlKTZH/GjP5h5I5VCgZVjUI6j9DGDJGu1Whx11FF44okn8J//+Z+IRCI4cOAALBYLgGm90zPPPIN169YVPdhCgeM4ZhuKsCBzIHGwQE7kjoNMRJOTk7SBx/j4OBKJBM0UF4IUp4qhaEjEoNr7MgAg3nI60DPJxLkgB47U7WYReakPSNYhf3wTLF/4wry/t5DINyFKJs2xWIxmmglpNhqNcDgceCHwAh7e9zA2mjZiAzbkLYZswQopZCUOluUWCx0pM8lf+tKXcNlll+EnP/kJBEGAIAg0qwxMW9BcddVVRQ200GDVK1luUliOY3oinJqaojcOAHj//fdhtVphs9mwaNEiWCyWoi53FXMfKA++Ay7iB693IlF7NLg9ua3Y5APlG0EZ+cQMHfINqXXIYshNjAo9vlqtRmVlJbWYJKR5ZGwETw88DQBwCS50dXXRTLO4kVcxIPcxYDEOVuUWLOyf+SCl6v6iiy6CWq2mXfaUSiXV7SqVSvzf//0f9WwsBXAcB7VaXdYkl+MAcJgUE0u28fFxxGIxWK1WuqJy/PHHF/3GQFDsSUdQ6RBv/jh4Sy2gONxQoYwy5EI+zr+FpEOWE4Q0vx96HxP8BOxqO461HAuO47Bnzx4Eg0GYTCaJPKPQcyMr5JQVd4tyJrlwSFua+sUvfjHtH5USQSZgNZOsUCiYICQskeR8QxAEhMNhqiceHx9HNBqFxWKB3W5HbW0tLBYLlEol4vE4BgYGZJ+Qinks+NqjMfWZh+jrI2nbCeTe5jJmYj7HZIYO+Xuz65DFkJugyTG+IAh4rPsxAMAn6j4BAwxYtmwZgOlaHq/XC6/XS0mz2WymhNlut+edNMt9DFiMgwWyXopISZI//PBDRCIRRKNRxGIxRKNRJBIJKBQK+Hw+nHfeeSV3QMqZ5CMrjuRMMSHFNpsNy5Ytg9VqpQWdyeMD8jtssHAs5AALN6QyprFQz8GUfsjnsa1DFkMOYrbdsx1d3i5oFBqcXn06JkYm6HsajQbV1dW0cVckEqHStO7ubkxOTlLS7HQ6Ybfbqe1qrmCBnJLzX+44ADb2R6kiJUneuHEjJicnqeSC4zhEIhHwPA+DwYBzzz1XYtFWCmCZJJcL9+YfR3KmOBKJwGw2w263z0qKU40vN4oZg2J4KwS9A4L1sCUkK+eCHGBhu2OxGBQKRUbna6GxEN0tvD+/LyM/5NnGZmEeKCYe2z2dRT6j8QxY1BZMYCLtZ7Va7QzSTDLNu3fvxuTkJCwWiyTTnC1pZuEYsESSy3KLwiElSd6xYwc4joNKpYJCoUA0GkV3dzduv/12qlcuJRB3C1ZJMgs35oUWB8lmEGIcDodhNpths9nQ3t4Oq9U6rxbkcu+LYo2ve+mHUA5vxdQn7kd86TlFGXMuyL3viw1x2+Hx8XEEg0EoFArYbDbaNMJqtR5xN8lctnfy1Vfh/8Mfpl8sUB1ysQliOB7G1rGtAIDz28+HEMxufK1Wi5qaGtpFNxwOU9K8a9cuhEIhWCwWOJ1OSprnmpvLJFkKFvZHKpTCXJ3yTBQ3EiGor69HZWUlzjnnHHzyk58sOV0yq5pkVsgpK9poIPWFR0gxyRRPTU3RTHFraytsNtu8SDEBK3KLoowzOQrl8FYAQGLRcZL3jrRmIsUEz/MIBAKUFPv9ftpWuLGxkc69Ho+HetsKgkCXs51OJ4xG4xGxr7JBbHAwZx2yGHLPg8UmRDqVDn87+294Z/gdtNpacSB4YF7j63Q61NbW0o65YtK8c+dOTE1Nzcg0J8/dLJBCVkgyiYNVCazc+2e+yIo1tLW1QaFQIBKJFCoe2aBWq5n0SWaFnLJC1kkc0WhUQopDoRDNFOeTFKcaH5CfJBdjfFXviwCARNVREExVkvHLyB/EHRq9Xi98Ph8UCgXsdjuqqqqwbNkySdtg4sZjNBrR0NAAQRAwMTEBj8eD0dFR7N69G2q1mhJmp9M5awe1+cQtF7JuDR+LYfSqq8FPTMsE5qtDPtKuAa1SixPrTgSQf4KaTJqnpqYoae7q6kI4HIbVaqWk2WazMUGSiQxSbnLKClkvVaRlEYlEAuPj4xgcHKRZOZPJhEceeQQ2m62IIRYHLGeSy5rk6Qpqn8+HWCyGrq4uRCIRmEwm2O12tLS0wGazFU0GxMJkVIxjodw7TZLjLZtkGT8dSiGLTbJnRBIUj8dht9tht9vR3NwMk8mU8Xgcx8FqtcJqtaK5uZnKMzweDwYGBrBjxw4YjUZKmB0OR0lI5rI5Ht5f/HJeOmQx5CZoxRx/bGoMTp0TCu4wESz0+Hq9HnV1dairqwMAhEIhSpo7OjoQiUSg0Wig1Wrh8Xhgs9lk0eezQk4JP5A7jlJFWpL8wAMP4Mc//jEGBwepT/Jpp52Gu+66S5LVKBWUNclsxUFIMckUT05OUuJQU1OD+vp62W70ch+TokyGsSmo+l8DMN2KuujjlxhIQwaSLQ6Hw9RisK6uLq/NaJRKJSXEZGyv1wuPx4Pu7m6JBpS4DeQ69kI4F0Jvvgn/7343/UKlQtVddy44HbIYxSLJgiDgW//+FiKJCG5ffzuWOpbS3xcTBoMBBoMBixYtoh72nZ2dCIfD2L59O6LRKGw2myTTXAzSzApJZl1usdAhIcnk4rv//vtx44034pvf/CY+//nPw2AwYM+ePbjiiivw9a9/HY888ggqKirkirkgYDmTfCSQ5FgsRgmxz+dDMBiE0WiE3W5HU1MTbDYbNBoN3n77bVgsFtkzYXIfk0KPr9z/Jrh4GLy5Frxrpm6zFLK5hUQikYDf76fZ4kAgQFv7FlIOlApqtRpVVVWoqpqWzITDYapn3r59O2KxGOx2OyXNFouF+f2c6fkX93gw9sPr6GvHt78N7YoV8x6b9f2TD2xzb0OPrwdapRY1xhr6ezm3n+M4GAwGmEwmmM1mtLe3SzLNBw4coI2fyKqJzWYrCIFkhSSznEkm7mgLGSlJ8oMPPohrrrkG3/ve9+h7jY2N+Oc//4ljjjkGBw8eREVFRUlNFqxawLGkSc6n7IOQYkKMg8EgDAYD7HY7Fi9eTElxqjjk3h9yx1CM8VVEatG8CUi6xkvlms8F6fY7KbYjmWK/3w+NRgOHw4H6+nrY7XZmbDN1Oh1dziZ6aEKa9+7dC47jJEWABoOByWM+Z/tonsfYtT9EwuMBAOg3nADrf15QjNAKimLddx/veRwAcGbjmbBqrZL35D4fSPMMjuNgNBphNBpRX18PQRAoaSZyo3g8PiPTnA/SzAr/KWeSC4uUqYxAIAC73T7j9xaLhS53lBpYJclyE7J8xRGPxyWZ4kAgQElxY2Njxl2ZWNgfck+MxRg/ctK1SDRsAG9bXPCxsoXcx5/EEAqFKCkeHx8Hx3G02G7p0qXQ6/WynytzgeM4mEwmmEwmNDY2gud5WgQ4PDyMnTt3QqvVSooAWSH7c8H/hz9gassWAICyogKVN98CrgTIUTHGd0+58fL+lwEAn2/9fNHHnwvpYkhFmicnJ2mmmZBmu91OSbPVas2JYLLiTcxKRrtUkZIkn3jiifjjH/+IY445Bm1tbQiFQlAoFLjllltQX18Pl8sFoLQOCsua5IVYuEdIMSHGgUAAer0edrt9Xpk1Fs45Foh6wcfXmBBv+0TKt+TcfrnJydjYGL3pxuNxWnXf1NSUVbEdqyD+yzabDS0tLbSAm1jNbd++HSaTCU6nEzzPyzY3zXX+hXfsgPe+X0y/4Di4brsVSmdp2ZYWEk/0PoGEkMBRFUeh3d4ueY9lkpwM8UMgcYIhKyderxf79u0Dz/M000zkRpmQZlZaQbNC1ksVEpJMDvhNN92Ez33uczjttNNwwgknwGKxYOfOneju7sYvfvELtLS0yBJsIVHOJM8vjng8Dr/fL8kU63Q62Gy2vC43s/LQILfcQm6wcE4WGkQSRDLFADAyMgKn04kVK1bAYrEw0fWukFAqlaioqKA1KNFolC5lj4yMIBqN4q233qJZ5kLpP1Mh3XXAB4MYveYHwCFLT9uXvwzDunV5G1dukljo8eN8HE/seQIA8B+t/1H08TNBrjEkr5wIgoBgMEgzzYQ0izPN6UgzC/uBxMECWU+FUrhPpMwk19XVYfPmzXjkkUfwyiuvIBwOY+PGjXjsscfQ1NRU7BiLAlYzySxpksVxkMIkUrEfCASg1Wpptb7dbi+INysLkxILDy6FHF/3r++At9YjtuYiCAb2CnQLte3J5/TExAQMBgMcDgdaWlrQ0dGBlStXwmAwFGT8hQCNRkNbDptMJoyOjqKmpgYejwf79+9HIpGQFAGazeaiXrOCIMB9222IHzgAANCuXg37f19atPGLgUKTszeH3oQ77IZT58Qpi05JOb7cyNc+4DgOZrMZZrOZkmbSyMfr9WLv3r20UY+YNJN7AAv3I1biKFWkLa9WqVS46KKLcNFFF0l+z/M8s08t80HZ3WJ2kKXV3t5e+Hw+TExMQKPRUFJss9mKYg3Iwv6Qe0Iq5D7ggsNQd/0FAjjEjvpS2vHlQj7HJjdEcbGdWq2m5/SqVaskqx9yH3cWoVQqsWjRImrPFQwGaRHgnj17oFAoJHrmfD1gpDv/g08/jeA//wUA4EwmVN5xB7g8O+GUOik5sfZE/O8p/4vx8DjUypn7joXtL1QMHMfBYrHAYrFg8eLFEtLs8XjQ29sLALDb7TAYDBAEQfb9UZZbFBZpSXIwGERHRwe6u7sxOTmJaDQ6/ZTuduOiiy5Ca2trMeMsOFjtuCeXvCCRSGBiYkKSVRMEAZFIBDU1NVi+fDl0Op0sF6fcJFnuGAq5z4mrBV+zBoLRlXZ8Fo5BtiBFx+ImHgBgs9ngcrnQ1tY2p5PDQtzuYkGclVu8eDF4noff74fH48Hg4CC6urqg0+kkpDmTYt3ZxhMjum8f3LffQV+7rr8O6kV1OX8/qyg0KeM4DkdXHj3nZ+REsYhpKtI8MTEBr9eLkZERxGIxvPTSS5JMsxyrJ6wmLkvOAo7gwIED+OpXv4rnn38eVqsVarUaCoUCBoMBQ0ND2LBhA1pbW0sqq3ykZ5LJDY0U2k1MTEClUsFut6OmpgZNTU3YunUrli+f6ZlbTLAgP2GBJBZqfNKKOt788YJ8fz6QzbZHIhGJAwXxUCWuKsW+oZUS5joOpLW23W7HkiVLEI/HaRHg3r17sW3bNpjNZklTk1y9o4VoFKNXXQ0hHAYAmD/7GZhOPz2n75pzLAYyqYUaP8EnoFTMrrNnYfvlikHc3dJisWDHjh1Yu3YtPB4P3G43enp6oFAo4HA4qOyo0AW9LByPUoZkRiKk9yc/+QlGRkbw2muvYcOGDWn/uFQIMjCttQuFQnKHMQOFImTE6kmcKVapVLDZbCktrMKHbj4sQG6CKjdJLtiEGJuCcmAzgNStqMWQ+xikA3FVIaR4cnISZrMZDocDy5Ytg9VqLfliO1ahUqngcrmoO1I0GqXSjK6uLoTDYdhsNkqaZ7PmSj7/PPfcg+ju3QAAdXMznFddVdiNkRGFuvYmohP4wr++gE31m3D5UZdDq0xdaM0CKWMlBqVSKWkJT+6rXq93BmkmP/kmzWW5RWGR8rF9//79OP300ylBTr4oS/GAsOpuQTKn850UyMVLMsV+vx9KpZL6ura3t8+61Ex+L/fkJDdBZSGGQo2v7N8MLh4Bb64DX7Fs1vHlQvLYZAWEZIvFVoNNTU2w2+2yd2csZcznXNBoNKipqUFNzXQ3t1AoRElzf38/eJ6XNDVJJhfk/5Ov/hsTjz42/TuNBpV3/giKAtZHyD3/FGoOfqbvGYxNjeG90fegUaSXwci9/SQGuXlIqhjEFoqENJPOm6Ojo9i9ezdUKpWENBuNxnltC6tyC8JbFjokJJkcqOOPPx59fX3Yv38/6uvrZT8ZiwFWSXKu5FTcAYz4FSuVyqz0l/mII9+Qm6CSGEoRqr0vADiURZ6rm5lMx0AQBITDYQwMDMDr9cLn81FZUCFdVYDSPe6swGAwwGAw0CYQgUBAsoytVCopYU4kEgCA+MgIxm64gX6H43tXQNvWVvBYS+1c4AUef+75M4Bp27e5dPlyb/9CiUEsOWppaZGQ5uHhYezatWvepJmFfVHKSEmSzznnHFxyySW4+OKL8aUvfQlarRbRaBTxeBxerxebNm3C6tWrS+rgkG1kDWJyOht4nkcwGKTyCb/fTzuAOZ1OLFmyZF5PrJnGUWiwQJIB+Qv3ClLMqdJD0FoQbzltzvGLBVJsR87rsbExAKBkqbW1ldm2yWXkDnHBVFNTE3ieh8/ng8fjwYEDBzAxMYFdXV2Y/O2DUPp8AADDySfD8oUvFDw2uTN3hbjvbhnaggPBAzCpTTij8Yw5Py/39cYC98glhlSkmcjDCGlWq9US0jzX/FaWWxQWKTXJv/3tb/Hqq6+isrISl112GRQKBZRKJXQ6HYaHh3H//fdj9erV4Hm+ZPR9KpWKWXcLYCYpI5kWcatnjuOopm++pDjTOIoNFkgyCzEUYvzIKTcj8rHr5swiF2p8gmg0Kim2i0QitNgukUjAbDajubm5YOPPBrmP+5EKsa6ztbUVW7ZsQcXmzVB2dQEAYlYr+j5xFvzd3bQIsFTuTckoBEH8U8+fAADnNJ8DvWp2qYrcDwkkBrmJYT5iEJ/XwLSrFCHNxBFGo9HA6XTSzyW3u2fheJQyUnbcu+GGG3DNNddApVJRZwulUjnjhCilSUij0TCZSSbHRCyfSCbFdrsdzc3NBa2iLZNkaQwlO34KX9RCj0+K7ci5HQwGYTKZ4HA40N7eDpvNRueanTt35nXsMhYmVP39UP7x8ekXHIeaO38Ec2MjPB4POjo6EIlEJE1NMm01nAnknn/yjQPBA3hz6E0AwOeXfH7Oz5cKQZ0vCpHBFUuKAClpPnDgADo7O6HVaiWZZpYzySVrAafT6aBWq6nwmud5JBIJCIKAeDwOrVZbcsUwGo2GqUyyuF0mAGzZsgUAKCluamoqqn1VmSSzFUO+x+fG90KwNWWURZ4vxBXgxFlFp9PBbrdj8eLFsNls8/LPLaM4kOsa4ENTsD74IHBIl2y7+MuwrF8PC4Da2loIgiApAty3bx/tmkYIyHxX2eS88eebID7V+xQECFhXvQ715vqij58LjpQYxKS5tbVV4t5DSLNKpQLHcTh48CDNNJeRP6Qkye+//z6eeeYZGAwGRCIRxGIxRCIRKJVKeL1enHXWWTjnnHNKzidZzsI9QRAwOTlJs8Tj4+MQBAFWqxUAsHz5cjidTtn2N0skmQXIrUnO5/jcxCBMD54E3taIyYteAlSzF75lOz45twkp9vl8VJtHGtNkOrGzcvzLmIYcx8Nz991QjYwCALQrlsN+qbTtNMdxMBqNMBqNaGhooA0gPB4PdRhQq9WSpibZFHvKTdDyPf6nmj+FhJDAMZXHZDy+3JD7GJAYin0/VqlUqKioQEVFBYDpVbienh6MjIxgYGAAHR0d0Ol09IHQ4XAUrJD5SIGEJJMT78MPP8Ttt9+OxsZGANNL/vF4HGNjYwgGg1ixYgX9fKmg2M1ECHEQa4p5nofVaoXNZkNDQwPMZjMUCgVefvllmEwmWR9IyIQkR/e/5DjkPu/kjiHfNwfSZU8wuOYkyJmCFNsRYszzPF0FaWlpyatevowjB5Mvv4zAX/86/UKrhev2udtOixtAEFsu0tSEEAuDwUAJs8PhKLmV0tlQb67Ht9d8O+PPs0JQyzFMk2aj0QiTyYRjjjmGNuzxer3o7+/H9u3bYTAYJPKMMmnODindLb761a/iq1/96owPP/PMM3j55Zdx5plnAig9TXIh5RZkCVCcKU4kErQgSUyKk8FClzlAfnJYjuEw8jk+tX5rnr2ByGzjR6NRSROPcDgMi8UCh8OBRYsWlYQmVO4b4pGO+Ogoxm66mb7WXPoNaBY3Zv09CoVCovuMxWIYHx+nVnPBYBBWq5V+RqyJB+RPDrFAzuQen4V9wEIMyXEkN+wh57bX68W+ffsoaRYXAmq1qZvGlDGNjHqAElnF2WefjTfffBPXX389Hn30UcTj8ZzbiLKGfBfuEVIszhTH43GaKc6GOBTM8itLsEAOWYmhZMaPhaAcmC7aibdk1oqanI8ej4dOwKTYzm63o7W1FTabrSBzg9z7vgx5IPA8xq67Hvwhu7fwmqNgOJSsmS/UajUqKytRWVk5/d3hMNUzb9++HbFYTFIEKDc5ytf4A4EB3LftPnxuyedwXPVxRR9/PmAhBlYK5maTfSSf24Q0ezwe9PX1Ydu2bTAajZJMc5k0SzHrXUxMRnieh9frRV9fX8kQYzHUavW8MsliP1dCjOPxOCwWC210MFub1dnAAjFkKY5yDPkbX7XvNXCJCHhrA3hn+iYMxF2FEOJdu3ZBq9XCbrejsbERdrv9iCi2k/u4H6nwP/IIpt56CwCgdLngv+ACOAtEUHQ6Herq6lBXV0dlcR6PB16vF3v37kUikYDBYKDWXAvVp/vJ3ifxyoFXEE1EyyR5gcaQbRzJpFlst7l3715s27aNOguRnyNhXp8NKdnuvn378OSTT0Kv1yMcDiMWiyEWi+Gtt97Crl27cMcddwAoLblFtppk0vlLbMkWjUZppri2thYWiyUv+4gVcspCHCxk1eXeD/kcXymWWiR5b5JCUvJDiu00Gg3q6upk68Yp9zlYxjSKdRwiu3fDe+/P6WvXrbfgQCJRlHOP4ziYTCaYTCY0NjZCEAS8//77EAQBIyMj2LVrFyXLxSqUygc5iyQieHrv0wCAc5ecW/Tx54tyDIcxn4y2RqNBVVUVqqqqAEyTZq/XC6/Xiz179kjsOIn/+JFGmlMW7u3YsQPf+9736NKSUqmEwWBAe3s77rrrLnz6058GUFpLn5lokpMzxdFolGaKa2pqYLVaC/LgIDcpI2BBG83CvpA7hrxddwIPVd8rAKalFuShj+iK4/E4bDYbHA4HmpqaqA/3Bx98ALVaLcv1X0pzThlzgw+HMXrND4BDzkPWL30JhnXrgDfekCUejuOgVqthMpnQ0tJCfWzdbjctlDKZTJQ02+32vBcB5oOcvbL/FfijflTpq3B8zfFZjy83WCCorDTxyGccGo0G1dXVqK6uBiAlzUSvbzabJZnmuc5vuY/TfJGycO/ss8+eNVtXStZvBESTLL74kjPFkUgEFosFNpsNy5YtKxgpToZCoZA9ewrITw5ZikFu5GMfxKJRDB93HZR9r2DHQSC0dwudAGtra9PKg1jY/jLYQKHPBe9P70Fs714AgKa9HY5vXl7Q8TIF2e7k5g9iUrFr1y5MTU3BYrGgoqICDocDdrudiXvnE71PAAA+1fIpqBTZySdZIajlGKZRSG10MmmORCL0/O7u7sbk5CRNFBbqoVBupL06SNvj4eFhjI6OguM4uFwuNDQ0lKSFiEajQTgcxgMPPIDXX38dK1aswPr162E2m2G329He3g6r1SqLHpsFYshKHCzEAMjvk5wLEokE/H4/zRYHAgEYjbWwr7wcLQ5HVsV2cm5/2d3iyMDkv1/DxOPTXfU4rRaVP7oD3KGlXrnPv3TnQjKpmJqaonpmcREgIc0WiyXr82q+5KzP34cPxj6AklPi082fzuk75L4WWCCoLMRA4ijWg5dWq0VNTQ1qamoAHE4kejwe7Nq1C6FQiLoaOQ7dUxY60t4R9+zZg6uvvhrPPfccfVKpqanBJZdcgm9/+9slQZQHBwfx6quv4pVXXsGzzz6L0dFRPPTQQzjuuOOwYcMGHH/88UwUKbJCDFmIoxxD5uOTB10in/D7/VCr1bDb7aivr4fdbi9XMpfBJOIeD8ZuuIG+dl75PWiamyWfYYGgzAW9Xo9FixZh0aJFVOfvdrup5pPY0TkcDlRUVECv18+5XfMlZySLvKF2AyoNlVn/PQvkkIUYWHK3kCsOnU43gzSLV1KITG8hIyUDPHDgAC6++GJMTU3hmWeewZIlSxCNRvHEE0/g3nvvxdTUFG688cYFK7t48cUXcdlll2HPnj1Yu3YtTj75ZFx55ZW4/vrr8fbbbzNx4oshNyljKQ4Wjg0L+yEVxF7cXq8XvkN2WXa7HS6XC+3t7fQmzIXc0Lz1Y8SbT0Wifn1W48h5DOQ+/iwed7lQqH0hCALGrr8e/Pg4AMBw0kkwf/7zBRkrF+S63eIiwMWLF9P27B6PB8PDw9i5cye0Wi3NMjudzoI8xC6xLUGzpRmfbflsTn/PAkEtx3AYLPEwnU6H2tpa1NbWguf5kpgvU+7ZAwcOYNeuXXj66adxyimnoKGhAUuWLMFVV12Fa665Bo8++iiA6eXbTPDaa6/h7LPPRm1tLTiOw1NPPSV5XxAEXH/99aipqYFer8emTZvQ09Mj+YzX68UFF1xANcFf+cpXEAwGJZ/Zvn07TjzxROh0OtTX1+Ouu+5KGU9bWxvuvvtueDwevPfee/jxj3+MU045paDNROYDFgrmADbIYTkG6fiRSARDQ0Po6urCm2++iXfffRdjY2OwWq1Ys2YNTjzxRKxatQqLFi2SWFUp+16B5r0HoH31pnmNX8aRjUKQhIk/Po6p16cL85ROJ1w33jhjHLnPv3xst0KhgM1mQ0tLCz760Y9i06ZNWLlyJdRqNfbt24dXXnkFr7/+Onbu3InR0VF6f5ovOftU86fw+JmPZ12wRyD3vicxyE1QWYiBpThSgdW4skHKTLJOp4Pdboder5/xnl6vR0tLCwBkLNCenJzEUUcdhYsvvhif/ezMp9e77roLP//5z/H73/8eTU1NuO6663D66aejq6uLyjouuOACDA0N4YUXXkAsFsOXv/xlXHLJJZSwT0xM4LTTTsOmTZvwwAMPYMeOHbj44oths9lwySWXSMZraGhAQ0OD5HcajQaxQxXUrIEF2zMSh9wTJAsxyIl4PI5AIIBgMIi33nqLasDsdntWxaSqvS9Nf1/zqYUOOe84ko9/qSO6dy+899xDX7tuuRlKpyPlZ+W6ARfq/FMqlaioqEBFRQWAw0WARO85NTUFq9UKQRDg9/uh0+lyziDOZ9+xQMpYiYEFG1xWXDZSQe5jlA+kJMkNDQ048cQTcd111+H222/H1NQUlEoltm3bhkceeQSf+9zncPDgQUxMTECr1aI5SSuWjDPPPJO2sk6GIAj42c9+hh/+8If41Kc+BQD4wx/+gKqqKjz11FM477zzsHPnTjz77LN49913ccwxxwAA7rvvPpx11lm4++67UVtbi0ceeQTRaBQPPvggNBoNVqxYga1bt+KnP/3pDJKcCmq1GrFYjImLLxmsEEMW4jjSYuB5Hn6/n+qKA4EAtV9raWmBzWbLvpo4EYNq378BAPGmU7KOSc5jwMLxL6MwEGIxjF77QwiRCADAcv75MJxwgsxRpUYx7hHJRYChUIjKqLq6utDR0UFdBSoqKqhFYzrsm9iHbe5tOK3hNOhVMxNg2UDueyQL92kWYgDY0UanA8uxZYKUJFkQBPT19WHLli3461//ipUrV8Lv92Pbtm1wOBx4+eWX8cQTTyASiaCxsRGPPPJIzgH09fVheHgYmzZtor+zWq047rjjsGXLFpx33nnYsmULbDYbJcgAsGnTJigUCrz99tv4zGc+gy1btuCkk06SGF2ffvrpuPPOOzE+Pg673T5rHET7FY/HmTPLZoUYsJDRZmFfFDIGUmxHdMV+vx8qlQoOhwN1dXVwOBzwer0YHh6Gy+XKaQzl4LvgogHwegf46jX53YASxkKf7FnH+K9/g2hXFwBA3dQEx3e+nfazcrtbyAGDwQC9Xo+Ojg4cf/zxiMfjtH32nj17oFQqqZaZdAIU4/Hux/HnPX/GeyPv4Zb1t+QcBwvksBwDe3GUKlKSZI7jYLfb8eUvf5nufLVajVNPPRUcxyEej0Ov14PnedreMFcMDw8DAO34QlBVVUXfGx4enjEOIQ7izzQ1Nc34DvLeXCSZZOMikUiZJDMeh9wx5HNCErczJ9liALDZbHC5XGhra0vZ9nY++4BILRJNJwOK3JYLj0SSUkbhEN6+Hb7/+7/pFyoVKm+7FYo5HJSOxAJScu4rFAqYzWaYzWZaBOj3++HxeDA4OEilipQwWw34Z/8/AQCfbPrkvGOQm5SxEAMrGVyW5RalgJQk2eFw4K9//WuxY5EVhBizqEsuNxMprRgikQhtUuP1emk7c4fDgYaGBpjN5lknvflOzMq9LwMA4k256ZGPRHJCIPe5xxLytS/4UAij114LHJrj7JdcAu2KFXn57kKAxXOAtIy32+1YsmQJ4vE49a/du3cvXnG/gsnYJCo1lVisWIx4PJ6zvancBJXsfxbmArljANgh66WKWa+S5Mkg3eQwn6cYorcaGRmhXnvk9Zo1a+hnRkdHJX8Xj8fh9Xrp31dXV2NkZETyGfKafGY2kEwyiySZBWLIShwsxABkd6OMx+O0lbnX68Xk5CRtUpNr58ac90HYBy7ih8ApEV/8sdy+Yz7jl1FGEjw/+SniA/sBANpVq2D7ysVz/o3c55/cmeS5xlepVHC5XFSS9atnfwVMARvtG7Fr5y6Ew2HYbDaaaU7XXTNdDGWSzE4Gl5U4UkHuY5QPzEqSkzewEBvc1NSE6upqvPTSS5QUT0xM4O2338all14KAFi/fj18Ph/ef/99HH300QCAl19+GTzP47jjjqOfufbaaxGLxSjhfeGFF9De3j6n1AJgO5PMCjFkIY6FEANZ+iTZ4omJCeh0OjgcDjQ1Nc27dee8rkOdDZNffw/ceB+gsxZ//DJKCvM9F0KbNyPwl79Mf5dOh8rbbgWXYYZTTqLKOkkWY5d3F3b5dkGtUONr678Gu86OUChE9cz9/f3geV6iZ56tCFDu+Zclkix3DCzFUaooSju5YDCIPXv20Nd9fX3YunUrXV7+zne+g1tvvRWtra3UAq62thaf/vSnAQDLli3DGWecga997Wt44IEHEIvFcPnll+O8885DbW0tAOCLX/wibrrpJnzlK1/B1VdfjY6ODtx77724R2QnNBuUSiUUCgWi0Wjet3++YIEYAmz4NbOwL1Lpg4PBoKSJh0qlgt1uR01NDVasWJHXDpXz3gecAoKjJW/xFBtyH/8y8oPE+DjGbriRvnZ+73tQNzZm9LflcyBz/LV3Wjp58qKTYddNJ4wMBgMMBgPq6+tpsbDH44Hb7UZPTw+t+SGkOdkOtpxJZoecluUWhUVRSPJ7772Hk08+mb6+4oorAAAXXXQRfve73+Gqq67C5OQkLrnkEvh8PmzYsAHPPvushFg88sgjuPzyy3HqqadCoVDg3HPPxc9//nP6vtVqxfPPP4/LLrsMRx99NCoqKnD99ddnZP9GoNFomGwoUtYksxdDNBrFwYMHabaY53m6fLlkyRIYjcaCTlw57QM+AXAcwM1vaU5uC7gyFj4EQcDYLbci4fEAAPQbToD585/L6jvkzubKOXam2y4IAiaiEwCAc5ecm/IzHMfBYrHAYrGgqakJPM/D5/PB4/HgwIED6OzshF6vp4RZblJWJskz4yjLLQqHopDkjRs3zjqxcByHm2++GTfffHPazzgcDto4JB1Wr16NzZs35xynWq0uZ5IZj0Ouiy4ajdJM8ejoKBKJBMLhMOx2O+rr6+cstssnct0Hyr5XoHv++4it/AKiJ14zrxhYIArFRilM+PnEfI5D8O9/R+ilaZcVhc2Wsqsey5CboGc6PsdxuPOEOzEYHESNsWbuP8B0UsbhcMDhcKC1tZXW/xCruVAohK6uLlRVVcHpdMJutxe1qQYrJFnuhwXW4ihVpCXJf/vb3zA1NYVoNIpoNIpYLDbj30gkgttvv72Y8RYMHMfRhiKsgQVyykocxYohHo9LmngEg0GYTCZq3q9QKLB8+fKCx5EOuewDVd/LUITGwEUmChBRGUcicrk5xw4ehPuOH9HXFdf9EKocPb/lACsZxGxQa6rN+W9VKhUqKyupDeurr76K6upqRCIRdHR0IBqNSooALRZLQRMGrJBkVs4DVuIoVaQlyZ/5zGeg0Wig0+mgUqmgVCqhUqmgUqmgVquhVquhUChw6623MpvqzxblTDL7cRQqBp7nMTExQbPFpJukw+FAY2Mj7HY7Le7cu3cvIoe6gsmBnCZEQYBq36sAgHjTybN/thDj5wly3wzkPv+J/l2v18/QiS4ECDyPseuvhzA5CQAwnf1JmESNpDL+HgbmQzmQDUEcmhyCklOi0jC/Xgap4HK5YLfbIQiCpAhw3759EARBomfOt/SMJZLMAvdhJY5SRVqSrFarsXnzZhx77LHFjEdWsJpJZqFgDigtkiwIAiYnJyXFdsRrtKamBsuXL2eWhOSyDzhfHxT+AQgKNRL1x887hiNRbiEXIpEIvF4v/eF5HjzPw2AwoKKiAk6nEw6HI2ff22LC//8eRvi99wEAqpoaVFx9dc7fJbfkQc6xM9n2X3f8Gv/c9098Z813cH77+XmPgcRhNBphNBrR0NAwrYGemIDH48Ho6Ch2794NtVpNCbPT6Zx3ETMr1z8rGVxW4ihVzDqrhkIhALP7JZfSEwyrJJnjOCQSCbnDWPAkmXS2Iz/xeJwa8Dc3N89qe5SvGPKFbMdX7fs3ACBRdyygMc5r7PKEXFgkEgkq9fF6vQgGgzCbzXA6nVi1ahX1tPV6vXC73di5cyfVx1dUVKCiogJms5m54xTt6YH3vvumX3AcXLfcDIXZLG9QOYK1fZuMQDSA5weeR0JIYJljWd6/P932cxwHq9UKq9WK5uZmJBIJWgQ4MDCAHTt2wGg0UsLscDiytsMkpFDuY8AKOWVVkyz3PTJfmEGSyYFXKpWUmBXDL1lulDXJCyeOTGOIxWKSznbhcBgWiwV2ux11dXU5a+fk3g+5XH+UJM+jgYgY5eK5/IEsWZPiKJ/PB7VaTaU+yUSCzFVVVVWoqqoCAExOTlILr97eXiiVSjidTkqatVqtXJsHABCiUYz+z7XAofnVeuGF0M9jlVJur2K5s9hzjf/Pff9EJBFBs7UZR1UclfcYMt1+ch46nU4A03MyOc+7u7sRCoVgsVjoZ2w225xFgKyQU5biKKVkJWtIm0nmeR7hcLiYsciOsiZ57jjktqKbTXpCshaEGAcCARiNRlqlbbPZ8rIkzcLxyGr8eATKgTem/7t447zHZuHGIAfyedwJWSA/sVgMNpuNnqsGgyGr/Sxe8iYWXm63G/39/dixYwfMZjMlzJkQkUyQzb7w3v8rRLu7AQDqJUtgv/yyeY9/JCITYiYIAvVG/tySz+X9ep0POUx+uAuHw1TPvH37dsRiMVocTYoAU/nSszAHsZLBZWV/pAKrcWWDtJnkuro6qskkGriFoHmbD9RqNZM+ySyQMpbiIDHwPI9AIEAzxX6/HxqNBg6HA/X19XA4HLTYLp+Q+8LP+jjEpxBb8yUoRnaAd+Vn6ZUFXeZCAikMJVm0QCAAk8kEh8ORc2vydBBbeLW1tSEajdIsMyEiDoeDkuZCe3qHP/gQ/t/9bvqFSoXK22+DQubM9nzA+vm3zb0Ne/17oVPqcFbjWXn//nySMp1Oh7q6OtTV1dE6EUKa9+7dC47jJEWABoOBGVLIShyskPVSxQzWS9L2vb294Hkeb775Jt544w2o1WrU1dXhmGOOQVNTU9EDLQY0Gg2TmWSWmonIGYcgCAiHw4jH49i+fTvGx8fBcRzsdjuqqqqwdOlS6PX6okwYC0puobMh8rHr5Bv/CAWRUBAbQUJeFy1aBIfDkZUEgud5CIJAfxQKBdVlznU8NBoNampqUFNTQ90x3G433G43uru7odFoaAGg0+nM6sFyrrH50BRGr78eOHS9OP77v6Ftb8/4+9NBbqLKstTjr3ums8hnNJ4Bk8ZUkBgKAY7jYDKZYDKZ0NjYSB8sPR4PhoeHsXPnTmi1WlgsFgiCgEgkIquMiBWZAytxlCpmTQ1/4xvfwMMPPwyTyQS32w2r1Yply5bh3nvvLUnXi7Immb04wuGwRFccj8chCAKsViuampoyLrbLJ1g4Hkfq+CwT9Hg8Ts9TooG3Wq1wOBw5natkBY8QYwCUFMfjcfp/MWEmn0kHjuNgNpthNpvR1NSERCKB8fFxqmXetm0brFYrzTKTIsFc4f3ZzxDfvx8AoD1qNaz/dVHO35UMlomqXGOH42G8OfQmgPQd9vKBYmy/QqGAzWaDzWZDS0sLPVcHBwfB8zxeeeUVmEwmSRFgMVe7y5nkIwNp5Ra/+MUv8PLLL+PJJ5/E6aefjvr6erz55pv4zW9+g+9///t47LHHUFOTWQefhQJWM8kskLJixRGLxeDz+Wj2bWpqCmazGXa7HStWrIBSqcSHH36IxsbGgsYxG+SekLIaf2ocyuGtSCxaB6jzY2kn9/azcC0A03EEAgF4PB7qra3X63PWwBNCTP4lIIXUSqWSkmIyPvm8+LMAKHEW/y4VlEolJcTAYY2o2+3GBx98QD1vyWcMBkPG2zP19tuYePzx6Rh0OlTecgu4InZmOxKhU+nwt0/+Da8Pvl4QVwtAPnJIzlWVSgWPx4MTTjiBypd27dqFqakpWK1WSRFgoZuayD0XshRHMlhwIMkH0pLkRx55BJdddhlOP/10RKNRJBIJDA0N4eabb0Z9fT2Ghobo8l0p7AigrEmWIw5id0UycKTYzm63o6WlBXa7XUI0Jg81IZATch+PbMZX7X0R+me/i0TtMQid/1RhAysC5J5rotEoBgcH6UOcIAiw2+2orq7OyVubZIuTiS4hxEqlMu2NXnwTIueDWJJBPpMpYQZmakQnJibgdrsxNDSEnTt3Qq/XU8I8my0lHwxi7IYb6WvHt78NdR4fbOXO5sqFTLbbpDHhjMVnyBpDIUHG12g0qK6uRnV1NYBpi0+iZ96/fz8SiYSkCDDftohy7wdxHGW5ReGQNs3h8XhoBapCoaDd9oDpg8JixnW+YNXdgiVN8nxvECT7RkiG3++HWq2G3W7PSKspN0ElYCGGTEC77OWhgQgBK8egGCCOKV6vF5FIBJ2dndSyqr6+HmazOasbVKpssZjIJmeLM0UyCRaTZvLgT74zU9Is9rxtaWlBPB6n3sy7du1CKBSCVquFTqdDRUWFxInAc/dPEB8aAgDojj0WlvO+kNX2sA45yVG6scPxMHSq+TXqyARyk8N04+v1eixatAiLFi2i2ntCmvfs2QOFQiFpapLNqkgqsCBzIA/EcsdRykhLkuvr63Hw4EHqaqFQKDAwMIDXXnsNLS0tcLlcAOTP7OQTZU3y7Mil858gCJiamqKkeHx8HABgt9vhcrnQ1taWld0VC/tC7hgyHl8QoByY1icmGk8scFTFQyH3PamwJ8u45CHO6XRCrVajra0NlZWZt/kVa4qTs8UKhYJmivOdCUpFmsVxiIv+Mi0AVKlUqKyspNvf0dGByclJTExMoK+vDxzHTWtD9/Yh/uST0+MbDHDddCO4PG+f3NlcFse+7q3rMDw5jCuPvjLv3sjJ47NIksUQa+8XL14Mnufh9/vh8XgwODiIrq4u6HQ6iZ452yJAFjK4LByPdJD7Pp0vzCDJZGefcsop2LNnD0ZGRlBTU4Oqqipcc801mJycxN13342WlpaiB1toaDSaMknOQxyRSITKJ8bHxxGLxWC1WmG329HY2DivZS8Sg5xPzywcj0zGV3h2QxEag6DSIVHzkaKPv1AQjUYlnsWJRAI2mw0VFRWSh7gtW7ZkpDFOJ6EgZJhYvRXzBptOmiHOhmVTAAhMJxXMZjOWL19OSYi7rw+Rn/0MRHkc+88L4NNo4Egk8mZxxwJYK9wbDY3itYOvISEkYFLn39FCPL7cyGXuVygUtLvqkiVLaJEtsZrbtm0b7WrpdDpnyPzyFUe+QY6H3GS9lJGWJH/9619HR0cHfbr6z//8T4yPj+PrX/86lWGUGljNJOeSwS0E0pFDMuGQn8nJSZjN5oJ4wMo9KbEQQ6bjKwdeBwAk6j4KqPJnlSTnQ0I+9j0hdIQUBwIBer6uWLEia0eH2QruCCnORUJRKKTLMpP4xUQ5U2kGISGxu+5C0O+f/t0xxyB60kno7OxENBqVtM3OhyvNkahJBlJv99/2/g0JIYG1rrVosRY+gcV6JnkuqFQquFwuuiJOvMQ9Hg+6uroQDodhs9koaU41J7BEkuWOo5SR9lGpoqICGzdupK+/+c1vAgB8Ph+effZZrFmzhgrmSwXlTHJmcRCSIS620+v1sNvtaG5uhs1mk7TRzXcMgPwTlNzHI5PxqdSi4QRZxmcFRPJDXCh8Ph+USuW8ms7Mp+CONcxWACiWZpDtSSfNCL74IoL//BcAQGE2Y9Htt0FVVUUlLG63m+pDVSqVpG12IZr+FBIsEfQ4H8dTvU8BAM5tKZztm3h8uefefI8v9hIHpj3OCWkeGBhAIpGQNDUxmUyy34MA0PlH7jhKGRn5E4VCIQwPD+PVV1/FCy+8gCeeeAJPPvkkzjrrLPA8v2BuBnOB1cI9jpO/iUcwGKRd7V577TWoVCrY7XbU1dXBbrdDpyt8wQgwszBJDsj90JLRhMjHodq/BQAQb9hQ/PELiEz2fSwWk3gWR6NRag/V0tKSdZc5cv3F43E6R4glFCTjutDnwtkKABOJhESHSfaJIAjgveNw33ob/R7nNddAdWjFkeMON4kg+lDizbxv3z5s374dFotF0jZ7rv3Iqi64GGMnn7dvDL2BkakR2LQ2nFJ/SsHHB0qPJCfDYDDAYDCgvr5eYvXodrvR09MDpVIJQRAwPDyMmpqarF1t8gWW5RaZ1DksBKQlyfF4HJFIBO+++y6eeOIJ/OMf/0AwGMQZZ5yB559/HscfP10tz+LByRVlC7hpkMwbIRk+nw88z0Ov10OtVmP16tVZFdsVKka5wAJJnnN8TonQ+U9COfAm+MqVeY+BNbkFaVEubvtsMBjgcDjQ3t4Om82WleQnVcGdTqdDZ2cnXYbNl2yAZYhJM+mARjLCgUAAra2tiMfjcN96C/hDRbmGk0+G6RPp2yGLXQaA6RoGQkC2bt1Ks3Zib+ZU+5hFh4lCI9V1Rzrsnd10NjTKwmbkjxSSLAbHcbBYLLBYLGhqagLP8/D5fHjnnXcwPDyMnp4e6PV6SRFgsVZGypnkwiOtT/Jf//pXXH/99RgcHMSJJ56IW2+9FZ///OeL2tGm2NBoNJiYmJA7jBkoBikjxUtEVxyJRGixXUNDA8xmM0ZHR3Hw4EEYjcaCxjIbWMkky425STIHvmIp+IqleR+bhe0HQF1TyHkLAA6HA7W1tXA4HFmvbsxVcLd27VpJs429e/dCo9FQwlzsjl/FQDgcpqTY6/VSB4vGxkZKBoL//CemXn4FAKCw2eD4nx/M0GbPBq1Wi9raWtTW1kqydqOjo9i1axd1ISCts9VqtezZXDkh3p+DwUFsGZpeMfpsy2cLPvaRSJKToVAoYLVaAQDHHHMMFAoFfTjfs2cPgsEgtYkkRYCFKlpNriEoI/9IS5Jfeukl9PT04J577sFFF10Eo9FYcjeAZLCaSS5E4V48HofP56PZ4snJSZhMplkzb3JnUEkMgPw3qjJJL/72x+NxBINBBINBvPXWW5iamoLFYoHD4cjJNSWdZ/FsBXdGoxFGoxENDQ20Ta7H40FPTw+mpqYWfJaZSCGIHnNycpLKVBYvXizxQgaA+NgYfHf9mL62X3MNOLtd0jYbyM6bWZy1SyQS1Ju5p6eHts0mZFquFS1W3C0qDZW4+8S70enpRL25vijjA0c2SSYxANP7IdkakayMeL1edHR0IBKJSJqaWCyWvK3As7AvUoGswpUC0rpbXHzxxZicnMTNN9+MO++8EyeffDI+8YlPYO3ataipqYHNZit2rAUHy22p56tJJkulJOs2MTEBnU4Hu92OpqYm2Gy2OZeIyiT5cAxy74dZx09EoXvhB0jUrkVsxX8AeV6CLdakLG4IQPTwxLM9VTfGuUCuobns2TK9gYlbOre3t2NqaopmXfv6+uj75OZYqGLW+YIUKbndbni9XuoL3dzcDIfDkTZuQRDgufkW8IEAAMBwxukwnfZx+h75dz7ezEqlUuJCQAowfT4fOjo60NHRISkALIY2lKUstkqhwsfqPoaP1X1MlvHlAAvEcLaHheSVEXER4L59+yAI063eiaQo2/oIMVhoaFLqSEuS161bh3Xr1iGRSOCf//wnfv/73+M73/kObDYb1q5diyuuuALHHXccEydsvlBK7haEYBD5hM/ng0KhgMPhQE1NTU4tdFkghyyca3Lvh7kcPhSjHVB3Pg5V73OIrfpiQWIo1PZHIhGJZzHP87Db7aisrMTSpUtpwRchTXNhtg53+S640+v1qK+vR319PdUtEsK8Y8cOmpFN7k5XbJDsLCHG4XCYZrqWLFmScQY8+Le/IfzGGwAAZYUTjquvpu/NVgAo9jnP1puZdFXr7OzE+vXrEYvF4Ha7aYMIg8FAH0wKKX85EvXQrMTAAufINKPOcZxk9UkQBJqsGhsbQ3d3N30oJe4Z2dyXxYW0ZRQGs84gPM9DqVTi7LPPxtlnnw0AePrpp3HnnXdix44dJUeSVSrVgibJ4mK78fFx8DwPm80Gu92eU0V/rnEUEiR+Od0+5D7f58y+HXwPAJCoPQbg2J5AE4mExLM4GAxSU/9Vq1bNWJok2uN0mM2zWNzdrtA3FvJA6nA40NraSrXMxFKKaHvJT7bdvrIBsWAjpNjn80Gj0dAMeLYZeQCIDw5h/Cc/pa8dP/whlId0mqmQijTPx5uZ/I3NZoPNZsOSJUsQi8WoNGPnzp2U/JMs83yaGLECst2CIOCb//4mVjlX4YvtX4RZYy7a+ECZJOe6HzjucKt3UgRI7tn79+9HZ2cn9Hq95EFvthUoFvZFqWPWmZHcSAKBAMLhMLRaLc455xycc845Mz5TCtBoNAtKkxyNRmmm2Ov1IhKJUI3mokWL8qp9AtggySQOucHCfkg3QSoH3wUAJOqOLci489n/ZPmRZDJ9Ph/UajXVFc91UyDfIUYmHe7knqd0Oh3q6upQV1cncYkgN0byYFBRUZF1M5NUiMfjlJR7PB7azMPlcmHp0qXz0vJOyyxuhjA5CQAwnnMODCedlNV3iElxqiwz+cxshDn5tVqtRlVVFW12JX4w6O3thVKplEgzcn0wkZOYkH3z/uj7eGv4LWwd24rz288v6vhyz7+sxADM/14kdnppbW2l1pWkziEYDMJqtVJpRnKtEMtyi1IpKJyVJMfjcTz77LP4y1/+Ar/fD6fTiY997GM444wzMl7uXEhgWZNMfErFxXbBYBAmkwl2ux1tbW2w2WwFLa5kiSTLLXeQe/y0EARRJrkwJHl6mMy3n2T4yE8sFoPNZqNZ1mwIm/haSCWhIBnjfEkoCgGFQiHJgIq7fW3fvh08z0saF2Sy/Jrs5er3+2EwGOB0OrF8+fKsLfBmQ/CvTyD8zjsAAGV1FRzfu2Je3zebNGO2AsC5IF7mJvIXt9uN/v5+7NixA2azWeLNnOn+kXsO5DgOj/c8DgD4RNMnYNFYija23NtOYpCbfIk19vmEWq2WFAGGw2G6OrJjxw76sEtIM8skuVQwK6O67bbbcNttt2Hjxo3o7+9HKBTCu+++i5deegn33XcfzObiLPEUC6y1pSber6Ojo+B5Hq+99hq0Wi3sdjsaGxtht9uL2qlKbnLIShwsjA+kvmFxvn1QhMYgKDVIVK8u6PjpIC4SJX66xDkllzblYs/iRCKBUCiEgwcPUps3VrLFuULc7YuQXbfbjaGhIezatYuS3WQyJybXHo+H+gvX1NRg5cqVBSliiw8OYfxnP6OvndddB0We7wOzSTOINAc4vIKQCVkRy1/a2trovnO73di+fTtisZjEm3kuaZqcmWRvwot/D/0bAPCF1i8UfXy5SdmRFINOp5MUAU5OTtJ5ta+vj94D+vv74XQ65y2pLGMm0lrAkc56v/3tb3HhhRfi8ssvh9FoxI9+9CNs3LgRDzzwAL7//e8jkUgUzAOw2JCbJJOLgEgoxsfHoVAoYLFMZwqOO+44GAwG2eIrhBVdLmCFpMqNVPtAOTidRearVgOqwnVBTB6bSCiIHp6QkkWLFsHhcGS9tE0IUPLye0VFBeLxOMbGxtDb2wuj0Uj1e5l0amMdHHfYAq25uZlm4T0eDzo6OhCLxaDT6SAIAsLhsES/XejtFwQBnltvgRAKAQBMn/4U9OvXF2w8ABKdscfjQTwepw9bKpUKiUQCALIuAEx+MAkGg3C73XC73eju7qaabZLNZ6VttiAIeC3wGniBx3FVx6HZ2lz0GOSe/44kkiwGxx3uXEmKAPv7+9Hb24vR0VHs3r0bGo1GsgpVrE64pYy0meSuri44HA6cf/603onjOPT394PjOKxduxYffvghADaWX/IFOdwtyHIKIcXxeJwuRTc1NcFkMiEWi+H111+X/YSXm5yyEgcL46eDwtcPAdx00V4Bx+d5HmNjY5QYh8Nhqp0j5202N5G5Cu6IhEKn02HJkiUApgkUyQbu2LGDyhQIuZH7eskHeJ5HIpFAPB4Hz/M0a072UTweRyKRoC2jC4ngU08h/NbbAABlVRXs3/1u3sdIJqxENlJRUYEVK1bAbrdLHgTEKwzJBDkbb2az2Qyz2Uy9mYmLSm9vL/VmJllmOZe4g7Eg3gy+CQC4YOkFRR//SCWoLMbAcRwMBgN0Oh2OPfZYKsckxcE7duygK3gVFRWw2+3M2lCyjLQkmdwIicZVq9XSHez3++lSntwnSj5RDJJMhPlEVxwOh2GxWGC321FbW5uyaGe25fViQm5yKIbcccg9froYoidciejRXwPH5/c8Fmteh4aGEA6HEQqFqK44Fz18uoI7QojnklCo1WpUV1ejurpaIlM4ePAgdu7cSbPM+SqGKwbE1nFut5sW7jidTjQ0NMBqtdL5QGzltnv3bomV23z9V5MRHx7G+E/voa+dP7w2bzILUmSYnC2urq6eUzaSTQFg8ufTQex/DUDSZfGDDz5AIpHAzp07UV1dTdtmFwvPDj6LiBBBi7UF66sLm8VPBRbIYTmG1HGQwlTS7l28CrV7926EQqEZnQAXwpwoN9Le1aqqqiAIAgYGBtDQ0ACVSoXBwUH89a9/xbZt23DDDTcAKC13i0LILcQWV+Pj4wgEAjAajbDb7RmTC7HtmZzSFlZIstxxsDD+rNBZkY/oyCoHOXcFQYDdbofFYoHBYMCaNWuy+r7ZPIvnW3CXSqYg1pyynGUmDTJIMw9ys2tqaqKtn1MhudFGKBSiRLO3txdqtTpjK6nZMC2zuE3iZqE/4YTcNhbSbDFxOCG661TZ4kwxVwEgcPh+lWmWGZA6kwiCgBdeeAFmsxlDQ0PYuXMntewqRmvyjzo/iu6xbpy57ExZSBoL5JCVGFjgPrOtaiS7vYhtKIkOP7kToNz7lUWkbSaycuVK1NfXY/PmzbjgggvQ0NCAu+66C93d3fj2t7+NT33qU0gkEkycKPmCWq2et7sFKbYjmeKJiQlqcVVfXw+73Z61PrOcSWYrDrknkkKdD2S5jhDjUCgEs9lMz12z2QyFQoH9+/fD5/PN+X1iTbE4WywmxYXyLGY5y0z2MyGJoVCILuc3Nzfn7OdrMBjQ0NBAW2aTMXp7e2c0M8lmjMmnn0H4zeklfqXLlZObhdiSzu1200K5qqoqrFixoiBFhukKAEk84veTNc2zfSfHcaivr4fJZEI8Hqea6V27dtHW5OTcyjfxWGRYhAtcF+C4xcfl7TuzASsEVe4YWHGVyIasJz/sEYtEj8eDvXv3guM4iZ45Hy3fWdhH80XaR94VK1bgoYceopPKOeecg6VLl2LDhg00s1EqBXsEWq0W8Xg8q4uQ+L4SUkzIg7hLmF6vn9fJUibJbMUh9/jpoN7+KFQ7/4r48s8htmpu79Tkamm/30+7PzU1NaXVsM22/Zl4FgPFXYFKzjJHo1FKbLZt2wZBEAqaZSZzBCGI4+Pj0Gg0tMNdIbSCyUuvJFvt8XjQ398v8WedrTAtPjIC709+Ql87MpRZkGyxuIFJPrLF80E6aUZyQ5O5CgDF9weVSiWx7BJn8/v6+sBxnMSbeb7nltwEkYV5T+59wEoMQO5kXVwE2NjYSB2JPB4PhoeHsXPnTmi12qI1PGIZaUkyz/OIRCIApi98o9GIj3zkI/B4PFRMegAAoo1JREFUPIhEInRyIRXWDQ0NRQu6UMg0k0xa5xJiHI/HadHS4sWL897ZqUyS2YtDbpKeKgbFyDaoDryNxKJ1af+WEETyE4/HaVeytra2rLMHsxXcEVKcq4SiUNBoNJIsM7k5kCyzyWSad2MPkmEkxFTc/a2tra3oVk2knfOiRYuolRrxDO7o6KBaRZL9JE423ttugxAMAgCMn/wEDCeemHYMcVa1WNniXJEuy0x+xEQ5WZox27UvzuaL9/P+/fvR0dEBk8kkkcBkmmh6ceBFvLj/RXza9WkoIO+1JDc5ZIGgshBDPuMQe7e3tLTQ4lWPx4N9+/Zh+/btdF4sdMt31jCru8U3v/lNOJ1ORKNRSQU1uSlyHAefz4cTTzwRP/3pT9N91YJBusK9WCwmaeJBBPB2ux3Lly/P2vc1W5AJW85WzCQO8U1E7jiO1PEJZpDkiQMAAN5ST38n9pb1er3Us5hk9LIlgWJSLH6gzKbgjiVw3OE2sSTLTIgtyTKTG8NsXdrEmVOPx4Px8XHo9Xo4nU60t7dnRYgKDYVCAbvdTusiIpEIjXvr1q10m+3btoF//Q0AgLKiAvYrr5R8D1mJIKTY5/NRfe6KFSvy2sCk0JitAFDsxZzNvJe8n8U6+c7OTtoYgmSZ0znCxPk4frXjV+gP9MPFuXCSOrvuhvmE3HN/OYaZcRRirk0uXiXJFY/HQ2VFRL5VKvab6ZCWJJOmFWQnqVSqGT9qtRrxeBxLly4tWsCFBCncm5ycxKuvvgqFQoHKykoEAgHo9Xo4HA60tLTAZrMV3UqFBWImvonITZLlBKvjcxODAICwtgJD+/dT+Y9SqaS64tkKwdIhOVusUqng9XqxdetWScZ1oRCi2ZDsn0vaRx88eBBdXV20SxvR7Im1xSRzWllZiWXLlsnqaZ4NtFqtpGHBxMQE3N3diP/v/9KcZfjL/wV/PA5TNCrZ5mg0ymy2OFckZ5lJhnxsbAwej4dmluPxeFYFgMk6efKA4fF4sGfPHqhUKok0g1ynv+n4DfoD/bBqrPhkzScR8AQKuPWzQ+65n8QgN1jYD0DxtNHi1TdAKt/av38/EomEpAiwlJqapCXJra2teOKJJ4oZi2xIJBLYunUrHnnkEfj9fiqZ+MY3voEvfelLOTVDyDdYI8lyx3GkZ5LFMRBbwfqQD0oAO3r2A7VO+lCX7YSVruCOZImJ9ZVY18txHL25O53OkvDjFGeZW1paEIlEcPDgQYyMjGDfvn30gcFqtaKtrQ2VlZULPptC9NuRRx7FVGgKACCcdBI8zc3Y98EHEAQBSqUSFosFLS0tqKqqKomHo2QQbbFYQ+5yubBs2TKaNSOuGamkGZkUABJN6OLFi8HzPPVmJsvbFosFHp0HD3U/BAC45phroIceAZRJstznHAv7Qc44xPKt5FW0PXv2QKFQUPOHhY5ZRSWpiECq32W7DMUCRkZG8OSTT+LFF1/Eyy+/DJ7ncfTRR4PjprsNHnXUUUzd8FjodlcmyVLINUERErt//35MTEwgEAhMayGF6e5ja44+Blz1qqy/c66CO/H1oFKpaPZRrL3s6+tDR0eHpPlCto1FWIK4fbHH46FFfvX19dBqtTTTvGPHDpplFut6FyIC//gHpl57DQCQMJvRf8rJsGk0aGtrg16vpzfErq4u9PX10Qcju90uO3nJFcSfmmSLQ6EQzYy1t7en1erP5c2caZZZXEgJTNe97B/Zj5vfvRk8eKzVrIVjzAGv0ktlj3JcUyyQQxbmftLYR26wYEXHcYeb8Ygf+BbKStpcmJUkp7oY8nWB3Hjjjbjpppskv2tvb8euXbsATHv6fe9738Mf//hHRCIRnH766bj//vup5x8ADAwM4NJLL8Urr7wCk8mEiy66CHfccUdGgvI9e/bgT3/6EzZt2oTvf//7OProo9HX14dly5ZhzZo1sk8EyWCBGJZJ8uHxgeLeMKampiSexeR3tbW1cDgc0Ol0UL4//VmlSoO51Ov59CxO1l6Gw2Gahdu7dy/16y2Gj+x8Qaq8SfyBQICS36OOOmqGhtvlcqGlpUVCpsW6XkIg5V6Jmg3ipX/v3r2w3fEjEKpruOIKnPSJT0jIr8vlQlNTk6RQb+fOnVRjS7Y7HxZShUQkEqHH2ePxUB1mS0sLnE5nRufpbAWA6bLM4s+ng1arxcODD8Mdc6PWWIubj78Z4Ykw9u/fj1AohNdee01yfhVr5UbuuZ/EIDcxZOFhgaU4xCD3A9biyhWy3q1WrFiBF198kb4WT0rf/e538Y9//AN//vOfYbVacfnll+Ozn/0s3nhjupAkkUjgE5/4BKqrq/Hmm29iaGgIX/rSl6BWq3H77bfPOfYJJ5yAl19+WfI7tVqNRCIhe9OOVGClcA+Qf6JkiSQXCvF4XOJZPDU1BYvFAofDgcbGRrz//vtYsmQJjEbj4T9S6SCodBAUM2+Y5NzJJlucK3Q6HV2KE/v1dnd3IxwOU7u1YncrSwdxRzWv10ttuxobG2e1RxMjnZZ5//796OzslGSZxV3z5ILYfcPtdk9ri+12OP/0Z2BqWmZhOP10uD51TtrvENufEZs7scZWo9FInBzkfjgSBIGueJBuhhaLBRUVFWhqasqLK1HyqqqYNCcXAM5WDBiMBdHl7YKCU+Cm425CjbMGcE5/v8fjQUNDA9xuN3p6ema0zS70+SX3ucsCMWQhBoAdv+Z0YDm2TJHzrJWPk0SlUlEhuBh+vx+//e1v8eijj+KUU04BADz00ENYtmwZ3nrrLaxbtw7PP/88urq68OKLL6Kqqgpr1qzBLbfcgquvvho33nhj1sVJAGi2JxaLMUmSWSCngPwkWe4YCnHhi3VdXq8Xfr+f+lS2tLTAbrdLSEYqMjt5yTuS14QQp1oGJj+FtmcT+/W2t7fTjOXY2Bi6u7sl3cqK5Z1LltYJoZucnKRkafHixfNuAJGsZZ4tyywu0CokSLZY7NVM3DeWLVsGu92O8AsvwP3O9DmksNvhuOr7GX8/x3EwGo0wGo1obGykFlKEyJEmG2S7iyXBSSWXqaioyOoBaD6YzTWD3EOTdcwcx8GkNuEPp/0B7468i7WVayXfqVAoJJ0WxR0b+/v7Z5xf+SymZIEclmOQxiF3Vr3UkTFJJstHJNuU/LScywnT09OD2tpa6HQ6rF+/HnfccQcaGhrw/vvvIxaLYdOmTfSzS5cuRUNDA7Zs2YJ169Zhy5YtWLVqlUR+cfrpp+PSSy9FZ2cn1q5dm2rIWUGWrCKRCFNta4GyJjk5DrljAOa/H4jfNvnheV7ShGa2LGuqfTCbZ7FSqWTCs1hMpMTL9Z2dnYjH45Iscz6vweRmHsRJoLm5eV4tmzNBcpbZ7/fTqvDOzk6JR3E+s4CJRELiW0zkEKQATXx+JTweeO+6i752/M8PoLTbcx472UKK7H/SZIO8Tx6g8rX/ycMmeRCbmJiA0WiEy+XCmjVrZNWKp5NmJK/sANPzvVapxYbaDZLvSHWvTS6iItnywcFBdHV1wWAw5C2jzwI5LMdwGKxnkksBs14txBuvu7sbH3zwATweDy3YWbZsGerr69HY2JjTQTruuOPwu9/9Du3t7RgaGsJNN92EE088ER0dHRgeHoZGo4HNZpP8TVVVFYaHhwEAw8PDEoJM3ifv5QIyUcfj8Zz+vpBggRiSbAcLcbCQSc42hkQiIfEsDgaDMJvNcDqdWLVqVdY3cHKDTSWhWAiexcnL9YTcDA0NYdeuXfNqHU0IIiFm4nbBS5Yska2YkOM4iWl/NBqlWc6tW7cCgMSXOZtMp1jyQB4GdDodKioqaLY41QqZIAjw3vEj8D4/AMDw8U0wnnpqXraXwGAwwGAwoL6+nmbyCWFO1cwkm2OT3MSEPGzV1tZi9erVzCU8CObKMpPPJCel5vpOcn4tWbIEsVhMohsXN7XJtj25OE45wQJBZYWcsrAv0oHVuLJFSpIsCAIGBgbwm9/8Bn/5y1/Q398Pu90Oq9WKeDyOcDgMhUKBY489FieddBI+/vGPY9myZVkNfOaZZ9L/r169GscddxwaGxvxpz/9STavTXJDyqTrXrHBgiaZxCH3RCl3DJle/IS0ELLm8/mgVquprthut+fsWQwAExMT0Gg0EukEC9niXCCukG5qapI0XhA39UgnURDLCUgzD6KJbW1tZUITmwoajUbiUSzu0EayzCQLmCrLPFu2eOnSpVLNehqEXngBoUP1GQqbDY6rry7IthIoFAo4HA44HA5a6EmO28DAANWEp2uHm+phQNzERI6W1/NFqiwz+Zckbcg5Ln5/rrlIrVajqqqKJpDEkpve3l4qhyLX1VwFpiyQMlZiYOEcY8EOr9SR8q7x9NNP49JLL8Wxxx6LH/3oRzjppJPgcDgkn9m1axf+/ve/449//CPeeecdPPzww/MKxGazoa2tDXv27MHHP/5xRA+Z1ouzySMjI1TDXF1djXfekWowR0ZG6Hu5gNx4U3XdkxtyE0OW4pA7htkyySRzQ35isRhsNhslBLm2fU5elq2srMSePXvQ19cHp9MJl8sFp9NZMhNmcuMFQh4HBgbQ2dlJ28CrVCq6lC/uYDabbRerSM4Ckk54ZLs5joPD4YDFYqE2S+Js8dKlS7Pu7JcYH4f3R3fS145rroYyaa4vNHQ6Herq6lBXVydxFxEXPZImOER/G4lE0kpHSgHkvCUOHGNjY/B6vdBoNGhubpY4Z8xWAJgMIncibbOJNr+/v3+GjWG6jolyX1Ny339IDHLvB2D6/sDiw38pIeXeVavVePXVV9HW1kZ/J36aVSgUWLp0KZYuXYorr7wSzzzzzLwDCQaD6O3txYUXXoijjz4aarUaL730Es4991wAwO7duzEwMID169cDANavX4/bbrsNo6OjqKysBAC88MILsFgsWL58eU4xcBwHlUpVJsmMx8FCDMBhucPExATNFpO2zw6HA8uWLcupE91cBXdKpRLLli3DsmXL6E2ut7cXO3bsoCTR5XKVDHEg5NFqtVLJ1ejoKPr6+gBMZyYJsayoqCiJRibA4U54VVVV8Hg8GBoagsfjockArVaLRYsWoaamJudiQ++dd4H3+QAAhlNPheHjH8/nJmQNcixtNhvq6uowMjKC4eFhDAwMUGJisVjQ0NCAyspKZqUUuUL8QDg2NobJyUlYrVa4XC60trZKVgbEjhnAzEYmc50P4ox+W1ubpMhx+/bttIMkIc1Go5EJcshCFpeF/cBSHKWMlCT5rLPOmvnBFE8r5AI9++yzsx74yiuvxNlnn43GxkYMDg7ihhtugFKpxPnnnw+r1YqvfOUruOKKK2jm5Jvf/CbWr1+PdevWAQBOO+00LF++HBdeeCHuuusuDA8P44c//CEuu+yyeXmSktbUrEGhUJTlFqIY5EQ4HAYA7Ny5E36/n95sFi1alFN3xvkU3IlvcuIl6J6eHuj1erhcLpoVkvvGkgtIXQTR7SYSCSpXIUvx5EGhr68PnZ2dVHtMbuxyny/ZItlObXx8HFqtFhUVFVi5ciUcDgfi8TglNB988AGVKBBpRiYyntArryD0/PMAAIXVCsc1V8u6r8RNadxuNyWIVVVVWLlyJQwGA9Wtj4yMoLu7W1KUthBlFgAk0iK3200dOBYvXjzrQ19yAWAikZhBkLPxZk4uMCX7mtg3ajQa6PV6xGIxRKPRoriypILc9x8SAwvzCgsPDOnAwv7JB2bN05MiiFgshng8jmg0SrNcwWAQxx13HIDcTpgDBw7g/PPPh8fjgcvlwoYNG/DWW29RW5t77rkHCoUC5557rqSZCIFSqcTf//53XHrppVi/fj2MRiMuuugi3HzzzdnuAwqO46BWq5nVJLMwObAQR7FjiMfjGB8fpxIKQpJNJhNaWlpyKgIrRMGdwWBAQ0MDGhoaaDHT2NgYduzYAZ7ni247lgvEHsMejwd+vx8mkwkVFRVYtWpVSrIvflCYmpqiN/be3l6qSyaNTFiVo4gLDd1uN5UTpOv4plQqJR0PyT7r7++nhXDi7n8ztMwTE/DecQd9bb/ySigPdXsrJkjhIjneHMdR3+JUrhcWiwUWiwXNzc2SorTOzk6a+RQ3M2ER4oegsbEx+Hw+WqSaqmHNXJitAFDszUy+MxNpRnKNALH06+vrw9TUFF5++eUZ3szFImssEENWSDIrBYSlDE6YhW2QSmTxBRgKhRAIBNDY2Ije3t6iBVoMCIIAl8uFv/zlLzj66KPlDkeCrVu3wuVyoa6uTtY43njjDaxcuRJWq1W2GDo7O2EymdDY2FiQ7xcEAYFAgHoWT0xMQK/XUzJms9mwefNmrFu3LuMi03Qd7sQyikIV3ImJJ+kiR0iUy+WSvW20WHvr9XolRXqkm2AuEBPPsbGx6YYZouVjuQqECZJ9i4kv9nwJvXh/EuKZnGV233gTJp9+GgCg37ABrnt/VpRzIPlcnJiYmJPQZ/q9xIObZN+JVptYn8n5gEQ05IQYizXVhTwXxaSZ/EvmmGyyzAQDAwMYGxvDihUrZmS/i9Uk6J133kFtbS0WLVpUsDHmQk9PD8LhMFatWiVbDADw4YcfwmazoampSdY4kkEasrGajMkGs2aSf/SjH1ENpEqlgiAI6OnpwWOPPYYLL7ywWDEWFRqNppxJniMOuWUfhdgX4XBY0vZZEATY7XZUV1dj+fLlM25ic8WQruBOnCUmP4UGx0mbW4jb8e7btw8qlYoS5mKQCbEFGNFxE6LU0NCQN69gpVJJmy6IG5mMjIxg9+7ddKm+WHKU5Gyx2I4rn4WGRMucKsvc2dmJigMHYD9EkDmjEY5r/6egBFksJ/B4PHRVo76+Pm8tuzmOg8lkgslkwuLFi+nqj8fjwe7du+m+Jg8LxZDhJLe9JtdZW1tb0YpsU7lmkHkrXdvs2fYL+VtxsaX4wWdoaAg7d+6UNAnKt7NMOZMsjUPufVHqmPXMveCCC1L+nhTNfetb3yqJJwUxWC3cY6GZCMAGWc9HDKRdMiHGoVCIVtHX19fDbDbPOfmkauZRjLbP84VWq5W4CYyPj2NsbAy7d+9GJBIpSLaVuBKQH2I9VczOZ8kkihC3HTt2IJFIZGWFlSmSs8VE/tHe3l6UBxJxIdySJUsw5fVi9Md30/fHzjoLE2NjcB4irvk4DuKs7tjYGPx+PwwGA1wuV1rJTL6hUqnoAxJZASXnHpHhEIu5fDWTIStQY2NjM1Zs8tX2er6Yy5s5lVuGOOZU5DD5IVzsW71r1y6JR/l8Vgtmi6HYYIWcluUWhUdOj3e1tbV46aWXEA6HS4okcxwHjUbDbDMRuTO4JA65STKQffEGuXGTTJ7f74darYbT6URTUxPsdntWN0pyPBKJRMqCO0KKWfcsVigUlCwQMjE2NkazrUQr6XK5ssrwkocQkkULhUJUw8gCYVCpVNQ/lpAbt9uNgwcPoqurS2KFle12k2X1QmaLc8XUr38DjI0BALTHHoOmr18Cr9dLs8y5NvVI5dfscDhQXV2NlStXyipt4ThOYn0mPjeJKww5N51OZ1bnZiKRkMgO4vE4zZKzrP0H0meZkwkzcDjLnAlBFTcJAiApQu3r65PIf3LprMkKSZY7BhIHi/cXFjhCvjArSR4bG0M4HKbVrKSN7v3334+jjz6a2SKY+aBcuMd+HJlm1YkzAvmJx+OUsLS1teXkWSz+1+12o6qqCmq1mrlscS4Qk4nFixdLlslJNzhyY0suqkrO1hFPV6fTiZaWloK3fp4PiK0YKQgjVlhjY2P48MMPaTEZubEnb0dyYwtxtthutzPjYxp+/wME/vQnAACn08F53XVQH9LZE19mQmaIL7O4dXQy4UvebuLAMVt3PxZAVjGchwoVxascpGW2uJlJ8nZPTU3RbLFY+7xy5coF6yIDzF0AGA6H4fdPd2UUFwTOBXFBsdjBZP/+/ejo6KCFuZlqx1kgqCzEwFIcqcBqXNkibcc9juOwcuVKjI2NSYT+8XgcSqUSr7zySkbdnBYaWLWAY4GcshRHqhjIBExIMfEsdjqdWLFiRU4V2OkK7hobGzEyMoJ9+/bBZrPRpV1WiWAuSNXQY2xsjLYStlqt0Ov1VPcqzpoST9eFOFGKrbDEN/V9+/bRbKvBYKD7RLzdbW1tTG43Hw7Dc8st9LXt8sugTip8SpbhkO0mWWaz2Qyj0Qie5xEIBDA1NcVUljxX6PV6LFq0CIsWLZqx3R0dHTCbzTCZTHTFIRQKSba7FO+DZJ4nWmPi2Wyz2dDY2Ej1zLl4M9vtdtjtdrS2tkosHjs7OyUNgSoqKlIWFbNADFnJ4JblFoVHSpJMdvrf//53xONxqFQqunQ8MDCAp556CrFYjImTNd8ok2T24yAxCIJAs0Berxc+nw9KpZLqikmXrmwwl2cxyRi3tLSgpaVFklXq6emhxWBEnsDCRJoPEN2hSqWCWq3G6Ogo/H4/JiYmwPM8ba9cVVW1YP1qU4Hc1LVaLbRaLUZHR+Hz+RAIBCAI0y1hq6urUVlZyWzrawDwP/C/iA8MAAC0q1fD/IUvzPp5st16vR56vR6jo6MYHx9HMBik202W1FNZtS1UkO02Go0wmUwYGRmB1+tFMBgEAJpdJ64U+dKuswKxVn9sbIx6Nidb8okzzOmkGZlwA41GI3kQFzuU7NmzByqVaoZ1JQu8g5VOd6yQ9VLGrEf52GOPnfG7tWvXYvny5fjCF76Av/3tb6ivry9YcHJAo9EwSZLLzUSmEYvFMDU1hXA4jC1btiAajdIWxS0tLTll8eZTcKfX6yXexGSZftu2bQDSyxMWCsRetB6Ph3rR1tTU0AYPRI86NjaGzs5OqsvMdxFcMUG0xYQwiLOmS5cupd3HiP64p6dH8hnioMACIp2dmHj44ekXajWc118PLs2Strjjm9vtRjAYpMVnra2tNKNKPkNWFcQ2bnLrzXMBIWjkgVfsz93U1ASLxQIANLN68OBB7Ny5k2r2nU7ngpVaEG9x0vqaNCGazbN5rgJA8plsbOaSi2vFtnn79u3D9u3bYbFYEIlEEAgE4HQ6ZdvfLBB1luIoZeT0KKTRaNDb20ufrksJZU3y7Ci2ywZZ2hW3fVapVNBoNGhvb4fNZsup7XMqCQWZ0HMtuEsuBiPyhL1796Kjo0Pii8pyowNSxEYKHEl2fMWKFSmzxGKrNdKpa2xsjBIJcRHcfCvbCwmiqSZ+zURT3dramjJLTAqQSMMPsZNFT08P1aq6XK6cztN8QIjF4LnpJuDQA6Dt65dA3Sz1VBW3I/Z4PAAwq/MIx3GSJfNwOEz/vr+/nxaDsv5wKC6yJD7aTqcTNTU1WLVqVcqCMrGLA5EKeDwe6pAibmYitw93OhAZxdjYmERGQawSs324S1UASP5NZzMn/nw6iIuKgcP+352dndi7dy96e3tneDMXa25hJYPLqtwi05WEhYBZSfKOHTswPj6ORCJBC/f8fj8efPBBrFq1Cna7vVhxFg1luYX8cUxNTUk8i4Hprmq1tbVwOBw4ePAgzVZmgtk8iwtVcMdxHLXeam1tpbKMsbEx2k6XEMt8+QLnCkKSCNEhjQFmIwvpwHGHO3WRIjiSlRwYGIBCoZB4Msu5ZCl2ORBniwkxznZVItlBgexP0g1uPhX9ucL/2wcR2zPd9EmztB2WCy+UPAiRhh4ka7pmzZqsz0exZ67YA5vFLHM4HJZ4F2s0GrhcrpyKDZOlAuKW2cSHm5A8uQsZyflIMuU8z2fU+joXzOaaIS74S2U3NxuI/3dPTw9WrFgx3RTH7cbo6Ch27doFnU5XtIczVjK4rMRRykh5h+J5HgqFAhdffDHef/99+mSpVCqh1WqxdOlS3Hvvvaiuri5qsMUAyyS5VOUW8Xhc4lk8NTUFi8UCh8OBxsbGGTfWTPYFkU+kWv4rdIe7VEgnyxC7RrhcLjidzoITR3GDCY/Hg4mJCZrtzaUt7mwgWmXS2IKQUrE8oZjZdXHb6kyyxblCrNkVE6ihoSHs2rWLLtMXsqVvtLsH/gd/SwICLr8cXd3dcLvd1Be6rq4Oq1evzhtpVygUtDMlyTKT82zfvn1QKpUSx4xCZ5nFWVMiHyF2b0uWLMlbkaX44bCpqUniFbxz505JQZrT6SxK1jMcDtMHc+LCUUyvaoJ00gxxFjSbAkCiiRc70ogtCHt6erBt27YZbbPzub9ZIaesZLRLGSnvCGSn//3vf0csFoNaraaZNofDIfksKydLvsCyJpmFuPJBkglpIAV3fr+ftuRtaWmZ0zYr1fk2V8EdS57F6WQZxLOVEEeXy5W3JVuyJE5+iFQgn13P5oKYQLW1tVELMXF2Pd8d8FJli0ljg2I5cCQTKLG13rZt2yAIwozipPmCj8UwdsMNQDwBAPBs/BimBAEVKhVWrlxZtOJKnU4ncY5IzjLn6k88G8QPoaTDX0VFRdEa1wBSr2Bij0jOwZ6eHjrfEduzfDycpZNRsOTCkS7LnEgkZryXTpqR6v4jlnwBh239iAQo+Rqb77zKCu9hVW5RSpj1yqyqqprxO6IzIqRZnNVjgYDMF2VNcmHiIB7b5IfnedjtdlRWVmLp0qVZZRFJDOkK7gghXgiexcmyjFTEMRdZhjhr6/F4MDk5SZe9GxsbmdAGi/1TkzvgkdbFJLueDbFJzhar1WpKiuWWeAAzrfVIVn///v3UYi4XDbdYYxt57I+w7d49/UZ9PdqvvRZGm61wG5UBZssyE39icSvjbLLMxBWBeBeT62b16tWyu8xw3GH/8cbGRslxIisqhMw6nc6UtmfpkEpG4XQ6CyKjKARyKQDMJHsqtvUTF5oODg6iq6uLPpDn+pDCCjllNZPMAlfJF1KeGf39/fD5fGhoaJgxwXAcRy+8cDiMvr4+PPbYY7jwwgvR2tpanKgLCJY77rFw4mUaRyKRkHgWB4NB2vZ51apVsFgs8/IsnpychN/vh9FonHfBHUsQE8d0zTzSyTIIOSQZekI6ku2bWERydp0QR3EnOCLLSCYR4ip40t2v2NniXEGs9UgxGClOGhsbk2i40xHHVPIRVzQK27PPTn9AoUD1rbdAKzNBToVUWWa32429e/dKuuClO+Y+n4+Sw6mpKTgcDrhcLixfvpzZojkAkocBQFowunfvXontWapjTmQU5JhrtVpZZBT5xlwFgEQmlkgkZpDoub5X3Jpd7Nizc+dOic95prp5VjLJrMRRykgrt/ja174GlUqF8847D+vXr0dFRQUUCgWi0SimpqbQ19eHt99+G2+//TY4jsMFF1xQ7NgLgnImObc4yJIiqfb2+XxQq9VUV2y323P2LE4uuHM4HAgEAti2bRu9QRAHgYV6g0gFccaRNDlIlmWQZh5+v1+SkWppackqI8USkomjuNiqr68ParUaNpsNKpUK4XAY4+PjUKlUVGfKQrY4V5DipGQNt7h9MrGf8/v9Mx4IDHo9Rr/2NUQOSbPMXzwf2lWrZN6quSHOMgOYccyVSiVtHU9WpcgSOysrBLnCYDDAYDCgvr4+5cMCkeqQgkuiq3a5XDl1Dl0o4DiOJgrIQ4FCoUBVVRW0Wi11zgCy82ZWq9X0gRyAxJWmt7eXdlyczcKSlQwuKxntUkbKWaW+vh7vvPMOHn74Yfz0pz/FVVddRU8akuWZmprCqlWr8PWvfx3/8R//Uey4CwZWM8nFtl5LB7G8hjyRk59YLAabzUaXU3OZvDPxLCZ6PrE/L1miF2daWc6cZguFQgGbzQaNRkObWoyPj8Pn84Hneeh0OtTX16Oqqkp2t4x8Q6fToba2Fnq9HjqdDmNjYxgeHqbbaLVaUVVVhcrKyqK5RhQDhDiSxhbDw8MYHx+H3++HIAhQq9WoqamhjUyUSiUm/vhHRLZOe3SrFi2C7dJLZd6K3EAcMywWC8xmM0ZGRjAyMkL94k0mE6qqquByuRbsw2AqkGNutVphs9kwMjICt9uNQCBA33e5XLSJSzH01cWG2AlofHwcRqMRLpcLH/nIR6j8KJU0I5VbRibnhdiVRvyQ0t/fTx9SxLUSSqWSmQwuK2Q9GSzsm3yBEzJgXm63G++++y72798PlUqFmpoafPSjH6UWXKycMPnApZdeCpVKhdtvv13uUCQ4cOAAPB4PjjrqKNli4Hke27dvB8/zSCQStO0zyQBZrda8eBYDh4lxphKKVEUrhSiAKzbEVfIejydllby4UMntdoPjOCpNKIZbRqGQLB8h2WKxjpBoUcfGxqj8hmz7Qn1YEMtNiEVbsk5ZLDFxu92IRCJwJhKw33gTEA4DAKp+/b/QHXOMzFuTHcTWeW63O2VjGnFRFjkvZpMnLBSQ7Dlp6pG8SgYgrSuN0+mUXXudK0iGnMzdwWCQ+ja7XK6M6lXE8ot0HQCB7Mmb2EPc7XbTZkqTk5Oor69HU1OTrHPMc889hw0bNjBRlCkG6cIqp+1hvjAnSZ6NAGeqCVpI+Na3voVoNIof//jHcociwcGDBzE2NoY1a9YUdVwioSCexYIgUDszh8ORtSsCyRCnyxbnq+AuFArRSdfn88FkMtFJV26v1tkgtgsjshW9Xk9vhHP5rYplGWNjYxKtJssNDoDD2mJyUwqFQrPqUpMRi8UkHrjAwul4KNafE6/qTB0vSLc4zze/CWzbDgAIbtgA1WX/vSBkSOKOb+Pj45QcVlRUzOnCIc785XLOyIlU5JDIKEjHxtliT+dvTs4blldVeJ6nq4BjY2OIx+OSdt/zuVaTs8zA4QJBci5lKs1I/l4yN/f29iKRSECr1UosDYud2X/22Wdx0kknMdec6ogiyUcarrzySni9Xtx7771yhyLB4OAgRkZGsHbt2oKOE4/HMT4+TolxOBymbZ+dTicOHDgAjUaDlpaWjL8zXYc7sYyikAV3hDyRTKtKpaKE2eFwyE4gCEEiN7t8du4SZ1p9Ph/NtLpcLiYcLgqVFSQPC4Q8ie2wSHZKzm0X33BJG+T5eCcH/vQneH90JwBAWVUF1S9/Cc9USOKJTG7mcpOnQh4b1rPMYolY8rGZj/1fqk6ZRqNR0sxE7nmONBYi1nxqtZrORYWMT0yayb9krFyzzG+++SYWL15MG5oke3AX0v+cQBAEPPfcc9i4caPs17QY5F6v1WrLJLkU8YMf/AAHDx7EL3/5S7lDkWBoaAhDQ0P4yEc+ktfvJZMrWdKemJiAXq+nEgpSIEWwe/duKJVKLFmyJO13ZtLhjvwUGyRbSTIYpBMayWAUIxMgXk4nNzTS8czpdBYs85eqCKbY3e/kyvzNJ1uZL4ilBEQ6IyavuT4Mxfr7MXT++RDCEQBA5S/ug/744wFIyVNyd71iSlLkyPKnWpmw2Wx0nxcry5xORlHIc0/s4ODxeKhMQCzTKgYmJyfpXEvmOaKplivLn4k0Y6643njjDbS2tqKyspL+TtyeXZzZF7fNzid4nsfzzz+Pk08+uSg+95miTJJLHDfccAO6u7vx61//Wu5QJBgZGcH+/ftxTB40huFweIaEwm63U2I82826u7sbHMfNsPtLV3An1hbLnclIBsnmjY6OzljurKyszOukRqy9yA9ZTic/xc4EiMnq2NgYtUEimZ18xiN2KhBb08mV3UvO5qXSveYL4iYSXq8XOp2OPpiQIqD5QIjHMXzxxYh2dAIATJ//PJw/uCbt58UaS0JWxUQ9Xw+JRALCkl58No17PrX76WQU5LgX25JQfCw8Hg/tvifW9+eLzIibI42NjSEUClG5V77nlXwgWZohzirPlmV+/fXX0d7eTpuXpPpecV2BWDZH5r35nm/xeBwvvvgiTjnlFKYKOMskucRx6623YuvWrXjooYfkDkWC0dFR9Pf349hjj836b0nXMUKMQ6EQ9Swmna4yJbB79uwBz/NYsmRJSgkFgKwK7liCuI2r1+vNuZEHIF1S9ng8CAQCtPjK6XTm5BNdSJCMD5nQ5yPLWEg6UfKgRLZdXAyVi349uaCOtN4m257vAhvfr38N/wP/CwBQNTSg5rFHocgwIy1uskCWi8k5motrhLhJxtjYGKLRqEQPzxJBms1bO9uGHkD6B69irlBlCiKpI9seiUQk254tiU9uaCIIwqx+7iwj0wLA119/HcuWLaNe13NBXICd3Pkz26ZBBLFYDC+99BI2bdrE1D4uNZLMzp5lBKXgk0wyB8Sz2O/3Q61Ww+l0oqmpifqNZgOSIRYEAVNTU4hEIhIizGq2OBsQG7X6+nqJY8TWrVvBcZxk4k918RM9JMlUKRQKOJ3OorbDzRXEBmnx4sUSDfcHH3wgkWWk2/Z02eKWlhYmtKDpwHGHW0Y3NzdLdJP9/f3Ui3e27E/ytpMMZaH9eyOdnfD/5v+mXyiVqLjl5owJMjCzyYK4A96+ffvodmS67R6PBxqNBhUVFVi6dGleM5T5Brk2iUOTuClLb28v7dI427ZHIhFKDMm2u1wurFixggkNcDqIazKIvz2Zt/bs2QONRiPRcc+27WIJSWVlJRMdDueD2ToAEk/iaDRKbWIzdfYStykHDq8wkW6THMdJVrMyeaBk2TiBxZhyRTmTnIR77rkHL7zwAh5//HG5Q5GATN7HHXdcyvej0ajEszgej0skFPPxLBY/XY+Pj6O3t1eSJaqsrGSaAM4XJCtMZBmRSIRm4TUaDfx+P81GkYwpydAv9MkiubNZOByWbPvExARte13q206cQog8hiynire9WJlyfmoKQxdcgPi+fgCA9Wtfg+3Sb+Tv+9NkxMm2k6JDkn1O1w1xISJdlploecm2k9UhQjhZ7uyYKciqo3jbrVYr3XZC7ogtYSlt+2yYnJyk8z/Z9pUrV0Kn083QMedynxWv6CTXqKR72AyHw3j11Vdx2mmnMfVQQviCVqtlKq5cUSbJSfjFL36Bp556Ck8++aTcoUjg9XrR3d2NdevWATh8YRFSTDyLyUWVy9N8pp7FHMdJJo1AIACr1YrKysqMfS0XKiYnJzE4OIjR0VGEQiEAoFn6+vr6BevNmwnC4TAGBwcxPDyMyclJANMZErvdjvr6ejgcjpLd9mg0Src9GAxCEATaBW7RokVwOp1FuyH09PRg+113oWLLW1is0UCzfDmqH3oQXIGy9fF4HIODgxgaGkIgEKDbbrVaUVdXB5fLxWzGeL5IJBIYHh7G4OAgJiYmwPM8FAoFLBYL6urqUFlZydRSdz7B8zxGRkYwODhImxZxHAeLxYKamhpUVVWVbHKEaIrJPY5oq8k9TqvVSpJHBPnyZhZLM8Te+OIH0ampKfz73//G6aefztS8WybJJY5f//rXeOSRR/D3v/9d7lAk8Hq96OrqQmNjI7xeL3w+H5RKJc0UOxyOnCas2TrcZepZTLS8pAsc0bNWVlYu+Iwi0RqSYidS4EaWxlQqFZVleDyekmqTTTKpZNtJxlTswyredtINjGRAFjJxmssVwmAwSPS3RIeZ7wI4MbxeL7785S/jxRdfpL/bYDLj4eeehSvP/unEZ9ztdmN8fBwGg4Fun9lslmjOyaoSeZ9lL+5MEIlEJFZlREZB9PnigqxkbelCz6jG43GJXSa5psl8RpyQSJ0FmQ9IM5OFvO3Eu5kQY9LBlXQ3nO1hKNcCwLmQXHQptjU0m83YvXs3zjjjjBy3uDAok+QSx0MPPYTf/OY3eO655+QOBbFYjHoWi58oyZJvLhPybJ7FhBTPp+Au2ZO4WF6Y+cJ8KsHFxTviSZYQx4WQcRLrUsW66rmsusTSBLEkhcWirXQgOnRCgJI9bNO5Xoi7PSb7peZzKfpTn/oUXnnlFSQSCfo7pUKBk085BX/729/m9d3JbidEWjKXfVU6F4tiecXmA+LiTbIylqmEhOh5iR49Ez0vayB6bJLkIAXLlZWVsxaUEccesu3iBjhOp5MpW7J0SOWhT7LF87lfpSLN+cgyi6VAo6OjmJyclHTjZCExUybJJY5HH30U99xzD15++eWij83zPAKBAM1cBgIBGAwG2tmuv78fJ554Ytbfmc6zWJwpLsTJPJ8n82KCeIqSCZ94ipIJPxf5yGxWSCxl21Jli8WTbi4rAamIE4sdD8VxElcPccY01xtOumI2cuPNJcPe09Mza7fN/33qVRy9aiksOjWcRjV06rnHIEWKJM58+GaLOwd6PB7wPM8kcSJOHIQc5cMvXaznTdZxs5Rlzkcb6FTfmez9bjabaZaZBfJGIMfKJ7kHp0pMiX+yQSAQwFtvvYUVK1ZIHuyTH26Lfc6VSXKJ489//jNuu+02bN68uSjjTU1NSTyLAUgkFCQDFwgEsHXr1oxIcqqCu2TPYgBFPYEz0XgVM5bk7lSEHJEJPd9SAZbaZItN77PJFucK4s1Llq+J8wUhY8WUZYjlM2KbskJJBfJli/bcc8/hs5/9bNr3Kz93I/Qt0x7q3zq5Cd84cTEAoGc0iCuf6IJOpYBWpYCKEwA+BsSjEOIxrFukw6bl1aioqECE0+IPbx+AUsFBpVRApeCgJD8csLrOgo802AAAgXAcz3WNQqHgoOQ4KBQ49O/06waHHm2VRkxMTGBoZAxv7hlFOBSCyWiA3WaDw26D2WyESqGA3aBGjXV6PyR4AQd8U5LvEn+3VqWA/tADgCAI4AVAwWWWkRPLKLxeL13lIlnffM+HLGWZC9kGOhXEulqPxyMhb/NpnJMLxCsFo6OjeXkomG885F+xNCPbAkC/34/33nsPp556Kv0+8X2N+LIXcm5PhVIjyWyk8hiCSqVCLBYr2PfH43GJZ/HU1BQsFgscDgcaGxvTEiaO4ySZYDFmK7hTKpVMeBZzHAer1Qqr1YrW1lbqyzs4OIhdu3bR5c3Kysq8e8kCh4ka+eF5Hg6HAzU1NVi5cmXBJ22DwYDGxkY0NjZKlvj6+/sL3iY7VRtgki1uamoqOEnXaDSoqalBTU2NZLlw9+7dRZFliO29CFkplk2ZuHFKe3s7Pe+Hhoawa9eujLvfNTc3zzpOe9sSTOo0CITjsOoO3wjHJ6PoGZ1M81cKrFtZh5aWxQCArqEAHtyyP+0Yl2xopCTZHYzi+r/vTvvZ//zoIvzPGa2wWq0Iczrc/cf9AJQAIgBGDv1M46ylNtzxmZVQq9UIRuI48xdvp/3eT6ysxI8/uwIAEOcFHHXbvwEAHAClgoOC46BUAAqOw8Y2J67/eAPNFl/xShAcp4BKpYRapYNaqYBC4YeSm8Caeg9u/EQ7Heebj+9AJM5DpeCgUk4/KKgU0w8Oi516fP3QQwgA/O/mfZiK8VAqOKgPPVSolBxUCg4VJg3OXLuWPiw9t+MgPLt2Ix6PwGoywW6zwG6zwWzUw6BRYXmNmX7voD8Mnhfo+GqFAmolB7VSAZVyeltnQ7o20MWwqNNoNKiurkZ1dbWkBfvw8DB27doFg8FAyVshkhKCIMDn80kciZxOJxoaGmT3rU4mwYRUJhKJGe/NJs0Qt9cm71ssFlgsFjQ3N9OEgNvtRk9PD7Zt2zajbTYLKxuso0ySk6DRaPLqk0wmCPJk5/f7odVq4XQ60dLSArvdnlFGIdknOV3BHSHErHsWi315xZ6be/fuhU6noxnmXC9knucly3/iJhFye3mq1eoZpHFsbAw7d+7MW5vs5Gwx8XluamrKucgzHxD707a1taUkjfPNsKdqZkKKq1pbW2Vb9uY4DiaTCSaTCU1NTZLudx9++KHEizvZW7q1tRWbNm2aqUlWKnHyySfjb9d+hv5uMhTC/v374Xa7MTLqxXfWqKE3WaA3mqHU6hFNCIjEeEQTPI45RHoBwGFU47/W1SMhCEjwAmKJ6X/jPA9eAJZWm+hndWoFNrY6kRAE8Px0Rpc/9He8ANTbDz90KhRAa6URCV6AIID+TSyRQDzOgw8H8O9//xtWqxVasx0GtQICgAR/+DvJzCcmhrxoPhQwTZoBATi0ew4Oj+Gdd4bhdDpRV1eH8Ug3pr8pfujnMCrN0pWsLX3jCEUTSIWP1FslJPnhdw7CM5n6nrG02oQzV1TRh6U/dPRg/3gc0w8MU4d+ph8Yak1KPPqfS2mW+bI/bsfukdQPOC6TBv++4gT6+rI/bsfO4SBUCoATeHB8ApyQgEalhN2oxX3/cSzVVv/m9X70eUahVh4m3eRfnUqBr21oPLwf9noxFoxKPqMh/6oUWFlrpsckGJnepxqVAmqFNCNKvMibmpporY3b7UZXV5fEvYFYzeVyfYqbmoyNjU3vJ5cLbW1tTBcSz+bNLF4JJvcr8vm5PJqJxzvpCkh8/N1uN/r7+yUa8kKsopUKAS/LLZLwwgsv4JJLLsG2bdtyPsiRSETiWczz/AzP4mwxOTmJd955Bxs2bChIwR0rEDfxGBsbk1RXz5X1I8SQ/BCDdvLDih4yHVK1yc50WTC5w5+4exrp8Mf6pJWc+SLNLDI59mQpXSwhkbP1dbYQHz8iR0ru1Dc+Po7/+q//krhbbNq0CQ899BAUCgXNmE5OTtKHAnLesH7s02X7xVKIxKF5T3VojhMEAf5wHOFIFGNjbrg9Xni841CqVLDa7aitrEDrokp63nQNBQ6R+MNkPsELSAgCrDo1VtQezuL+q3ME0fj0A0KcFxBPCNP/8gIqzRqcvaqafva+V/sQjMQPfUb6+VqrDt/b1EI/+72/dmJkIoI4f/gBJJ4QEInFUaED/nuFQB10bn07gn5fDAlh+vvEN+o6mw4vfGs9rX340sMd2ONNvQJqN6jxxpUb6OuLfv8h3u33pfysTqXAB//zMfr60se24989nrTHbccPN0Kp4Oi2/atzFMB0Zl+rmibS2kM/T37jWBg10wmhB98cwFt949CqFFCChxCPgo9Hwcci0KmVuGBtBeprKmG327FjaBL93hD9Pr1KCZ1aAZ1aCRUS0CUm4XUfdhciCRabzcb8eT8XkkkzcFgm6fP50NnZiZNOOimnuhHx/UJcj0EK1HOVA5FYdTrdgt//QJkkz8C///1vfPGLX8TOnTszPsCJRELiWRwMBiVtn3NpQZxccBeLxfDuu+9Cr9fD6XSiqqoKZrOZ2afjfIBkBAlpJFnWyspKVFRUQKlUpiw6I0/HC4EYzoa52mQTUil+KCCTHOsd/uaCOMPudrvpcikhfqSJCyFWxI5qPgWHLGFqaopuu9frhV6vp9tGOqPZ7XaYzWa43W4AkFjQsf5QMBvEOm5y7MUPDHq9ni7fk+YOZrOZXhsLvaEJadhB7PfIA4PN4YTFakOcFzDm9iASGKdtoKNaG3RmGwwmC3hwiCUExBI8YgkBHAdsWuqi3/+vzhEM+sL0M9Gkz/7wzDb62Z+/shc7Dk5IPjP9NzwSPPDcN9fRz17++A68vNuddru2XvsxaJTT98GrnuzC33eMpP3s7z9VhWhwHFNTU3jqgA4vD6SXQP74JB2WNVShsrISv9oyjD++dxDaQ0Rar5b+e/PZS1F7SP/+Wo8H7/b7KOHWi/7VqpQ4ttEGs26aKE6EY5iK8jBolNBrFPRBrdhIdlDS6/U45phjJFZzuZz7pHidnHfkQS2X+bRMkkscb775Jj7zmc+gp6cn7QEmrTxJAZDP54NaraaZYrvdnlfPYnIBiN0i3G439eStrKwsiafm2UCyrAcPHsTo6CgikQiA6SUl8tCw0MnBbCD+pYODgxgfH6cTkcFgQFVVFfVwLcVzgLhQDA8PY3h4GFNTU/S6sNvtqK6ull1nWEiQ1ZXh4WFaBAWAZs2qq6tLVl9I5trR0VGMjIwgEAjQ7bRYLKitrS164W8xQR4YRkZGaKIAAG2bXVtby4xzhCBMS3QicZ7+ROn/E1hdd3h++mDAh4HxqaTPHP6bK05tgUalQCgUwv+9tgdv7PUhHI0jygMxHogLCiSgQJQH/nX5OjiM09f+Lf/sxmPvHUwb43PfXEelQD99sRf/9+ZA2s8+ccmxVGL0wOZ9+PkrffQ9jVIBvUYBg0YJg0aJOz+9nOrJX9/jwfM7x6DXKGFQKw8R60P/qpX46GIbnIfiDUbimIwkoNdME3m1cuZxTCQS9IFwbGxMIqOw2+0S6UUqt4xc5oXJyUmJSw25z85lhwmUHkkua5KToFarU2qSyZMW+YnFYrDZbHA4HFiyZEnePIuBmR3uxBMg0bKK9VdEGkIIcyGKv+QCuUmQC5aY99fU1Ehs1qampjA5OYnKysoFn0kSQ+xFSrLFlZWV0Ov1tIK8v78fgUCATpylQhjEBT+kXavRaER9fT2USiUmJyfpyo3f76dL86WyupIqm+5wOGAymegqy4EDBzAxMVEyGXQxUslvamtrodVq6XXR3d0Nt9tNt38h+HFnAvJgSIgRaYVMaikmJiYwMjICn88nccyQ89znOA4aFQeNSgHzHJ/9SIONFoGmAs/z9P62xuDDyqVx2hsgHo9jfHycNjfyjRyA8tCK7XdOacbFx9djKsYjHEsgHOMxJfqXkFMAOLrBihhfn/S5BCJxHlMxnmaRp+MRoOQ4KvmJJnhEp3j4p+IzYu8aDuIvHw6l3bbff2kNjePp7cO49V899D21kqNkWqMQ8F8rNHBhAjqdDmOw4k2PEzaTDoYhFYyeSRi1YRg1Khg0ShxVZ0aFSQNBEDAVjSOaEGDQqqBRKrL2ZiY1Qw0NDZIaj/7+fuzYsYPW96QqvCy1vGs5k5yEbdu2YcOGDdi7dy9ee+01JBIJVFRU0LbPJFtstVqznpBIhni+He5Sfa9YlkDsfVjzI84EJHMkbuZBlhvTaaVisRi9mbjdbmg0GokubSE9MIgLDsUygnQSknQ3U0KYWfFmzRTxeFyy7BePxyUWbckkSEwkicWauPBxoT0wiLXVhBiKbcqS55xUnxfLLhbSA0Oqc5ncjFMVcqZ7iCL7a6Fl11M15JntXE7uBkpkKWJ/94W0/am6/ZF5PFXiJ1VxstjuLN8rSyRTHoomEIolpv+NJjAVTWBlnZnqrT/c78fb+8YPvx87/LlQNIEbPtGOFte0g9Mf3tqPu1/sPVR0OhO3b6rCptUNMBqNePz9Qdz8z+608d33hZU4tX1aVvPM9mFc/dROANPE26hRUjJt1CrxzZObcUKLExzHYfdIEH/fPgyjVgmjRgmDVjX9+UP/LnYaaKYegKTgWNxXQCyH4jiuZDLJZZIsQm9vL/7whz/glltugV6vh1qtxiWXXIKvfvWrtKFHtpitwx1p4pHPgjtx96/R0VHaOYtMNiwuSRNiRC48Uu2cy2RPbhxEkkLaBZMHBhZJQ6psca6TfXJL3YXQJlvc0GN8fFyiv83GqiodyWJZqypuwkAeijLt9pYMsb0eIVl2u525BjZizKU9z2bOFd+8PZ7pYrNCkqZ8YLY20NlkhklygWz/+Pg4tFptRp1C5QRxNhodHZXUXczV7S8ZqdyMkutTWJ37RkdHMTg8ArcvCJ3JAqPVAZ3JCl6hQnuVCVb9tISwczCA13s9lKRPRqZJ92QkjlA0gatPb8XqOgsA4E/vD+LGf6S3aPzZ55Zj01IXFAoF/tExgu8/0ZX2s3d+Zjk+vaY25XviB1Xi4KXRaLBixQrU1dUxN9/mgiOaJAeDQbz00kt47rnn8Pzzz2NgYAAf+chH8Pbbb+Nf//oX1q1bl1O2OF2HO0KKC9XhLhXIRTg6OkqzkpWVlXTJXg4kX1g+n48SI6fTmXNXslTj+P1+mmEPh8NMPDCIK4vFxIgQw3xpi9O1yZZ7hSGZzJHjQo5/vnyyU/nEzrfzXT5AHgoJMRJ3pcuXtlq8IkMa2BACIne76Pm4mGSK5GtM7PYityyFOHmkK8jN57WfnGWer83afJHqQdZqtUpWvvKB5AcmQRAkc4xcspzkplqFTGLFEvw0iY4SQh3H5KFs9qpaM1ym6bF2HJzAPzpHDxHuBEIxnn52MpLAdWe142NtFRmNSc47s9kMq9Wat22REwuGJP/yl7/Ej3/8YwwPD+Ooo47Cfffdh49+9KPz+s633noLF110EU4//XScdtpp2LhxI7xeLxobG+H1ejMmEXMV3LHiWZzcjtNkMlHCXOhledKulkxcpAMTIQf/v737Do+qTNsAfk9675kUICQECaH3AKJAAAMEkhAUgVWaqDRZXCxYYGW/tYG6rAXFTxZ0VxCQhIQqkRIpoQgEKRKqtJBMeiVlMu/3B9979szJTEiZcmby/K7La5cQYGYyc85z3vO8z23sgl18cBZfMPBVC2OnLhlytbg5GorJ9vf3N/pJQxrVzAtWU6WP8U2vvDjhtwhN1ZYhLlj5ajn/t02xws/3VPDCnN9h4f8Zc8Or+LPH2yJMnTgpvjUvTn3knz9jvv+MEQPd1H9f2sJmylXmhhYrTPHZ44UpP//wthxxmIkxP3/idkiVSiW0cJp7sYLTlwAobgPlv24MjUYjtFtYA4sokjdt2oRp06bhq6++QlRUFFatWoUtW7YgKysLSqWy2X+vrmHcOTk5CAoKwr179/Re1TbUQmEpM4ulfbx8p7xSqTTIaob4NjK//eXq6qoV/WzO10fXeDV+NW+IlVxTrRY3l7FjsnWl/IlHtJmz9UEcU5ufny/cmuWrmYZ4bLoCTcStD6aOwhXTtcrKfzaG6mPX1fph7GTFpjw2XT8b3v9riFVWU8dAN4U4ia2goKDeKrMhVnN13cXixxdzF4bicWcFBQVQq9X1Vtlbim+s521/lrSxXlfR3JgEQI6KZDOIiopC//798fnnnwN48ENo164dXnrpJSxZssSg/1ZhYSF8fX1x69YteHl5Cf+evhYKua0WN4f4A80DPHjB3JSeUL5ayv/jiT78P7l+aKR9geIRO005oPHbyHwjCQDhuct5RJk4Jjs/P7/ZMdni5y+e2yz32b3iPu7CwkIhvlccZNEY0ucvDjQxd2HQEL7Kz5+/g4OD8Pyb0pbCb3HzNorm9teamnQuMV9lberzFy88iGOgeXuPHM8P4lVm/vydnJya/fzz8/OhUqmE5y/3DdTiRFy+ys6zCFry/I2x8GQuutL/9I2bA6hINrmamhq4uLjgxx9/REJCgvD16dOno7i4GCkpKQb99/iK39WrV+Hj46PzzWGMDXdyId5II701xAM8xN9bUlIi3Mbkr53cN0s0hD9/fsFQV1cnBJhICz1papF0s4glHhil0yJqa2v1roBJN52JN8rJYbW8OfjIQX7BwANsxCEmnLi3nvdX8hV5S37+4ukifFqIrukivI2CP39ztFEYmq7nL925L2bsOzKmpuv5i0MlpKusPPSGtxHx52+pozj5eDnp8+eLHdK7LLpaGC35+T+MeJWZ/680yIQxBhsbG4ubLKSP7Ivk7OxstGnTBkePHsWgQYOEr7/22mtIT0/H8ePHDfrvVVVVwdnZGR988AEmTZokbHCxhBYKQxNvMlCpVKiqqoKXlxccHR1RW1uL4uJiq0p5kxJPCsnLyxPifp2cnKBWq1FcXAwAWidRa3v+0l5KT09PODs7o66uDsXFxdBoNMJtdEuI/m4KcVtGXl4eysrK4O7uDldXVyFl82Ej6iyZvhFrbm5uwmdDTm0Uhia+CMjPzxc2GHt4PJggUFZWZvLeflPStcrs6OgoXPyXl5ejoqJCaCPy9/eX5QSV5tI1McTBwUGoCSoqKmSzGd5cxIuIjDHcvHkTqamp0Gg0ePvtt8386AxDnvf/zKiurg7Dhg3Dd999h2XLlmHo0KGIj49HbGws/P39H/4XWBGFQgF3d3eo1WowxoQxPba2tqirq4O7uzuCgoIQEBBgVScHTqFQwMPDQ7ha5qsF/Pm7uLggMDAQAQEBFjePuDH4z59fJKpUKhQXF6OsrAx1dXVwcnJCUFCQxd9O1Ic/f3t7e9jb2ws///Lycmg0Gtjb2wvPX66301uCP38nJyc4OTnB3t4eBQUFqKysBGMMtra2QnEg53aS5lIoFHBzc4OzszNcXFzg6OiI/Px85ObmCu91cdqnNV0gAg+ev6urK5ydneHu7g4XFxfk5uZCpVIJK4Z8A6JcRwy2BH/+Li4u8PLyQm5uLnJycpCbmyucA3gvv4+Pj1WeAxvj8uXLSElJQWpqKi5cuIDHH38czz77rLkflsHIfiXZ1O0WHGMMly9fRlJSEpKTk3HmzBkMGjQI8fHxGD9+vNXMANRFvBOa92iKd0Lb29ujqqpKWGEuLi6Gu7u70H/m5uZm7qfQIrrGB4knUTg6OqKmpkar/5D3n/H+O0t+bzTmljOPSuavAe+/5SvKcu0/bQxxGw2/g8Anofj5+cHV1bXetAy1Wq0V/GDpdxTEY7rEbRS8jYQxpnPzG38PmHNjoiHwPnW+MCCdN65QKOptTBankFliq42YOApZvPFMvE9BHF3ckl5eOWKMabUd8rYz3nZoZ2eH+/fva4WZiKObfXx8LP4YoI9Go8G5c+ewbds2pKam4saNGxg5ciQSExMRFxcHX19fi37vS8m+SAYebNwbMGAAPvvsMwAPfkghISFYsGCBwTfu6cJvIyQnJyM5ORlHjx5F3759ERcXh/j4eISFhVn0m0I6U7OqqkorzONhq6R8wxLfsOHk5CSsMFnCyUJfb634hNfQKqF0JzMArZ3MlnCy4L2Fzdm81NSkMDniIwr5ewCA8BwetulQV1uGpaUein+G/BjAL4wa00Ygvi1fWFgozD2X86YtsZYmV1rqplUxfuHPLwycnJyE49jD7hTpCoQSj/i0hIsmcRBVXl4eAAgLH76+vg2+h/nnh28A5HO59SWlWpq6ujqcPHkSKSkp2L59O1QqFUaPHo3ExETExsZazUxkXSyiSN60aROmT5+ONWvWYMCAAVi1ahU2b96MS5cuISAgwKSPhTGGnJwcbNu2DUlJSUhPT0dkZKRQMEdGRsr+wyDuteM7evmOZh7m0dxbp3yFkReM/Jas3HZ4N2a1uDl0FYzijW9yWV0w1hgsS4nJ5v2GvCgsLi4WRhTyMYDNfa/yFDH+3uIXHHL7DIinmoincbT0boApwlIMwVgXd3IefyglvWNgiM+qrvOLMcKiDEE62YdP5FAqlS26I6hrLr44zMQSFg7UajWOHDkiFMaVlZWIjY1FYmIiYmJiDBb8IncWUSQDwOeffy6EifTq1QuffvopoqKizPqY+C2ZlJQUJCcnIy0tDSEhIYiLi0NCQgJ69uwpqxMiv9IvKCgwyZW+eFKESqUSZmWaIyJaOre5pKSkSavFzf03+QqjSqXSChEwxyYPfgvZlIEKcorJNkdss3hebH5+vtnbMsShHvzCgP88jLHaJd78KZ0Xbo6ocHO0CZk7SEdMmvjGNx7yNgJj9NXyiyb+/MXtW4aaS9wU0ihsV1dXoTA2xvuRt2/xcy+fgiOegiSXOqG6uhoHDx7Etm3bsGvXLigUCsTHx2PChAkYMWKERRT3hmYxRbIlKC0txa5du5CUlITdu3fDz88P48aNQ3x8PKKiokxeFJaVlQlXsyUlJXBxcdFKGTL14+GpSyqVSmuF1d/f3yi3I/lqMX8NDLVa3FzScUn84GyscVFyi+blbSniFUZjBwxILwyMEYHcWPqmhRgyxENKfMdAHINrrs1W5vh56AoOMnQMdGPxqTD85yFuazHmYoU42IOP9eTvAVMX6fpWmY15XqqsrBTOPfzuFi+MTV2k19TUaF008DGj/D9TfyYrKyuRlpaGlJQU7NmzB+7u7oiPj8eTTz6JIUOGWN2G3KaiItlIKisrsXfvXiQlJWHHjh1wcnISCuYhQ4YYvSgsKCgQxnOZ68OnDz9Q8oNWeXk5vL29hYKxuasZDa0W+/r6yuqKXddtPkMED/C/V9xGIl4tlsutbmPFZMtt5bIh0hAPvsrO+8Bb8h4QX4yIV0tNvXLZEPFM7vz8fGGcnL6ZxI1l7hjophCPmJMWjIZ4D/C2Nzs7O1m2vTW0ytzS90B5eblwjqmoqBBWzP39/WWzImqOxSx+ntyzZw9SUlKQlpaGoKAgJCQkYOLEiYiKipLN+0MOqEg2gZqaGhw4cABJSUlISUlBbW0tYmNjER8fj+HDh7eoIBCHefANZ3K8jdOQ+/fvCwczcV+cUql8aN+TvtVi/hrI5WDYEB5gwW+BajQaYSf1w1ZY9QVaGLONxBhaEsogPtHy10+8WiqXC4OGSNsy+OpSY/t4xaEepmijMLSH9Yg/bMW3oRhoOV0cNkT8PuatOU2ZwS1dMbfE94B0LrW4YHxYcc8nrvDjKA/C4a0klrB5sra2VmgJk7ZF8taU5vaJFxQUYOfOnUhNTcWBAwfQsWNHTJgwAYmJibJqDZUbKpJNTK1W4/Dhw0hKSsK2bdtQUlKCmJgYxMfHY9SoUQ8dn6ZrQ4D4Vo0lFIUNke6wdnZ2Fq7++RD/0tJSrQsDufZ3NYd0hVV8e5yvgLT0ZCp34nhjvgomHT9l6dMUGqKvLUM8gq6h94k1zKxtzLQRQ8Wpy5G+IBf+GecXDfyOHJ+qwoMt5LZi3hzS41xtbW29VWaNRqPVY84Ys7jJQvrwiwbxmD0nJyeti4aHLaDk5OQgNTUVKSkpOHLkCHr27InExEQkJiYiIiJC9hdOckBFshlpNBqcPHkSW7duxbZt23Dnzh2MHDkScXFxGDt2LDw9PVFdXY19+/ahpKQEYWFhqKiosKrRMg1Rq9XIz89HTk6OMKsTgHBhwFsILL0obAg/Cebk5KC8vBx2dnZQq9VwdnY2yK15ueMrhPxOg1qtho2NDTQajVAQ8MLRWvG2jNzcXBQVFcHGxkaIfjV2T7cciHvrc3NzUVlZKYQ5iDddWWIMdGOJW2j43RL+OfDx8UFAQEC92HRrwi8a+GtQXFwMW1tbIdQnICBAmEhhrcdC8ajWgoIC3L9/H97e3jh27Bj69++Pfv36QaFQ4I8//kBqaipSU1Nx8uRJDBw4UFgxDg0NtdrPiLFQkSwTfED31q1bsXnzZly9ehVeXl4oLS2Fi4sLnn32Wbz88stWPaSc4ytp4rnFrq6uWnHAALQKBEteMdCFt2Dw16C6uhqenp5wcHBATU2NcCvSXBuQTEG8oszvmvA7BZWVlUJMuBx7TQ1F3IJQVFQEFxcXuLm5CRvyeHsRv2CyhFvKTaGrd93T01MI9CkpKZHtiD1DEW945fN7xZ8D8QZQc2zINYWamhphxbygoAAuLi5ad1Tq6uqEMBtruJPSGPxu2pw5c5CRkQE7Ozs4OjqitLQUjz76KCZNmoQJEyYgKCjI6t4PpkRFsgzwsSu7d+/Gnj17cO3aNfTu3RseHh64e/curly5gsGDB1t12p/49qp406Gu1WJr6D3T5f79+1otBA4ODlqjosQXArpGWYlvM1pioSCescxvMfP+al19lXKaWmAofMYufw34hkb+GohP/uKNqtK2DD4twxI1ZQqKOB2S9yKL204stf1MGtDEN3XyYA/x57uh0Y48IdUS6dqrwltJxO9tcWtKQUGBsIAgnstsicfDhohT77Zv345r166hW7du8PX1xe3bt3HlyhUMHDgQo0ePxujRo9G3b1+LPB7KARXJMnDz5k0MHTpUeENHR0cL/bf60v7i4+MRFxdnsWl/+laLxT13jTmw6dvFzE8ocj5JNhQ60JSRYOIpAXl5eUKEqiWsLvIVc14Q8QuepvZX65t/awm9ibr6b8WbzhrbRsEvGvhFFg8IsoQ+bUPM09a3iVUcpy3nYyUvCsWbV3lR2NipLLpCgry8vITPk1zCfHQRH8v5RV9zph7xTABeNIv3bMhpylNT1dXV4ddffxUK44ZS727fvo2ffvoJe/bswe3bt3H8+HEzPnLLRkWyTDDGHnrwsvS0P+lqsXgHv6F6i/k8THGClLnmYeoija+1sbHReg1aWtCKN33xiwYemKFUKmXRvy0dfebg4KDVX93SgtYSYrL5rVI+M9vQq+C6VmPl1JZhimRGXZ81Y4fnNAX/rPLjFf+stnQUplhT7k6Zg775+Ya6K6hrAyRfZeYj1uR88WiI1LvG1BZEPyqSLZQlpP2JV4v53GK+Wuzr62v0A5SuZCVeLJqqb098S5yvmIsDPYy9umWI1amW0hVqYuwQDfG/LYeYbF29tfziRdpGYYx/u7S0VPi3eS+3+PU3BV0XL+K0N2NevOiLYecXDaa6gDbnXR/xxi/epmaImcRNJd6MyydSiEdeGrNwF68y81GLcltl5u2XKSkp2LlzJxQKBeLi4pCYmNhqU+/MiYpkK1FaWoqdO3ciOTnZrGl/fLWYrxiL04TMOZ5MOlzf3t5eWGH28vIyaKGkq7/anEl/HF9Z46uLxoyI5icj/m+JQ03MuZLJb+vzCydjvgbiFpCWtFEYGl9d5KvYTk5OQpFmzNfAVDHQjaFrJd9Yq4v8NeDHHjnsH9A3k9hUr4Gtra3W8ddcr4FcVpn1pd5NnDgRjz32mNnverRmVCRbIVOm/elKDDLlanFz8BUVvpIBoEWzNcUnHN7m0Zz+alPS9Rq0dDVHmh7GWwjk/BoYOiZbGj0u982EfBat+DVo6cWMpW2o5AUcf++KL2qbG0bD72KJpzHwY4wce6Olr4E0zKY5F/a6Zt7L+TVoaJXZ0As8lHpnOahItnI87W/r1q1ISUlBXV0dYmNjERcX1+y0P10HEzmsFjeHeFKGSqUSbn/yW8D6CiXxrnq+4cwcty4Ngb8G/IQm7uFtaPYqv3XMXwMeaKFrEoPcNTcmu6E2ClPexjcEfW0Z4hATfX/OUmKgH0bXxBDenuPn59dgi5I42IO39eiaxiB30k3VJSUlcHd3rxdkogu/SFSpVCguLoa7u7uwYmxpr4GuMBdxXHRTi1h9qXe8MJZDiySpj4rkVqShtL8nnniiwZOgoQ8YcqRrIw3vmfT390ddXZ3WSimfz2qoDWdyIO7hValU9VK8bG1ttWYX29raCgWEj4+P1dwWlMY8i2OynZ2dtVZfAWhtCDP3pjhDEbdliFcCeVS4+OKgtrZWGMNoKTHQjcE3mfKNb/b29lqf+fLycuGzUlVVVS8d0xrweeX8dVAoFMJ73dfXV5hhrFKphIkUctoobAjNXRgSp96lpqbi8OHD6NmzpxDu0blzZ9mtqBNtVCS3UvrS/uLj4zFmzBio1Wps374dBw4cwIwZMwBAdhscjK2srAy3b98WNrkAgIuLCwICAhAUFAQXFxerP8Ddv38fd+7cQW5uLu7fvw8AwsVBmzZtZHnb1NBqampw7949ZGdno7y8HABgZ2cHX19ftG3bFt7e3lb/GqjVaqhUKty9exelpaVC4puXlxfatm0Lf39/q7hQbghvz7l79y6KiopQV1cHhUIBd3d3tGnTBoGBgVZzkagPH1t59+5dISoaAFxdXREYGIg2bdpYzcWBPrpaDHNycpCRkYGxY8dixIgRyMnJQUpKCqXeWQEqkgk0Gg1+++03rF69GqmpqVCpVEKSV3R0NN555x2EhIRY/UkQ+O/KEd98aGdnJ9xi5KsJfFIGv41oqikRpsKLAb5qolarhaH8CoVCaLGws7MTVoysbWC/uI2Cz7D29vYWVop5W4JarbaYmdTNwRP/xCvqvJ2Ib37jrw1/HSypvaIxamtrtYI97O3thdV0vhmW310T9+Bb0zGBt1bxu2x1dXXCZlc+raKwsFA4XlrbnaWG1NbW4ujRo1ixYgWOHTuGmpoaMMYQERGBZ555BjNnzqTUOwtGRXIrt2vXLiQlJWH37t0oKSnBiBEj0KdPH5SUlODw4cM4c+YMBg8ejLi4OMTFxSE4ONiqPuy6xpPxEW36xqSJT5p8SgQvmC315CideMCnPvDbytICmJ8YeQFVV1enVSxa4slRvHlJPJqKb+STFsDW1IvLNdSbra/Xnveh8pYEPiGAb9SzxIunqqoqoSAsKioSLop5cazrmCBuQwIsvwWHXyzz18HGxkY4zuk7Jkj3KIijoi2pJ7kxpKl3169fx4gRI9CzZ08AQHp6Oo4fP44uXbpgzJgxeOaZZ9C9e3czP2rSVFQkt3Kvv/466urqMGbMGAwZMkTrVpm1pv2Je+z4CU08oq0p/ZTiCQl5eXlQKBRmH+/UGOK0P14MNWaTli7iDV8qlarRm97koKG+26YWeNK/S+5THTi+CZW/h/mEC95f3JQLHn1j7+ReLOpKe/Py8hIK46a0l+m6CyGeSy3nNq3a2lrhc1xQUAAnJyfhNWjqe5jfadCXAGmJezj0pd5NmDAB48aN00q9A4DCwkKkpaVh9+7dGDt2LCZNmmSmR06ai4pk0ij60v54wSzntD9dEdj8trEhb43ywAJ+ouW34ptTbBgDXwGXbsDx9/eHj4+PwQoYcXgH3xkv3uVvzvdJcyc4NJVardaaSc1n4/LX2twFgiFioB9GX8uKXCZ/6Ao3Ed8NMdTmQ2nqHe/p9/f3l0WbEh/Zp1KpUFRUJAQO8YkUhvi8Slu4+EZPY4xXMzS1Wo2jR48KhXFzUu+I5aIimTQZYwyFhYVITU0V0v7at2+P8ePHyybtr6G5n4aKwG6IdHWVj0fjxaIpdv+LJ1XwvkljXBw0RDorlQdXmLI1Rd8sYH1tFIYmh5hsOSQPymGGtLiFgK90t2RGenP+ffF7kff7t2QecXPwcXV8gk1zV82bQ9+0JDnNlW8o9S46OlrWRT0xLCqSSYvpS/tLSEjAgAEDTLJqxhjTur3HT8K8GDH3mDpTnZTq6uqEvkBx9CwvyMx5cJcWKHwl2xgFijjQwtipck1hymJVXwy0HEaUmTKNkF+oiVfN5bCHgBeL/DUoLS0V5hHr631uyb9VWloq3OUyx0W7PuKEUp7O2dIwl+ag1DuiCxXJxKAqKyvx008/ITk52ehpf+KCMD8/H9XV1VobRcx9O1cfQ9/eFM9yLSgogIODg9YOc3Pf2tdFXMDxEBdxgElT3yf62ih4wSHXW6LiZDZDxGTrKj7FKYJyfC80FMjS3IvIyspKoSCUW8uPPnxSBv8ciyO8mzMpQtz+pVKphM21cmn/0kUc5sIvHPhGaj8/P4OOnGwo9S4xMREDBw40+4o2MT8qkonRGCPtT9rfZwkFYUOas1FGXBDyiRyenp7C62BpI+mau2lKV6x0SyOVzUm6CRRo3OqqpcVAPwy/I9SUtgxL3jyqi/giUppm2dACgK67NZawkVif6upqrU3W/MKBH++bczFdUFCAXbt2ISUlBQcOHEB4eDgmTJhAqXdEJyqSiUnwtD9eMDc27Y+fLHhhzKcwiMcKWVoRoE9DI5fc3d21Vs01Go2w8mpNCWdA/d5VnnanVCphZ2enVUBJd8xbywnuYaPY+MWVdPSctY3a4rPJdbVleHt7ayVk8n0HfKXU0i6SGsITIMWtZOJpGYWFhVY1klKX5p4LKPWOtAQVycTkNBoNTpw4IcRjS9P+SktLkZKSgoyMDMyePRu2trYtWj2wRBqNBvfu3RMSzhhjsLW1hY+PD9q2bWuRq0LNUVNTg9u3byMnJweVlZUA/pv4165dO7i7u5v5EZoGT3/kbUVA60o5A/67Cnjnzh0UFhYKiXeenp5C4l1r+Eyo1Wrk5OQgOztbODbY2dnBx8cH7dq1axUJkED9u4q5ubn46aefMHbsWIwZMwaFhYVISUnB9u3bcfLkSURFRSEhIQETJ06k1DvSaFQkG9C7776LnTt3IjMzEw4ODiguLq73Pbo+mBs3bsTkyZOFXx88eBB/+ctfcOHCBbRr1w5vv/22EA1tbTQaDTIzM/HFF19g+/btwsaNoKAgjB49GkuXLoVSqWwVBzR9t1j5NA6+8aaqqkpYMTPlxhZTEY+L4nN7fX194evrCxsbGxQVFQlfF/fbyrHHsiX4yD7+fuAJh97e3kLvsTgBTi4jxQxNVzsJv7ty//59FBQUCIEf4hATaztm8A2fKpUKpaWl8PT0FFaSeR+vpbdeNVddXR3OnDmDDz74AIcOHUJFRQUA4JFHHsHUqVMxe/ZsqwvCag6qUZqOimQD+utf/wovLy/cuXMHa9eu1fsGXLduHUaPHi18zcvLS+iZu3HjBrp164Y5c+Zg9uzZ2LdvHxYtWoSdO3ciJibGVE/FJJKSkpCSkoLdu3ejtrYWMTEx6NWrF4qKinDgwAGrT/sDmrdZh++Il07KUCqVFtd7yfHNh43dwCZuR+AXDnKZ3NASumKg+XPSNe1AmnxoDTHZ4gkg/D3OC0KlUqmzH1eceCfuxeUjHy3xAorPd+cb7yorK4UWK6VSqfPi2BI38bYET71LSUlBamoqrl+/jujoaERFRcHGxgYHDx7EoUOHEB4ejrFjx2Lq1Kno27evuR+22VCN0nRUJBvB+vXrsWjRIr1vwOTkZCQkJOj8s6+//jp27tyJ8+fPC1+bPHkyiouLsWfPHiM9YvOYN28ePDw8MHbsWAwePFjrRMbT/nhLRkZGBvr27SsUzJaa9mfosU88PlelUqG4uFhrF7+bm5sRn0nL6Ip05oVQc3rN+Yg98Vg18TQDuWpODHRDf5elxmTz14H/DPndEv7Ym3K3hKdJ8s9YS15TU2OMCXdK+NQXPpGiqXHvch4H2RI89Y4Xxg9LvSstLcXPP/+MXbt2YeDAgZg9e7aZHrl8UI3SeFQkG8HD3oDBwcGorq5Ghw4dMGfOHMycOVMoCB5//HH06dMHq1atEv7MunXrsGjRIpSUlJjoGciLJaf9AaYLENAV3MFXmA05Oqm5pK8D32hl6M2HfKwafx34dAQ5vg7iGGhDh5vwnk0+apC3Kfj7+8vqdeCFMQCtEWWGWvWUrs67uroKxbdcXwf+c+ItRi2lK1iIvw6mChZqCXHq3Y4dO1BRUYHY2FhMmDABo0ePlvWFsBxRjdJ4lncPysL97W9/Q3R0NFxcXLB3717MmzcP5eXlWLhwIQAgJycHAQEBWn8mICAApaWluH//vqxXQYxFoVAgKCgIc+fOxZw5c4S0v6SkJKxcuRLt27dHXFwc4uPjZTPChxcofAoD32zWtWtXo/WNOjg4oE2bNmjTpo3Qs6pSqXD69GnY2toKJ15T9q3qa6Mw5uvg6OiItm3bom3btvVeBx4PbeqRWPpioLt37260qRzOzs5o164d2rVrp9WOIH4dTB2TzduLeLHm4OAApVKJHj16GO11cHFxQfv27dG+fXudr0NLZhE3l7Tf3N7eHkqlEj179oSXl5fBC1aFQgE3Nze4ubkhLCxMK6L+zJkzRouobwl9qXdff/01pd4ZEdUo2qhIfoglS5bgww8/bPB7fv/9d3Tu3LlRf9/SpUuF/9+7d29UVFRg5cqVwhuQNEyhUMDX1xczZ87EzJkztdL+Ro8ebZa0P0D7tnl+fr5WmEVERARcXFxMulJjZ2eHgIAABAQEQKPRoKioCCqVCufPnxc2vBl6xQ7Q30bh5+eHRx55xOQj+3S9Dnl5ebh48aJR+3cbStbr2LGjyV8He3t7BAYGIjAwUGuDaFZWllZMtjHS1/hIP94SxPusO3ToYPKNZbpeh/z8fFy5cgVVVVVaISaGLsKkdzhcXV2hVCoRFhZmltchKCgIQUFBQntKfn4+rl27hnPnzpltpCBPvUtNTcWePXvg6uqK+Ph4bN68mVLv9KAaxbio3eIh+MpPQzp06KB1YmnoVobUzp07MW7cOFRVVcHR0bHV3cowJH1pfwkJCXj00UcNvjoiXpXi7xHeQiHXOa3i3k+VSoXq6mqhUGxO0h2gu51EHOohx+kb4k1RPKHP29tbWG1vToHEiw3+d8opBlofY8Rkiy+UVCqV8Nq2JEHPFPgsYkO2ZUiT/3ivvL4NiHKg6y4YL5gNffeHv1d2795NqXfNRDWKcdFl2UPwg6SxZGZmwtvbWziBDho0CLt27dL6nrS0NAwaNMhoj8FauLi4YMKECZgwYYJW2t/MmTOFtL/4+HgMGzasWUUQLyj4CUTc19erVy/Z9/UBD1bivby84OXlhUceeUTY8Hbr1i1cvHix0YWirjhlY7eTGJJCoYCHhwc8PDzQsWNHoW81JycHWVlZcHd3F1bbGyoU9cVAd+rUSbYx0GLS2/Din+v169fh5OSklXan7+cqjkDOy8sTYsZDQ0MtZsqGq6srXF1dhbYM3o4gbcto6OcqTo/kFwg+Pj4ICgpCjx49ZHmhJCVu0xGPY7xw4YKwn4K/Ds15Pg2l3i1btgy9evWS/fFDTqhGMS5aSTagW7duCf2yK1euxKFDhwAAHTt2hJubG7Zv347c3FwMHDgQTk5OSEtLwyuvvIJXXnkFy5cvB/Df8Srz58/HrFmzsH//fixcuNBqx6uYgq60v9GjRyMuLq7BtD8AWrfoeZCDOB5WrqtizXH//n3h5M5XvcRjt/jqYH5+PsrKylq84ihXvG+WR4XzlTSlUgkvL696FwiWHgOtz8NisgFo/b65+pyNTTq/XNqW4ejoqHWBUFNTozXH3BIuEBqDr/ryRYKysjLhYtLPz6/ByTx88/X27duRkpKCw4cPo0ePHkhMTKTUOxOiGqXpqEg2oBkzZuDbb7+t9/UDBw5g2LBh2LNnD9544w1cvXoVjDF07NgRc+fOxfPPP6915Xzw4EG8/PLLuHjxItq2bYulS5da7aBuU+Npf1u3bsW2bdtw9+5dIe1v7Nix8PDwwM2bN5GcnAx/f38EBwfD3t7eqmeN6lJTU4Pc3Fwh1YufwLy8vBAUFGSU3lU5qqurQ35+Pu7du4eCggJoNBoAD1Ydg4KChJVma8fbdHJycpCbm4uamhoAEDbeBQUFWdUFQkMqKiqQm5uLnJwcVFRUQKFQQKFQwMfHB23atLGIOwiGUF1drdVuZmdnh5MnTyIgIABxcXFwd3fHzZs3KfVORqhGaToqkq1AY1J0bt26hblz5+LAgQNwc3PD9OnT8f7772tthGhNKTrAg4L5t99+w9atW7Fhwwb88ccfcHZ2RmVlJTp16oSFCxdi4sSJrSa1Cqg/hcHBwUHor66srNRKeOMrq9Z4a1R8B0HcPuDq6oqamhoUFhYKG96sNfmQkya9eXh4CAVxSUkJSkpKhM14SqXSaj8varVauMPAJ1KIPxuFhYXCajrfl9AaimXgv5+XDz/8EFu2bEF+fj5cXFxQWVmJqKgoTJ06FRMmTLDKQKimovO1ZaGeZCtQU1ODp556CoMGDcLatWvr/T7vxw0MDMTRo0dx7949TJs2Dfb29njvvfcAPLiFEhsbizlz5uD777/Hvn37MHv2bAQFBVnlLZSysjKkpaVhx44d2LVrF6qqqjB69Gg4ODjg+vXruHjxIjZt2oSqqiqMHz/eag/u4nATfgu1oSkMPOFNpVLh3LlzYIxpjVSz5KJAXwx0ZGQkvL29tZ4b709XqVS4ffs2Ll68CE9PT6GfW66bshqDMSZEoPOAE19fXwQHB6Nnz571+lDFY91u3rxpVTHZ0tnjzs7OUCqV6NevX732AnFbxuXLl7U2blpyeMfDiFPv9u/fj5KSEgwePBiBgYHIzc1FRkYGSkpKcPv2bcTGxtYLjmpt6HxtWWgl2Yro27G6e/dujBs3DtnZ2cJ8w6+++gqvv/468vLy4ODg0OpSdJKTk/Hmm29i3LhxiI2N1Zp+IU77S05ORkZGBvr162fxaX8cT+LixSBfJeUn88auiDLGLL4Xs6kx0PpUVVUJxVRRUZGwoVOpVDY5RdEcxBc/4oATPiawsUWN+L2Vl5enFRhjKe+JhnrzG9tawxjTem+JV9ubk6wpNxqNBidPntRKvYuJiUFiYmK91LuSkhJhQSItLQ0XLlyAl5eX+R68TND52jJQkWxF9H3oli1bhtTUVGRmZgpfu3HjBjp06IDTp0+jd+/erW6sC2OsUScpxhju3buHbdu2ITk5Genp6ejSpYsQXmIpG07EbRSFhYXCah/vs27pap++Xf18ZVUuu/r5KikvXowxnkxXUIQcV1aN/TgtJSZbfDdFpVKhvLy8xeMApWpqarT6d21tbbXCOyzhDowhUu8ae9xtDeh8bRla7z2PVkRfQg7/vYa+x1pTdBp7oOYRnfPmzcPcuXP1pv0lJCSgR48esimAxCf+/Px8oZfUz88P4eHhBu8bVSgUcHd3h7u7O8LDw4X5sPfu3cOlS5fMOh9WXwx0WFiYUeZZS4Ma+L/Ng1yas0JrKPpWvHW1D7SUeMxeeHi4ECqSl5eHK1eumDUeWt+88JCQkGbPC2+Ig4OD1nuiqKgI+fn5QpiLXNsyqqurkZ6ejm3btmml3q1ZswYjRoxo8mOlAvnh6HwtL1Qky5ShU3RIy+lL+0tKSkJMTAz8/Pwwfvx4xMfHmzTtj+MFGV8d5G0Ubdq00dlLakwuLi4IDQ1FaGioVtLY1atXhaQxY27y4r2kpoyB1oXP1/Xz80Pnzp2FXl+ebGbs1XZdq6R8NbdLly4mPZk6OzsjJCQEISEhZonJlraUMMbg5+dn8pnWNjY28PX1ha+vLzp16iRsjOQXlOZuy6isrMTPP/+MlJQUSr1rJDpfWy96t8vU4sWLH7pTtUOHDo36uwIDA3HixAmtr+Xm5gq/x/+Xf038PR4eHnRVqoeHhwemTJmCKVOmaKX9PfXUU0ZP++N4MZifny9MnvDz89O52cxcHB0d0bZtW7Rt21brFv/Jkydhb28vFMxeXl7NLgjkFgOti0KhgKenJzw9PYUgF3Fx1JzeV12kveJ8CkdISIhspnCYKiabh73wiRS2trZQKpUmv1jSRxrmwjdB5ufn4+bNm7CzszN6W4Y49S41NRVpaWkICAhAQkICdu7cSal3jUDna+tFRbJMGTJFZ9CgQXj33XehUqmgVCoBPEjI8fDwQJcuXYTvaU0pOoYmTfvbv38/kpKSDJb2x/GVQV5olpaWCgP9O3ToIPvxW+JWBN4GoVKpcPbsWQAQikRfX9+Hnph5DDQvjKuqquDj46N3CoPc8IQ38Wq7OOmOrzA3Zv6wruAPS0n+s7GxgY+PD3x8fLRWVu/evYvff/+9XqjNw14LXRMp/P390adPH5O3dTSVg4MDgoODERwcrDWGUHzxwIvmlry/GWMoLCzEzp0766XeLV26lFLvmojO19aLNu5ZgYel6NTV1aFXr14IDg7GihUrkJOTg2effRazZ8/WGinTmlJ0TKUlaX+cdGYvnyLBexjlXgw2hng1UaVSoba2Vujd9fPzE27x6ouBflhcsCURP8eGkux0JQPywrolq/JyIk031BeTzfudVSoViouL4e7uLtyhsIawF113Stzd3YWCuTFtGZR6Jw90vrYsVCRbgYel6ADAzZs3MXfuXBw8eBCurq6YPn06Pvjgg3rDyVtLio45SNP+srOzMXLkSMTFxQlpf/wklZ2djfz8fDDGhDQr8TQKaygG9eG3f3m7QHl5uVDoVFZWWm0MtC784kE8Zs/FxQUajQaVlZX1WjSs+bUQr5arVCoAgJOTE+rq6rSiopVKpaw2vxmDeDa1+PhQXl6OLl26CJ8XPs6Sp96dOHECUVFRmDBhAhITEy1+nKUlovO1ZaEimRhcaGgobt68qfW1999/H0uWLBF+/dtvv2H+/Pk4efIk/P398dJLL+G1114z9UM1G572x2cxZ2VlCRMGbt26hcuXL2PevHl48cUX4e/vL/s2CkMSj5PjASfOzs5gjKGqqgpeXl7CKqG1999JLxgqKirg5OQEjUajNRXBUOPr5EwccqJSqXD//n2hSBbfXTHU2DZLIb7TNG/ePGRmZqJbt27w9/fHnTt3cOnSJTz++ONCO5i1BiO1FJ23iC7Uk0yM4m9/+xuef/554dfu7u7C/y8tLcUTTzyBkSNH4quvvsK5c+cwa9YseHl54YUXXjDHwzU5GxsbREZG4rHHHkNRURGKiorw66+/wtnZGeXl5ejfvz/CwsLg6OjYKgpkfTHQ0s1m1dXVQsHIx4gZe1KGqYlfC5VKBbVaDT8/P4SGhmoFcohbDC5fvmyV0dD8teA/87q6OmEzpp+fn3BHhbci5OTkICsryypfC31sbGzg7e2Nu3fvYujQocjNzUVmZibc3NxQVlaGnj17YujQoRgyZAgVyA9B5y0iRSvJxOBCQ0OxaNEiLFq0SOfvf/nll3jrrbeQk5MjFD9LlizBtm3bcOnSJRM+UvPZvXs3nn76aXh4eGDcuHEYP348oqOj4eTkpDPtLz4+HnFxcQgNDbWak5x40gUPWBCHWTyspYT/eT65gPfkKpVKi2vDUKvVWsEeNjY2Qn9xY8JeamtrhQuM/Px8ODg4aPUnW9ImLN5WwQtj/loolcpGhZxIWxHkGubSUuLUu+3btyM3N1cr9c7DwwN5eXnYtWsXtm/fjr1798LLywuZmZnw9fU198OXHTpvEV2oSCYGFxoaiqqqKtTW1iIkJARTp07Fyy+/LPRTTZs2DaWlpdi2bZvwZw4cOIDo6GgUFhbC29vbTI/cdPLy8nD79m307t1bbzFnLWl/YpWVlUJhW1xcLKwEt3QmrHS6g0KhEFYSDZEoaAzi+dGFhYVCr7VSqWzRFAZpeAqfB8ynhsixn50X+XwTYlOne+hjDTHZYjz1jhfG5eXliI2NRWJi4kNT76qrq5GRkSH0vRJtdN4iulCRTAzuk08+QZ8+feDj44OjR4/ijTfewMyZM/HJJ58AAJ544gmEhYVhzZo1wp+5ePEiunbtiosXLyIyMtJcD122+MimlJQUJCcn4+eff5Zt2p+YKWKgpcSb3VQqFerq6syacsfpmlDg6ekpvBbGmMIgTpYTj8njBag5ZyZL0//c3Ny0JlIY+gJQV3+3sd+LhiBNvQOA+Ph4TJgwoVmpd0Q3Om8RXahIJo3SkkShf/3rX3jxxRdRXl4OR0dHOtgYgDjtb8+ePWZP+xPTFwPNx7SZcvVOXKTzzV6mLBIbKlJNPb6voSLdVHHhFRUVwsVLWVmZsAnTHEWqOCZbHNFtjphsKX2pdxMnTsTjjz9OqXeNROct0lJUJJNG4f19DenQoYPOouPChQvo1q0bLl26hIiICLptZWA87S8pKQk7d+6Es7Mzxo0bh/j4eKOm/YlJY6Dl2hNriiJN10WCeJazXAocvpLLZxC7uLgIr4WhikRzX6Q0ljgmm/eEGzsmW4yvcu/ZswcpKSlaqXcTJ05EVFSULNtk5I7OW6Sl5HG0JrLXkkShzMxMYfMN8CAt6K233kJtba1QwKWlpSEiIoIONM3Q2LS/4cOHG2zlkjGGyspKofgRJ//JJQZaF1dXV4SFhSEsLEzrdj+fDtHc2/3iTYR8s5ic4o91cXJyQrt27dCuXTutjYOnT5/W2kTZ1J5u6WxnPp0jPDxcVhcJYvpisi9dulRvvJyhCntx6l1qair279+P8PBwJCQkUOqdgdB5i7QUrSQTg8rIyMDx48cxfPhwuLu7IyMjAy+//DLGjBkjDFAvKSlBREQEnnjiCbz++us4f/48Zs2ahX/84x80SseA9KX9xcfHY9SoUU3ugdUXA81PRJac/NecjWPS2/XWMnZM19g1X19foadb150JS9w42Rh8Zjd/XmVlZS3qIxen3qWmpuLQoUPo0aMHJkyYgIkTJ1rkZlxrQOctog8VycSgTp8+jXnz5uHSpUuorq5GWFgYnn32WfzlL3/RKqLEQ9n9/Pzw0ksv4fXXXzfjI7du+tL+4uPjMWbMGL2311tDDLSUvhFk/v7+sLe3F1Zcy8vLLWLjV0vo2njJL4y8vb2FjXCWPoKvsRobky3GU+9SU1ORmppKqXcyROctog8VycTqfPHFF1i5ciVycnLQs2dPfPbZZxgwYIC5H5Zs8LQ/XjBfvnwZw4cPR1xcHMaNG4fS0lJs3boVBw4cwMKFC4Xo49YQAy2lVqtx584d3Lt3D+Xl5QAgFEahoaGtbrJAcXExbt68icLCQqjVatjY2MDLywtt27aFv7+/xa4YN4d09fzKlSvYu3cvxo0bh7i4OKhUKqSkpCA1NRXnzp2j1LtGoGM3kRsqkolV2bRpE6ZNm4avvvoKUVFRWLVqFbZs2YKsrCyht4z8F2MMly5dwurVq5GUlITs7GwAQHBwMOLi4vDaa68hICDAzI/StOrq6rSCPXjrgL+/P+zs7ITe46qqKqENga8yW6PKykphsyOfiKFUKuHl5SW0IhQUFAgryXyzZmsqAhljyMzMxIoVK3Dw4EGUlpbCxsYGXbp0wYwZMzB9+nT4+vq2qtekqejYTeSIimRiVaKiotC/f398/vnnAB6smrZr1w4vvfQSlixZYuZHJy8HDx5EUlISUlNTkZ+fj5iYGAwePBhlZWXYt2+fVaf9SfHpHDzY42E9yXycGi8exa0XSqXSoleYdc0TFk+k0NV7Ll1VBaDVk2yNbTnAg+PLr7/+im3btmml3kVFRaGmpgZ79+7F0aNH0bt3b8TFxeHpp59Gp06dzP2wZYmO3USOqEgmVqOmpgYuLi748ccfkZCQIHx9+vTpKC4uRkpKivkenAzNnDkTjo6OwuQLcWEnTvtLSkrCL7/8YvFpf1LimcElJSVabSVNnW7BN/HxJEF3d3ehqHRzczPiszAMxpiQTKdSqVBbWysEsPj5+TVpIgXf4MmL7OrqamFOtp+fn2zGvjVXU1Pv8vPzhQkWo0aNwpw5c8z0yOWLjt1ErqhIJlYjOzsbbdq0wdGjRzFo0CDh66+99hrS09Nx/PhxMz46y6Ur7S80NBTjx4+XddqfFN+Exou3yspKrWAPQ63+6luVbmnctKHxec789QAgFPaGWv0VT4fgK+5eXl7CKrOlbHbUlXoXFxeHxMRESr0zADp2E7mS38BKYjE0Go1FFEekZRQKBXx9fTFr1izMmjULpaWl2LFjB5KTkxETEyOk/SUkJKB///6yurWu0Wi0gj14RHWHDh2avELaWA4ODmjTpg3atGkjTAdRqVTC/GFeMJtjfrJarRZei/z8fGGec8+ePY3SR6xQKODu7g53d3d06NBBa2zelStX4OrqKhTm7u7usrmAALRT73bv3g03NzfEx8dj06ZNlHpHSCtBn3LSZDU1NXBwcJBdgezn5wdbW1vk5uZqfT03NxeBgYFmelTWx8PDA1OnTsXUqVO10v6efPJJs6T9SfH0ND6azM7ODkqlEl27doW3t7dJ37d2dnYICAhAQECAULCrVCqcO3cOjDGhpcGY4/T42DK+ss0L07CwMJPPc3Z2dkZISAhCQkKEAJa8vDzcvHkT9vb2QruLqX9OQMOpdzt37sTAgQNldQFoTejYTeSK2i1Ik61duxbfffcd1q5di44dO9b7fXOuMEdFRWHAgAH47LPPhMcSEhKCBQsW0OYPI6upqcG+ffuQlJSElJQUaDQaYRyWIdP+dJFGLLu6ugq39OW2Qgk8KMh4365KpdLq2zXEpAw+kULcb81XsF1cXAz0LAxHfAHBo7zFFxDGWrXVlXrXoUMHIdyDUu9MR07HbsYYNm7ciN69eyMyMtKk/zaRFyqSSbN4e3vj22+/RVxcHOrq6mBrawvGmNmLkU2bNmH69OlYs2YNBgwYgFWrVmHz5s24dOlSqxtlZk7itL9t27ahrKwMMTExzU77kxJPlxAnofFb93IsBPXhfbv8ufBJGfy5NKbfVfx3qFSqRk2kkCt+AcEveu7fv2/QZMeGUu8SExMRGRlp9uNYayS3Y/fs2bNx7949vPLKKxg+fDi1F7ZSVCSTJlOr1XjuueegUCiwfv164esrV67EF198gZSUFPTs2dNsj+/zzz8XBtL36tULn376KaKiosz2eFo7jUaD48ePIykpqUlpf1KMMRQXFwutA9XV1cKcYmuYmsDdv39fKHbFUzeUSqXWxQV/PXhxXVNTo/V6WMvcZj6FhM9p5qviTYmFZozh1q1bQrgHpd7Jk5yO3WVlZVi5ciW2bNmCs2fPWs3xhTQNFcmkSfjV9Oeff44vv/wSFy5cwO3bt7FixQps2LAB77//PmbNmkWbWohO+tL+4uPjERsbWy9woby8HBUVFULvKmD9sdhi4kkZBQUFcHZ2hru7uzBmjTHWKuYRc9JYaGdnZ2HTn7+/v9bzZ4zh8uXLSE1NRUpKCs6dO4fHHnsMiYmJSEhIQJs2bagwJtBoNGCM6fzsaDQahIeH4+mnn8Ybb7wBT09PMzxCYk5UJJNmuXbtGuLj4zFt2jTs3bsXtbW1WLZsGUaMGGHuh2Yy77zzDpYvX671tYiICFy6dAnAgz7ZxYsX44cffkB1dTViYmKwevVqavv4f4wxZGVlISkpCcnJycjMzMSjjz6K6Oho1NTU4NChQzh+/DhWrVqFqKgoKJVKeHp6trpbnmq1Gvn5+cjNzUV+fj6AB6+deFOgOSZlmBufHJKXl4c1a9YgOTkZw4YNQ58+fVBSUoJdu3bh6tWrGDFiBCZOnIj4+HhKvft/reXYpa8FkLcISuXn58PPzw/Agw3A9vb2WLNmDdatW4dXX30VEydONPpjJvJCRTJptu7du+PChQuYN28eli9fDl9f3xb/nRqNBgqFwiJOZO+88w5+/PFH/Pzzz8LX7OzshIPs3LlzsXPnTqxfvx6enp5YsGABbGxscOTIEXM9ZNm6fv061q9fjw0bNuDatWsAgMDAQCQkJGDevHno0KGDRbwnDEU6a9nZ2VnYeOfu7i5sOOOtFq1tRVlMo9EgIyMD//znP5Geno6KigrY2tqiT58+eO655/Dkk0/Cx8fH3A9TVlrDsSsrKwsRERHCr/WdWwoLC/HKK69g8+bN6Nu3LyZPnoy5c+dCrVbDzs4Oubm5mD59OkJCQvD111+b+mkQM6N74qRJ+JX57du30aVLF0RERAgxog19vz68faOoqAgODg4t3tBlanZ2djpHFJWUlGDt2rXYsGEDoqOjAQDr1q1DZGQkjh07hoEDB5r6ocrSN998g88++wwXL17E8OHD8fLLL2P8+PGws7MT0v769u2LLl26CPHY1pD2p4u+XuROnTrV+1woFAr4+fnBz89Pqzc5KyvLanuTxfSl3q1btw6jR4/GlStXsG3bNqxevRrz58/H0KFD8be//Q2DBw8290OXDWs+dm3atAmbN2/GmjVrhMKf32mpqanBv//9b1y9ehWTJk1CQUEBXF1dsX37duzcuRPz58/HY489hm7dugEAAgIC0KtXL5w6dQrXrl1DeHi42Z4XMT0qkkmznD17Fr///rswmkff7StezNTV1QFAve/hv79u3Tq8/vrrePXVV7F06dJ6SVxymJyhy5UrVxAcHAwnJycMGjQI77//PkJCQnDq1CnU1tZi5MiRwvd27twZISEhyMjIsIgTjSn4+Pjg9ddfx9ixY+Hl5aX1e/PmzcPcuXO10v5WrFiB0NBQIR7bUtL+dBFP6OBpdN7e3ggMDET37t0bneKmUCjg7e0Nb29vdOrUSZhy8ccff+DChQsWO+VCiqfepaSkYOfOnWCMIS4uDmvWrKmXete7d2/07t0by5cvx40bN5CamgoPDw8zPnr5scZjF190OX36tLAyrlarYWNjg71796KkpAT79+/H4cOH4e3tjc8++wxdunTB119/jV69emH48OHYuXMnvvnmG3z44YfC56Vr165IT09Hbm4uFcmtDBXJpEl4oXr+/HloNBo88cQTAFBvw4xCocCxY8dw584djBkzRu8KsUKhgFqtxsWLF+Ho6Ij//Oc/ePPNN4XfLykpQWVlJYKCgmRXKEdFRWH9+vWIiIjAvXv3sHz5cjz22GM4f/48cnJy4ODgUK/wCwgIQE5OjnkesAwlJiY2+PuWnPani775yCEhIQaZjyxOuAsPDxfmJd+7dw+XLl2S/bxkKWnqnaurK+Lj4/HDDz80OvUuLCwMf/7zn03waC2HJR67eGdoQ+cAGxsbaDQaODk5wc3NDQCE98g777yDmzdvYsKECTh16hTs7OwwduxY3L59W2tD3p/+9CesX78eixcvRrt27QAA/fv3R1ZWFrXttEJUJJMm++OPP7B//35EREQIt3vFBy7+/ysqKrBixQo899xzCAwMxO7du9GhQwfh+/ify8zMRF5eHvr164c7d+6gvLxcOMBt374d06ZNQ1lZmexaMcaMGSP8/x49eiAqKgrt27fH5s2b662EE8NoTNpfQkICBg8eLJs2A41Gg6KiIqEw1mg0QhuFsSd0uLi4IDQ0FKGhoVrJe1evXhWS95RKpcmT9xpSWlpKqXdGZonHLvH7U6PRAIDOu0g2NjY4e/YsIiMjUVNTA3t7eygUCkyZMgVLly7FgAEDhLsOL7zwApYsWYIbN24gLCwMADBt2jQsW7YMFy9eFIrk9u3bQ6PRoKKiwthPk8iMZd6nJGbl4uKCbt26Ydy4cQD+e8CSGjFiBI4fP46jR49i+vTpwgFH6uTJk1CpVJg0aRICAwOxd+9eAA+K7F9++QW9e/eGq6ur0LIBPGjfkNueUy8vL3Tq1AlXr15FYGAgampqUFxcrPU9FLNqOC4uLpgwYQL+/e9/IycnB9988w00Gg2mT5+O8PBwzJs3Dz/99BOqq6tN/tjq6uqQm5uLc+fOIT09HRcuXIBCoUC3bt0wdOhQdOvWDUql0qQFn6OjI9q2bYs+ffpg6NChCA0NRUVFBU6ePInDhw8jKysLRUVFJv9cMcZQUFCA7777Dk8++SRCQ0OxYsUKdOnSBenp6bhy5Qo+/vhjPProo1QgG4klHLuKioowefJkZGZmwsbGRmeBzM8Rnp6eOH/+PBwcHITz06OPPop27dqhoKBA+P6YmBjU1tbizJkzwveFhITgkUcewc8//ywcO7KysjBw4EDZXEgS06EimTSZUqnEJ598gpkzZwKo32csplAo0LVrV7z55pv1VvYUCgUYYzh9+jQ8PDwwe/Zs5Ofno6qqCgCQk5OD3bt345lnnhG+n7O1tRX+vFyUl5fj2rVrCAoKQt++fWFvb499+/YJv5+VlYVbt25h0KBBZnyU1snBwQFjxozB//7v/yI7Oxs//vgj3NzcsHDhQoSFhWHWrFnYtm2bUVeCampqkJ2djczMTBw8eBBXr16Fk5MT+vTpg8ceewydO3eGr6+vLHqo7e3tERQUhB49emDo0KHo3Lkz1Go1zp49i19++QUXL14U4qGNgTGGe/fu4euvv8b48ePRoUMHfP311xg8eDBOnz6NCxcu4N1330Xfvn1l8XpZO7keu/gMY+BByuu+ffuwZ88enD59Gn/5y1+wa9cuAP9txeDvlccffxzHjh0DY0z4Wr9+/dCmTRtcunRJOA64u7ujT58+OH78uFYryahRo/DDDz+gqKgIAFBcXCwEnJDWhUbAkSZjjGkdfJr7dygUCly4cAELFy5E3759hdaMyspKbNy4Edu3b0d8fDxycnKgVCoBAMeOHcPOnTvh7e2NZ555Rvi6rr+7sV9vrldeeQXjx49H+/btkZ2djb/+9a/IzMzExYsX4e/vj7lz52LXrl1Yv349PDw88NJLLwEAjh49arDHQBpmqLQ/faqqqoQ2iuLiYri7uwub5HjLkCXRaDRaqYa1tbXw8/MTJmW0JCRIX+pdQkICJk6cSKl3JiTnYxdjDBqNpt7iS0FBAbp3747S0lJoNBqMGTMGS5cu1Vm4/vbbb+jbty8OHTqEgQMHChvLly5dikOHDmHlypXo378/AODbb7/FkiVL8N1332HUqFEAHoyFKy0tRWhoKADg9u3bOHLkCCZPnmzU507kh3qSSZMZYo6xeHNfRUWFMJopICAA6enpAIDU1FR06tQJSqUS5eXl+P777zFv3jyMHz8ed+7cwcqVK/Hxxx9j6tSp9R4f8GBMFF9xFn/dUO7cuYMpU6agoKAA/v7+GDJkCI4dOwZ/f38AwD/+8Q/Y2Nhg4sSJWgP5ienY2Nhg0KBBGDRoED788EOcPXsWSUlJ+OSTTzB37twG0/704dMj+EQKLy8vKJVKdOvWrdETKeTKxsYGPj4+8PHxQadOnVBWVgaVSoXr16/j/Pnz8PX1FeYxNyamV1/q3dSpU7F582ZKvTMTOR+7FAqFUCDv27cPR48eRWxsLIKDg9G+fXucPHkSv/76a4OrupGRkRg0aBC++OILrQ29MTEx+Omnn3Dq1CmhSB4/fjySkpK0Flz4Z4Br27YtFcitFSPEjBYsWMBiYmJYXl4eY4yxzZs3s969e7P9+/ezyMhI9te//pUxxtj69etZjx49hF8zxtibb77JunXrxoqLixljjNXV1bHVq1ezsrKyev/OX/7yF3bhwgXGGGMajYYxxpharTbiMzO89PR0Nm7cOBYUFMQAsOTkZK3f12g0bOnSpSwwMJA5OTmxESNGsMuXL2t9T0FBAZs6dSpzd3dnnp6ebNasWTpfL2un0WjY77//zt59913Wt29fZmdnx4YOHco+/vhjduXKFVZeXs4qKipYRUUFKy0tZRkZGSwzM5Pt3buXpaamsiNHjrArV66woqIi4fus/T+VSsUuXLjADhw4wFJSUtjBgwfZ+fPn2alTp7S+r6ysjGVkZLAlS5awLl26MAcHBzZmzBj2zTffMJVKJXz+WovW/LnVaDSsrq5O5++p1Wq9x+AvvviCtWnThgUGBrKnn36affvtt6yqqooxxlibNm3YihUrHvpv79ixgwUFBbHdu3cLX6utrWXdu3dnL7zwAquurm7GMyKtDTV7EbP5/fffceTIEYSGhgoD3wcPHoxz587ht99+Q1ZWFqZPnw4ASE5ORteuXTF79mzhz48aNQpqtRoZGRkAgL1792L+/Pn48MMPMWPGDLz66qu4fv06srOz8Y9//EPodVar1QCADz74AC+88AJUKpUpn3azVVRUoGfPnvjiiy90/v6KFSvw6aef4quvvsLx48fh6uqKmJgY4XkDD8YbXbhwAWlpadixYwd++eUXvPDCC6Z6CrKhUCjQuXNnvPnmmzh58iQuX76M8ePHIzk5GZGRkYiOjsbcuXPx1FNPISwsDAkJCbh//z46duyIYcOGoVevXggODm7Uaqq1cHV1RWhoKAYMGIAhQ4YgMDAQp06dQlRUFLp3745nn30Wzz//PHr06IERI0YgKysLb7zxBnJzc7Fz504899xz8Pf3b3Urx63tc8sYEzbQKRQKrbY89v+tesCDfSW69rPcvXsXGzZswKJFi3Dv3j388MMPSExMFGYWx8bGYuvWraitrW3wccTGxiI2NhYff/wxcnNzATwYB7d+/XqsWrWq3mfXWP33xMKZuUgnrVhZWRn79ttvWVpamvC1u3fvsoEDB7KAgADWtWtXxtiDVZR+/fqx5cuXa608nDx5knl6erL09HTGGGMvvfQSUygUbOLEieyf//wnmz9/Phs3bhxTKBTM19eX/fTTT8KfLS8vZ5MnT2YxMTGspqbGRM/YcCBZkdJoNCwwMJCtXLlS+FpxcTFzdHRkGzduZIwxdvHiRQaAnTx5Uvie3bt3M4VCwe7evWuyxy5XFRUVbOvWrWzixInMxcWFOTg4MIVCwUJDQ9mbb77JTp06pbXC3Nr/KykpYbt372bTp09nnp6ezNbWltna2rKAgAC2cOFCdvjwYb2riK1Va/vcnjhxgj3//PNsxIgRWl+vrq5m3377LYuJiWHR0dFs9erV7NatW4wxxn744QfWpUsXtmfPHqbRaNjVq1e1jvv79u1j9vb27OrVq3rvSvCvq1QqFhsby6ZOncpu375tpGdJrBmtJBOzcXNzw7Rp04RkJ41Gg+DgYAQEBEClUmHKlCnC1728vFBeXi6sPDDGcPLkSdTV1eHxxx8H8GAledKkSfjXv/6FhQsX4tNPP8WWLVsQFhYGPz8/TJw4EUqlEqdPn8bFixdx9+5dDB8+XJi6Icexco1148YN5OTkaKVkeXp6IioqSlhpz8jIgJeXF/r16yd8z8iRI2FjY4Pjx4+b/DHLhUajwaRJk+Dn54clS5YgPDwc+/btQ2VlJfLy8rB06VKcPXsWgwcPRr9+/bB8+XJkZma2ypWnmpoapKWlYf78+ejYsSOeffZZ2Nra4vvvv0d5eTnKysrw9ddfo7S0FHFxcQgODsZHH31k7octW9b4uT1x4gSeffZZeHl5ITo6Gnl5eVi0aJFwbL116xZeeOEFfPzxx+jfvz+GDBmCr7/+GnPmzAHwIOikb9++SEhIQL9+/fDqq6+ie/fuWLBgAcrKyhAdHQ0vLy9s2bJFuCtRUlIC4L+rwXzykb+/Pz777DN07dqVNkyTZqGNe8SsmGjiBL8tt27dOnz//fd46qmnAEBIJDt69ChKSkrg6emJtLQ0/Oc//0F8fDwAIC0tDZWVlZg0aRI8PDyE6Rv37t3DzZs3cezYMfTr1w8ZGRno2rUr1q5dC1tbW7Rv3x6XL19Gp06dLHoGKx9fFBAQoPV1cUqWeEoIZ2dnBx8fn1adAmhjY4Nx48bhr3/9K7p06aLVDvCwtD8ej20JaX/NxVPvUlNTsWvXroem3sXFxSEuLg5qtRqHDh3Smm9OtFnb5zY1NRVTp05FZGQkdu/ejV69etULJ7GxsUG/fv2watUqIdWva9eumDx5Mn7//XdERkbio48+EjZkFxYWIjs7G//85z/xyCOP4M9//jP+9Kc/4csvv0R6ejrOnz+PmTNn4m9/+5tWawf/HIeFhWHJkiWtrs2HGAYVycSsdB24vL29sWDBAq2vvfbaa5gyZQr69euHIUOGYPv27Rg5ciTeeustAMDWrVvRsWNHdOvWDcB/i++UlBQEBAQgPDwcADBo0CDU1NTg6NGjuHjxInbs2IGPPvoI165dw9///nfMmzdP78GU/5337t1DcXExIiMjDflSEDOaNm3aQ79Hmva3Z88eJCcn10v7e/TRR1s0Kk0OpKl3SqWyyal3dnZ2GD58uAkeLTE3fmwMDw/HkCFD0L17d70zldu2bYsXX3wRRUVFWLZsGb7//nuUlpYCALZs2YJly5ZBqVRi9OjRwp/Jzc3Fd999h7KyMgDA8uXL0aNHD5w9exaLFy/WWonXhWZtk+ay7CM5sVpMMtM4IiICGRkZ2LhxI44dO4ZPPvkETz75JFxcXAA8mN85fvx4IdWP/9nNmzdjzJgx8Pb2Fv7O8+fP49y5c+jduzfeeOMNdOnSBR988AE+/fRTTJ48Gb6+vnofT1FREV588UW4ubnhww8/1JsiaGo8CSs3NxdBQUHC13Nzc4VRSYGBgfU2KarVahQWFlIKYBO5uLggMTERiYmJqK6uxv79+5GUlITp06eDMYbY2FjEx8dj2LBhwoYjOWOMobCwEDt37kRqair279+PDh06YMKECXj77bfRu3dvKjSMwFo+t/x4Gx4ejm7duuHw4cPC723ZsgXr1q2Dvb09vvrqKwQFBUGj0eCtt97C5cuXsXz5csTGxmLZsmVISkrCa6+9BgDYtWsXgoODcfXqVWzYsAFKpRJz584F8OCClYdZEWJMdNQjsiRdzWWMwdHRETNmzMBXX32FadOmCQXyiRMncPnyZXTt2lW4tccL2lOnTuHpp5/W+ruOHDkCR0dHvPrqq+jatasw6YAxhnPnzul9PIwxLF68GLW1tfjyyy+FAlkOvalhYWEIDAzUSskqLS3F8ePHhRWdQYMGobi4GKdOnRK+Z//+/dBoNIiKijL5Y7YWjo6OWml/W7ZsMXnaX3Ow/0+9+9///V+t1LtBgwZR6p2JyOlzy/4/xKMlnJyc0Lt3b6hUKvTo0QM+Pj54++23ER4ejqVLlwptI4cOHcJ3332Hd999F8888wzc3NxQXFyMa9eu4fLly3BycsLx48cxZ84cvPPOO4iIiMDXX39dbwGDiaZlEGIMtJJMLAIvmvkBUfzrAQMG4OjRo8JKDE9X+u2336DRaNC2bVvhz9TV1eHMmTNQKpVaJ5h79+7B29tbSEmTrmQDwJdffon9+/dj27Zt8PT0FL6HFxAajcYgQSv6lJeX4+rVq8Kvb9y4gczMTPj4+CAkJASLFi3C3//+dzzyyCMICwvD0qVLERwcjISEBAAPBuyPHj0azz//PL766ivU1tZiwYIFmDx5MoKDg43ymFsbOzs7DBs2DMOGDcOnn36K48ePY+vWrVi2bBmef/55jBo1CnFxcQZJ+2sOJkq92759O06cOIEBAwYgISEB33zzDaXeGYGlfG75saumpqZZow358bBHjx4ICQlBSUkJTp06haCgoHohO97e3qitrRXadn799VeUl5ejoqICW7duRY8ePbBw4UK8/PLLDa6W03uVGJ2JpmgQYnJXr15lQ4YMYaNGjWL79+9njDGWmZnJRowYwd544w3h+yorK9mcOXNYdHR0veH2fJTQb7/9xjp16sT+/ve/M8YeDKXnf19ubq4png47cOAAA1Dvv+nTpwuPdenSpSwgIIA5OjqyESNGsKysLK2/o6CggE2ZMoW5ubkxDw8PNnPmTIsIJbB0dXV17PTp0+ztt99mXbt2ZQ4ODiwmJoatXr2a3bx506ij5crLy9mZM2fYO++8w3r37s3s7OzY8OHD2aeffspu377d6sI9TE2On1v+M5f+7CdNmsQWLVokHN90aSgEhLEH4zUXLlzIBg8eLHytrq6u3r8VHR3NOnbsyDp16sR8fX3Zjz/+yDIyMphKpar3WGmUIDEXBWN0r4JYrwsXLmDlypX49ddfkZaWhuTkZHz55Zf46KOPEBMTAwA4ffo0XnnlFURFReH999+HRqOpd3t51apV+Mc//oEzZ87Ax8cHtbW1sLe3R2RkJMLDwzFhwgTk5OTgqaeeQqdOnbRWoqXx2ABQVVVl8RHGpHkYY8jKykJSUhKSkpJw9uxZPProo4iPj8f48eMRFBTU4hUyjUaD8+fPIyUlBampqbh69SpGjBiBiRMnIi4uDn5+frQK18oVFhYK0csajQaFhYXo0aMHVq9ejYSEBJ3HQbHKykrY2dnpXHVev349PvjgA/zrX//C4MGDha9fuXIFt2/fRnR0NLKzs5Geno6ioiI8+eST9SZ4ECIH1GhGrFrXrl2xfv16nD9/HkFBQWjXrh0GDBig1Wpx5swZlJeXY9SoUTr/jpycHGGEnI+PD+rq6mBvb4+qqipcv34dJ0+exB9//IGjR4+iX79+2L9/PxQKhbDZxs7OTqsgKS0txcsvv4xvvvnGuE/eCH755ReMHz8ewcHBUCgU2LZtm9bvz5gxQ7hty/8T71IHHpyc//SnP8HDwwNeXl547rnnUF5ebsJnYV760v62bt2Kzp07Y+TIkfjnP/+JGzduNKnfUqPR4MSJE3jrrbfQs2dPSr0DvV/1ee+999CzZ0989NFHqK2thY2NDbZv3w4nJyeMGDFCb4FcVVWF1atXY9CgQXBzc8OJEye0fp+/X3v06IHg4GCkpaUhLy8Pb775Jjp37oyIiAh8/vnnAIDg4GBMmTIF8+bNg1KplMXeDkKkqEgmVo2JIlIBYPz48Vi7dq0wn1OtVuPYsWOorKwUVjykJ4fq6mqcP38eI0aMAAAhDnXTpk2ws7PDF198gf/5n/9BUlIShg4divfffx8fffQRpkyZgjZt2uDjjz8WHkNdXR08PDxQVFSEGzduAJDHxr/GeljELgCMHj0a9+7dE/7buHGj1u9bUsSusSkUCoSFhWHx4sU4dOgQbt26hWeeeQb79u1D7969MWTIEHz44Ye4dOmSzoJZrVbjl19+weLFixEZGYmEhATk5ubiww8/RG5uLpKSkvDMM8/Ay8ur1RTGYvR+1e2ll17C8uXL8emnn2L69Omoq6vDb7/9hoiICLi7u+tdQU5PT8fevXsRGxuLzMxMDBkyROv3+XusY8eOaNu2LZYvX46goCCkp6fj1VdfRUVFBZKSkrT+DH9f0+ZQIktma/QgxAx09bbl5+cL0db6ft/Ozo5duHCBMfYgUpUxxoYNG8YmTpzIiouLhe998cUXmbe3N3vvvfdYdnY2+/jjj1mnTp3Y77//rvV3LlmyhC1cuFD4uywRJBG7jDE2ffp0Fh8fr/fPWHLErilpNBqWl5fH1q5dy2JjY5mjoyPr3Lkze+2119gvv/zCkpOT2YwZM5i/vz/z8/Njs2bNYtu3b2f3798390OXLXq/1nfixAnWrl07Fhsby5ydndmmTZsYY7qPg4yxBnuRpfbv38/27t1b7++i/mJiSejSjbQqulYrfH19hWhr8e8zUYxqUFAQ3NzcwBiDg4MDNBoNDh8+jHHjxsHDwwPAgxXhvXv34sUXX8Rrr72GoKAgjB07FrW1tUhLSxO+B3gQyX3y5Mlm7SKXu4MHD0KpVCIiIgJz585FQUGB8HuWFrFrLgqFAn5+fpg1axZ27NiB3NxcLF26FNeuXcPw4cMxY8YMODs7Y+PGjcjOzsbatWsxbtw46nNvhtb6ftVoNOjfvz8OHjwIb29vVFVVITs7G8CD46CuO1xNSZUcPnw4Ro0aJfxdjFaMiQWiEXCE6MFvHTo7O6N79+74448/EBISAuBBwp+npycGDBggfN/Zs2dx8+ZNPP3008LJxMbGRisYoLa2Fo6Ojjh79qwwmu5hG2QsyejRo5GYmIiwsDBcu3YNb775JsaMGYOMjAzY2tpaVMSunHh6egppf7du3YKnpyc8PT3N/bAsXmt+v/JjTlhYGLy8vODt7Y2VK1dCpVLhvffeM+gxyVqOb6T1oSKZkIfo3Lkzzp8/r7Wy8tFHH6FLly5o06aN8LWtW7ciIiICERERwteOHDkCAEIwAE9f+/XXX/Hcc89ZVYEMAJMnTxb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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "test_flight.prints.burn_out_conditions()\n", + "test_flight.prints.apogee_conditions()\n", + "test_flight.altitude()\n", + "test_flight.vz()\n", + "test_flight.plots.trajectory_3d()" + ] + } + ], + "metadata": { + "colab": { + "name": "getting_started.ipynb", + "provenance": [], + "toc_visible": true + }, + "hide_input": false, + "kernelspec": { + "display_name": "Python 3.10.0 ('rocketpy_dev')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.0" + }, + "vscode": { + "interpreter": { + "hash": "18e93d5347af13ace37d47ea4e2a2ad720f0331bd9cb28f9983f5585f4dfaa5c" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/reference/classes/aero_surfaces/AirBrakes.rst b/docs/reference/classes/aero_surfaces/AirBrakes.rst new file mode 100644 index 000000000..f9adfdeb5 --- /dev/null +++ b/docs/reference/classes/aero_surfaces/AirBrakes.rst @@ -0,0 +1,5 @@ +AirBrakes Class +--------------- + +.. autoclass:: rocketpy.AirBrakes + :members: \ No newline at end of file diff --git a/docs/reference/classes/aero_surfaces/index.rst b/docs/reference/classes/aero_surfaces/index.rst index fbc51d9ab..5cbb9eedb 100644 --- a/docs/reference/classes/aero_surfaces/index.rst +++ b/docs/reference/classes/aero_surfaces/index.rst @@ -12,3 +12,4 @@ AeroSurface Classes TrapezoidalFins EllipticalFins RailButtons + AirBrakes diff --git a/docs/user/airbrakes.rst b/docs/user/airbrakes.rst new file mode 100644 index 000000000..ca914660d --- /dev/null +++ b/docs/user/airbrakes.rst @@ -0,0 +1,437 @@ +Air Brakes +========== + +Air brakes are commonly used in rocketry to slow down a rocket's ascent. They +are usually deployed to make sure that the rocket reaches a certain altitude. + +Lets make a simple air brakes example. We will use the same model as in the +:ref:`First Simulation ` example, but we will add a simple air +brakes model. + +Setting Up The Simulation +------------------------- + +First, lets define everything we need for the simulation up to the rocket: + +.. jupyter-execute:: + + from rocketpy import Environment, SolidMotor, Rocket, Flight + + env = Environment(latitude=32.990254, longitude=-106.974998, elevation=1400) + + Pro75M1670 = SolidMotor( + thrust_source="../data/motors/Cesaroni_M1670.eng", + dry_mass=1.815, + dry_inertia=(0.125, 0.125, 0.002), + nozzle_radius=33 / 1000, + grain_number=5, + grain_density=1815, + grain_outer_radius=33 / 1000, + grain_initial_inner_radius=15 / 1000, + grain_initial_height=120 / 1000, + grain_separation=5 / 1000, + grains_center_of_mass_position=0.397, + center_of_dry_mass_position=0.317, + nozzle_position=0, + burn_time=3.9, + throat_radius=11 / 1000, + coordinate_system_orientation="nozzle_to_combustion_chamber", + ) + + calisto = Rocket( + radius=127 / 2000, + mass=14.426, + inertia=(6.321, 6.321, 0.034), + power_off_drag="../data/calisto/powerOffDragCurve.csv", + power_on_drag="../data/calisto/powerOnDragCurve.csv", + center_of_mass_without_motor=0, + coordinate_system_orientation="tail_to_nose", + ) + + rail_buttons = calisto.set_rail_buttons( + upper_button_position=0.0818, + lower_button_position=-0.618, + angular_position=45, + ) + + calisto.add_motor(Pro75M1670, position=-1.255) + + nose_cone = calisto.add_nose( + length=0.55829, kind="vonKarman", position=1.278 + ) + + fin_set = calisto.add_trapezoidal_fins( + n=4, + root_chord=0.120, + tip_chord=0.060, + span=0.110, + position=-1.04956, + cant_angle=0.5, + airfoil=("../data/calisto/NACA0012-radians.csv","radians"), + ) + + tail = calisto.add_tail( + top_radius=0.0635, bottom_radius=0.0435, length=0.060, position=-1.194656 + ) + +Setting Up the Air Brakes +------------------------- + +Now we can get started! + +To create an air brakes model, we essentially need to define the following: + +- The air brakes' **drag coefficient** as a function of the air brakes' + **deployment level** and of the **Mach number**. This can be done through + a ``CSV`` file which must have three columns: the first column is the air brakes' + **deployment level**, the second column is the **Mach number**, and the third + column is the **drag coefficient** added to rocket due to the air brakes at that + specific deployment level and Mach number. + +- The **controller function**, which takes in as argument information about the + simulation up to the current time step, and the ``AirBrakes`` instance being + defined, and sets the desired air brakes' deployment level. The air brakes' + deployment level must be between 0 and 1, and is set using the + ``deployment_level`` attribute. Inside this function, any controller logic, + filters, and apogee prediction can be implemented. + +- The **sampling rate** of the controller function, in seconds. This is the time + between each call of the controller function, in simulation time. Must be + given in Hertz. + +Defining the Controller Function +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Lets start by defining a very simple controller function. + +The ``controller_function`` must take in the following arguments, in this +order: + +1. ``time`` (float): The current simulation time in seconds. +2. ``sampling_rate`` (float): The rate at which the controller + function is called, measured in Hertz (Hz). +3. ``state`` (list): The state vector of the simulation. The state + is a list containing the following values, in this order: + + - ``x``: The x position of the rocket, in meters. + - ``y``: The y position of the rocket, in meters. + - ``z``: The z position of the rocket, in meters. + - ``v_x``: The x component of the velocity of the rocket, in meters per + second. + - ``v_y``: The y component of the velocity of the rocket, in meters per + second. + - ``v_z``: The z component of the velocity of the rocket, in meters per + second. + - ``e0``: The first component of the quaternion representing the rotation + of the rocket. + - ``e1``: The second component of the quaternion representing the rotation + of the rocket. + - ``e2``: The third component of the quaternion representing the rotation + of the rocket. + - ``e3``: The fourth component of the quaternion representing the rotation + of the rocket. + - ``w_x``: The x component of the angular velocity of the rocket, in + radians per second. + - ``w_y``: The y component of the angular velocity of the rocket, in + radians per second. + - ``w_z``: The z component of the angular velocity of the rocket, in + radians per second. + +4. ``state_history`` (list): A record of the rocket's state at each + step throughout the simulation. The state_history is organized as + a list of lists, with each sublist containing a state vector. The + last item in the list always corresponds to the previous state + vector, providing a chronological sequence of the rocket's + evolving states. +5. ``observed_variables`` (list): A list containing the variables that + the controller function returns. The return of each controller + function call is appended to the observed_variables list. The + initial value in the first step of the simulation of this list is + provided by the ``initial_observed_variables`` argument. +6. ``air_brakes`` (AirBrakes): The ``AirBrakes`` instance being controlled. + +Our example ``controller_function`` will deploy the air brakes when the rocket +reaches 1500 meters above the ground. The deployment level will be function of the +vertical velocity at the current time step and of the vertical velocity at the +previous time step. + +Also, the controller function will check for the burnout of the rocket's motor +and only deploy the air brakes if the rocket has reached burnout. + +Then, a limitation for the opening/closing speed of the air brakes will be set. +The air brakes deployment level will not be able to change faster than 20% per +second, in our case. + +Lets define the controller function: + +.. jupyter-execute:: + + def controller_function( + time, sampling_rate, state, state_history, observed_variables, air_brakes + ): + # state = [x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz] + altitude_ASL = state[2] + altitude_AGL = altitude_ASL - env.elevation + vx, vy, vz = state[3], state[4], state[5] + + # Get winds in x and y directions + wind_x, wind_y = env.wind_velocity_x(altitude_ASL), env.wind_velocity_y(altitude_ASL) + + # Calculate Mach number + free_stream_speed = ( + (wind_x - vx) ** 2 + (wind_y - vy) ** 2 + (vz) ** 2 + ) ** 0.5 + mach_number = free_stream_speed / env.speed_of_sound(altitude_ASL) + + # Get previous state from state_history + previous_state = state_history[-1] + previous_vz = previous_state[5] + + # If we wanted to we could get the returned values from observed_variables: + # returned_time, deployment_level, drag_coefficient = observed_variables[-1] + + # Check if the rocket has reached burnout + if time < Pro75M1670.burn_out_time: + return None + + # If below 1500 meters above ground level, air_brakes are not deployed + if altitude_AGL < 1500: + air_brakes.deployment_level = 0 + + # Else calculate the deployment level + else: + # Controller logic + new_deployment_level = ( + air_brakes.deployment_level + 0.1 * vz + 0.01 * previous_vz**2 + ) + + # Limiting the speed of the air_brakes to 0.2 per second + # Since this function is called every 1/sampling_rate seconds + # the max change in deployment level per call is 0.2/sampling_rate + max_change = 0.2 / sampling_rate + lower_bound = air_brakes.deployment_level - max_change + upper_bound = air_brakes.deployment_level + max_change + new_deployment_level = min(max(new_deployment_level, lower_bound), upper_bound) + + air_brakes.deployment_level = new_deployment_level + + # Return variables of interest to be saved in the observed_variables list + return ( + time, + air_brakes.deployment_level, + air_brakes.drag_coefficient(air_brakes.deployment_level, mach_number), + ) + +.. note:: + + - The code inside the ``controller_function`` can be as complex as needed. + Anything can be implemented inside the function, including filters, + apogee prediction, and any controller logic. + + - The ``air_brakes`` instance ``deployment_level`` is clamped between 0 and 1. + This means that the deployment level will never be set to a value lower than + 0 or higher than 1. If you want to disable this feature, set ``clamp`` to + ``False`` when defining the air brakes. + + - Anything can be returned by the ``controller_function``. The returned + values will be saved in the ``observed_variables`` list at every time step + and can then be accessed by the ``controller_function`` at the next time + step. The saved values can also be accessed after the simulation is + finished. This is useful for debugging and for plotting the results. + + - The ``controller_function`` can also be defined in a separate file and + imported into the simulation script. This includes importing a ``c`` or + ``cpp`` code into Python. + + +Defining the Drag Coefficient +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Now lets define the drag coefficient as a function of the air brakes' deployment +level and of the Mach number. We will import the data from a CSV file. + +The CSV file must have three columns: the first column must be the air brakes' +deployment level, the second column must be the Mach number, and the third column +must be the drag coefficient. + +Alternatively, the drag coefficient can be defined as a function of the air +brakes' deployment level and of the Mach number. This function must take in the +air brakes' deployment level and the Mach number as arguments, and must return the +drag coefficient. + +.. note:: + + At deployment level 0, the drag coefficient will always be set to 0, + regardless of the input curve. This means that the simulation considers that + at a deployment level of 0, the air brakes are completely retracted and do not + contribute to the drag of the rocket. + +Part of the data from the CSV can be seen in the code block below. + +.. code-block:: + + deployment_level, mach, cd + 0.0, 0.0, 0.0 + 0.1, 0.0, 0.0 + 0.1, 0.2, 0.0 + 0.1, 0.3, 0.01 + 0.1, 0.4, 0.005 + 0.1, 0.5, 0.006 + 0.1, 0.6, 0.018 + 0.1, 0.7, 0.012 + 0.1, 0.8, 0.014 + 0.5, 0.1, 0.051 + 0.5, 0.2, 0.051 + 0.5, 0.3, 0.065 + 0.5, 0.4, 0.061 + 0.5, 0.5, 0.067 + 0.5, 0.6, 0.083 + 0.5, 0.7, 0.08 + 0.5, 0.8, 0.085 + 1.0, 0.1, 0.32 + 1.0, 0.2, 0.225 + 1.0, 0.3, 0.225 + 1.0, 0.4, 0.21 + 1.0, 0.5, 0.19 + 1.0, 0.6, 0.22 + 1.0, 0.7, 0.21 + 1.0, 0.8, 0.218 + +.. note:: + The air brakes' drag coefficient curve can represent either the air brakes + alone or both the air brakes and the rocket. This is determined by the + ``override_rocket_drag`` argument. If set to True, the drag + coefficient curve will include both the air brakes and the rocket. If set to + False, the curve will exclusively represent the air brakes. + + When the curve represents only the air brakes, its drag coefficient will be + added to the rocket's existing drag coefficient. Conversely, if the curve + represents both the air brakes and the rocket, the drag coefficient will be + set to match that of the curve. This feature is particularly useful when you + have a drag coefficient curve for the entire rocket with the air brakes + deployed, such as data from a wind tunnel test, and you want to incorporate + it into the simulation. + +Adding the Air Brakes to the Rocket +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Now we can add the air brakes to the rocket. + +We will set the ``reference_area`` to ``None``. This means that the reference +area for the calculation of the drag force from the coefficient will be the +rocket's reference area (the area of the cross section of the rocket). If we +wanted to set a different reference area, we would set ``reference_area`` to +the desired value. + +Also, we will set ``clamp`` to ``True``. This means that the deployment level will +be clamped between 0 and 1. This means that the deployment level will never be set +to a value lower than 0 or higher than 1. This can alter the behavior of the +controller function. If you want to disable this feature, set ``clamp`` to +``False``. + +.. jupyter-execute:: + + air_brakes = calisto.add_air_brakes( + drag_coefficient_curve="../data/calisto/air_brakes_cd.csv", + controller_function=controller_function, + sampling_rate=10, + reference_area=None, + clamp=True, + initial_observed_variables=[0, 0, 0], + override_rocket_drag=False, + name="Air Brakes", + ) + + air_brakes.all_info() + +.. note:: + + The ``initial_observed_variables`` argument is optional. It is used as + the initial value for the ``observed_variables`` list passed on the + ``controller_function`` at the first time step. If not given, the + ``observed_variables`` list will be initialized as an empty list. + +.. seealso:: + + For more information on the :class:`rocketpy.AirBrakes` class + initialization, see :class:`rocketpy.AirBrakes.__init__` section. + +Simulating a Flight +------------------- + +.. important:: + + To simulate the air brakes successfully, we must set ``time_overshoot`` to + ``False``. This way the simulation will run at the time step defined by our + controller sampling rate. Be aware that this will make the simulation run + **much** slower. + +We will be terminating the simulation at apogee, by setting +``terminate_at_apogee`` to ``True``. This way the simulation will stop when the +rocket reaches apogee, and we will save some time. + +.. jupyter-execute:: + + test_flight = Flight( + rocket=calisto, + environment=env, + rail_length=5.2, + inclination=85, + heading=0, + time_overshoot=False, + terminate_on_apogee=True, + ) + +Analyzing the Results +--------------------- + +Now we can create some plots to analyze the results. We rely on the +``observed_variables`` list to get the data we want to plot. Since we returned +the ``time``, ``deployment_level`` and the ``drag_coefficient`` in the +``controller_function``, the ``observed_variables`` list will contain these +values at every time step. + +We can retrieve the ``observed_variables`` list by calling the +``get_controller_observed_variables`` method of the ``Flight`` instance. +Then we can plot the data we want. + +.. jupyter-execute:: + + import matplotlib.pyplot as plt + + time_list, deployment_level_list, drag_coefficient_list = [], [], [] + + for time, deployment_level, drag_coefficient in test_flight.get_controller_observed_variables: + time_list.append(time) + deployment_level_list.append(deployment_level) + drag_coefficient_list.append(drag_coefficient) + + # Plot deployment level by time + plt.plot(time_list, deployment_level_list) + plt.xlabel("Time (s)") + plt.ylabel("Deployment Level") + plt.title("Deployment Level by Time") + plt.grid() + plt.show() + + # Plot drag coefficient by time + plt.plot(time_list, drag_coefficient_list) + plt.xlabel("Time (s)") + plt.ylabel("Drag Coefficient") + plt.title("Drag Coefficient by Time") + plt.grid() + plt.show() + +.. seealso:: + + For more information on the :class:`rocketpy.AirBrakes` class attributes, + see :class:`rocketpy.AirBrakes` section. + +And of course, we should check some of the simulation results: + +.. jupyter-execute:: + + test_flight.prints.burn_out_conditions() + test_flight.prints.apogee_conditions() + test_flight.altitude() + test_flight.vz() \ No newline at end of file diff --git a/docs/user/first_simulation.rst b/docs/user/first_simulation.rst index 9cfa5ae43..6fab61238 100644 --- a/docs/user/first_simulation.rst +++ b/docs/user/first_simulation.rst @@ -1,3 +1,5 @@ +.. _firstsimulation: + First Simulation with RocketPy ============================== diff --git a/docs/user/index.rst b/docs/user/index.rst index cc7591631..4a609885a 100644 --- a/docs/user/index.rst +++ b/docs/user/index.rst @@ -23,6 +23,7 @@ RocketPy's User Guide ../notebooks/deployable_payload_example.ipynb ../notebooks/compare_flights_usage.ipynb + Air Brakes Example ../matlab/matlab.rst .. toctree:: diff --git a/rocketpy/__init__.py b/rocketpy/__init__.py index 4abb08e2f..10404b619 100644 --- a/rocketpy/__init__.py +++ b/rocketpy/__init__.py @@ -1,3 +1,4 @@ +from .control import _Controller from .environment import Environment, EnvironmentAnalysis from .mathutils import ( Function, @@ -22,8 +23,10 @@ TankGeometry, UllageBasedTank, ) +from .plots.compare import Compare, CompareFlights from .rocket import ( AeroSurface, + AirBrakes, Components, EllipticalFins, Fins, @@ -35,4 +38,3 @@ TrapezoidalFins, ) from .simulation import Flight -from .plots.compare import Compare, CompareFlights diff --git a/rocketpy/control/__init__.py b/rocketpy/control/__init__.py new file mode 100644 index 000000000..0fa89380b --- /dev/null +++ b/rocketpy/control/__init__.py @@ -0,0 +1 @@ +from .controller import _Controller diff --git a/rocketpy/control/controller.py b/rocketpy/control/controller.py new file mode 100644 index 000000000..81fc8b332 --- /dev/null +++ b/rocketpy/control/controller.py @@ -0,0 +1,132 @@ +from ..prints.controller_prints import _ControllerPrints + + +class _Controller: + """A class for storing and running controllers on a rocket. Controllers + have a controller function that is called at a specified sampling rate + during the simulation. The controller function can access and modify + the objects that are passed to it. The controller function also stores the + variables of interest in the objects that are passed to it.""" + + def __init__( + self, + interactive_objects, + controller_function, + sampling_rate, + initial_observed_variables=None, + name="Controller", + ): + """Initialize the class with the controller function and the objects to + be observed. + + Parameters + ---------- + interactive_objects : list or object + A collection of objects that the controller function can access and + potentially modify. This can be either a list of objects or a single + object. The objects listed here are provided to the controller function + as the last argument, maintaining the order specified in this list if + it's a list. The controller function gains the ability to interact with + and make adjustments to these objects during its execution. + controller_function : function, callable + An user-defined function responsible for controlling the simulation. + This function is expected to take the following arguments, in order: + + 1. `time` (float): The current simulation time in seconds. + 2. `sampling_rate` (float): The rate at which the controller + function is called, measured in Hertz (Hz). + 3. `state` (list): The state vector of the simulation, structured as + `[x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz]`. + 4. `state_history` (list): A record of the rocket's state at each + step throughout the simulation. The state_history is organized as + a list of lists, with each sublist containing a state vector. The + last item in the list always corresponds to the previous state + vector, providing a chronological sequence of the rocket's + evolving states. + 5. `observed_variables` (list): A list containing the variables that + the controller function returns. The return of each controller + function call is appended to the observed_variables list. The + initial value in the first step of the simulation of this list is + provided by the `initial_observed_variables` argument. + 6. `interactive_objects` (list): A list containing the objects that + the controller function can interact with. The objects are + listed in the same order as they are provided in the + `interactive_objects`. + + This function will be called during the simulation at the specified + sampling rate. The function should evaluate and change the interactive + objects as needed. The function return statement can be used to save + relevant information in the `observed_variables` list. + + .. note:: The function will be called according to the sampling rate + specified. + sampling_rate : float + The sampling rate of the controller function in Hertz (Hz). This + means that the controller function will be called every + `1/sampling_rate` seconds. + initial_observed_variables : list, optional + A list of the initial values of the variables that the controller + function returns. This list is used to initialize the + `observed_variables` argument of the controller function. The + default value is None, which initializes the list as an empty list. + name : str + The name of the controller. This will be used for printing and + plotting. + + Returns + ------- + None + """ + self.interactive_objects = interactive_objects + self.controller_function = controller_function + self.sampling_rate = sampling_rate + self.name = name + self.prints = _ControllerPrints(self) + + if initial_observed_variables is not None: + self.observed_variables = [initial_observed_variables] + else: + self.observed_variables = [] + + def __call__(self, time, state_vector, state_history): + """Call the controller function. This is used by the simulation class. + + Parameters + ---------- + time : float + The time of the simulation in seconds. + state_vector : list + The state vector of the simulation, which is defined as: + + `[x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz]`. + state_history : list + A list containing the state history of the simulation. The state + history is a list of every state vector of every step of the + simulation. The state history is a list of lists, where each + sublist is a state vector and is ordered from oldest to newest. + + Returns + ------- + None + """ + observed_variables = self.controller_function( + time, + self.sampling_rate, + state_vector, + state_history, + self.observed_variables, + self.interactive_objects, + ) + if observed_variables is not None: + self.observed_variables.append(observed_variables) + + def __str__(self): + return f"Controller '{self.name}' with sampling rate {self.sampling_rate} Hz." + + def info(self): + """Prints out summarized information about the controller.""" + self.prints.all() + + def all_info(self): + """Prints out all information about the controller.""" + self.info() diff --git a/rocketpy/plots/aero_surface_plots.py b/rocketpy/plots/aero_surface_plots.py index 0e9c12bab..57d48d78b 100644 --- a/rocketpy/plots/aero_surface_plots.py +++ b/rocketpy/plots/aero_surface_plots.py @@ -448,3 +448,40 @@ def __init__(self, tail): def draw(self): # This will de done in the future return None + + +class _AirBrakesPlots(_AeroSurfacePlots): + """Class that contains all air brakes plots.""" + + def __init__(self, air_brakes): + """Initialize the class + + Parameters + ---------- + air_brakes : rocketpy.AeroSurface.air_brakes + AirBrakes object to be plotted + + Returns + ------- + None + """ + super().__init__(air_brakes) + + def drag_coefficient_curve(self): + """Plots the drag coefficient curve of the air_brakes.""" + if self.aero_surface.clamp is True: + return self.aero_surface.drag_coefficient.plot(0, 1) + else: + return self.aero_surface.drag_coefficient.plot() + + def draw(self): + raise NotImplementedError + + def all(self): + """Plots all available air_brakes plots. + + Returns + ------- + None + """ + self.drag_coefficient_curve() diff --git a/rocketpy/prints/aero_surface_prints.py b/rocketpy/prints/aero_surface_prints.py index 8dd9b5934..9a971babe 100644 --- a/rocketpy/prints/aero_surface_prints.py +++ b/rocketpy/prints/aero_surface_prints.py @@ -291,3 +291,16 @@ def geometry(self): f"Angular position of the buttons: {self.aero_surface.angular_position:.3f} deg\n" ) return None + + +class _AirBrakesPrints(_AeroSurfacePrints): + """Class that contains all air_brakes prints. Not yet implemented.""" + + def __init__(self, air_brakes): + super().__init__(air_brakes) + + def geometry(self): + pass + + def all(self): + pass diff --git a/rocketpy/prints/controller_prints.py b/rocketpy/prints/controller_prints.py new file mode 100644 index 000000000..cb19ec00c --- /dev/null +++ b/rocketpy/prints/controller_prints.py @@ -0,0 +1,68 @@ +from inspect import getsourcelines + + +class _ControllerPrints: + """Class that holds prints methods for Controller class. + + Attributes + ---------- + _ControllerPrint.controller : controller + Controller object that will be used for the prints. + """ + + def __init__( + self, + controller, + ): + """Initializes _ControllerPrints class + + Parameters + ---------- + controller: Controller + Instance of the Controller class. + + Returns + ------- + None + """ + self.controller = controller + + def controller_function(self): + """Prints the controller function information. + + Returns + ------- + None + """ + if self.controller.controller_function.__name__ == "": + line = getsourcelines(self.controller.trigger)[0][0] + print("Controller function: " + line.split("=")[0].strip()) + else: + print( + "Controller function: " + self.controller.controller_function.__name__ + ) + print(f"Controller refresh rate: {self.controller.sampling_rate:.3f} Hz") + + def interactive_objects(self): + """Prints interactive objects.""" + print("interactive Objects") + # check if is list + if isinstance(self.controller.interactive_objects, list): + for obj in self.controller.interactive_objects: + print(getattr(obj, "name", str(obj))) + else: + obj = self.controller.interactive_objects + print(getattr(obj, "name", str(obj))) + + def all(self): + """Prints all information about the parachute. + + Returns + ------- + None + """ + + print("\nController Details\n") + print(self.controller) + self.controller_function() + self.interactive_objects() diff --git a/rocketpy/rocket/__init__.py b/rocketpy/rocket/__init__.py index 0fd8d27f0..fb6ea2b2c 100644 --- a/rocketpy/rocket/__init__.py +++ b/rocketpy/rocket/__init__.py @@ -1,5 +1,7 @@ +from rocketpy.control.controller import _Controller from rocketpy.rocket.aero_surface import ( AeroSurface, + AirBrakes, EllipticalFins, Fins, NoseCone, diff --git a/rocketpy/rocket/aero_surface.py b/rocketpy/rocket/aero_surface.py index a72fb74cc..1ab8c7597 100644 --- a/rocketpy/rocket/aero_surface.py +++ b/rocketpy/rocket/aero_surface.py @@ -1,17 +1,20 @@ -from abc import ABC, abstractmethod import warnings +from abc import ABC, abstractmethod +from functools import cached_property import numpy as np from scipy.optimize import fsolve from ..mathutils.function import Function from ..plots.aero_surface_plots import ( + _AirBrakesPlots, _EllipticalFinsPlots, _NoseConePlots, _TailPlots, _TrapezoidalFinsPlots, ) from ..prints.aero_surface_prints import ( + _AirBrakesPrints, _EllipticalFinsPrints, _NoseConePrints, _RailButtonsPrints, @@ -1885,3 +1888,195 @@ def all_info(self): """ self.prints.all() return None + + +class AirBrakes(AeroSurface): + """AirBrakes class. Inherits from AeroSurface. + + Attributes + ---------- + AirBrakes.drag_coefficient : Function + Drag coefficient as a function of deployment level and Mach number. + AirBrakes.drag_coefficient_curve : int, float, callable, array, string, Function + Curve that defines the drag coefficient as a function of deployment level + and Mach number. Used as the source of `AirBrakes.drag_coefficient`. + AirBrakes.deployment_level : float + Current deployment level, ranging from 0 to 1. Deployment level is the + fraction of the total airbrake area that is deployed. + AirBrakes.reference_area : int, float + Reference area used to calculate the drag force of the air brakes + from the drag coefficient curve. Units of m^2. + AirBrakes.clamp : bool, optional + If True, the simulation will clamp the deployment level to 0 or 1 if + the deployment level is out of bounds. If False, the simulation will + not clamp the deployment level and will instead raise a warning if + the deployment level is out of bounds. Default is True. + AirBrakes.name : str + Name of the air brakes. + """ + + def __init__( + self, + drag_coefficient_curve, + reference_area, + clamp=True, + override_rocket_drag=False, + deployment_level=0, + name="AirBrakes", + ): + """Initializes the AirBrakes class. + + Parameters + ---------- + drag_coefficient_curve : int, float, callable, array, string, Function + This parameter represents the drag coefficient associated with the + air brakes and/or the entire rocket, depending on the value of + ``override_rocket_drag``. + + - If a constant, it should be an integer or a float representing a + fixed drag coefficient value. + - If a function, it must take two parameters: deployment level and + Mach number, and return the drag coefficient. This function allows + for dynamic computation based on deployment and Mach number. + - If an array, it should be a 2D array with three columns: the first + column for deployment level, the second for Mach number, and the + third for the corresponding drag coefficient. + - If a string, it should be the path to a .csv or .txt file. The + file must contain three columns: the first for deployment level, + the second for Mach number, and the third for the drag + coefficient. + - If a Function, it must take two parameters: deployment level and + Mach number, and return the drag coefficient. + + .. note:: For ``override_rocket_drag = False``, at + deployment level 0, the drag coefficient is assumed to be 0, + independent of the input drag coefficient curve. This means that + the simulation always considers that at a deployment level of 0, + the air brakes are completely retracted and do not contribute to + the drag of the rocket. + + reference_area : int, float + Reference area used to calculate the drag force of the air brakes + from the drag coefficient curve. Units of m^2. + clamp : bool, optional + If True, the simulation will clamp the deployment level to 0 or 1 if + the deployment level is out of bounds. If False, the simulation will + not clamp the deployment level and will instead raise a warning if + the deployment level is out of bounds. Default is True. + override_rocket_drag : bool, optional + If False, the air brakes drag coefficient will be added to the + rocket's power off drag coefficient curve. If True, during the + simulation, the rocket's power off drag will be ignored and the air + brakes drag coefficient will be used for the entire rocket instead. + Default is False. + deployment_level : float, optional + Current deployment level, ranging from 0 to 1. Deployment level is the + fraction of the total airbrake area that is Deployment. Default is 0. + name : str, optional + Name of the air brakes. Default is "AirBrakes". + + Returns + ------- + None + """ + super().__init__(name) + self.drag_coefficient_curve = drag_coefficient_curve + self.drag_coefficient = Function( + drag_coefficient_curve, + inputs=["Deployment Level", "Mach"], + outputs="Drag Coefficient", + ) + self.reference_area = reference_area + self.clamp = clamp + self.override_rocket_drag = override_rocket_drag + self.deployment_level = deployment_level + self.prints = _AirBrakesPrints(self) + self.plots = _AirBrakesPlots(self) + + @property + def deployment_level(self): + """Returns the deployment level of the air brakes.""" + return self._deployment_level + + @deployment_level.setter + def deployment_level(self, value): + # Check if deployment level is within bounds and warn user if not + if value < 0 or value > 1: + # Clamp deployment level if clamp is True + if self.clamp: + # Make sure deployment level is between 0 and 1 + value = np.clip(value, 0, 1) + else: + # Raise warning if clamp is False + warnings.warn( + f"Deployment level of {self.name} is smaller than 0 or " + + "larger than 1. Extrapolation for the drag coefficient " + + "curve will be used." + ) + self._deployment_level = value + + def evaluate_center_of_pressure(self): + """Evaluates the center of pressure of the aerodynamic surface in local + coordinates. + + For air brakes, all components of the center of pressure position are + 0. + + Returns + ------- + None + """ + self.cpx = 0 + self.cpy = 0 + self.cpz = 0 + self.cp = (self.cpx, self.cpy, self.cpz) + + def evaluate_lift_coefficient(self): + """Evaluates the lift coefficient curve of the aerodynamic surface. + + For air brakes, the current model assumes no lift is generated. + Therefore, the lift coefficient (C_L) and its derivative relative to the + angle of attack (C_L_alpha), is 0. + + Returns + ------- + None + """ + self.clalpha = Function( + lambda mach: 0, + "Mach", + f"Lift coefficient derivative for {self.name}", + ) + self.cl = Function( + lambda alpha, mach: 0, + ["Alpha (rad)", "Mach"], + "Lift Coefficient", + ) + + def evaluate_geometrical_parameters(self): + """Evaluates the geometrical parameters of the aerodynamic surface. + + Returns + ------- + None + """ + pass + + def info(self): + """Prints and plots summarized information of the aerodynamic surface. + + Returns + ------- + None + """ + self.prints.geometry() + + def all_info(self): + """Prints and plots all information of the aerodynamic surface. + + Returns + ------- + None + """ + self.info() + self.plots.drag_coefficient_curve() diff --git a/rocketpy/rocket/rocket.py b/rocketpy/rocket/rocket.py index 2c076576a..30f5d389b 100644 --- a/rocketpy/rocket/rocket.py +++ b/rocketpy/rocket/rocket.py @@ -2,11 +2,13 @@ import numpy as np +from rocketpy.control.controller import _Controller from rocketpy.mathutils.function import Function from rocketpy.motors.motor import EmptyMotor from rocketpy.plots.rocket_plots import _RocketPlots from rocketpy.prints.rocket_prints import _RocketPrints from rocketpy.rocket.aero_surface import ( + AirBrakes, EllipticalFins, Fins, NoseCone, @@ -93,6 +95,12 @@ class Rocket: Rocket.aerodynamic_surfaces : list Collection of aerodynamic surfaces of the rocket. Holds Nose cones, Fin sets, and Tails. + Rocket.parachutes : list + Collection of parachutes of the rocket. + Rocket.air_brakes : list + Collection of air brakes of the rocket. + Rocket._controllers : list + Collection of controllers of the rocket. Rocket.cp_position : Function Function of Mach number expressing the rocket's center of pressure position relative to user defined rocket reference system. @@ -272,6 +280,14 @@ def __init__( # Parachute, Aerodynamic and Rail buttons data initialization self.parachutes = [] + + # Controllers data initialization + self._controllers = [] + + # AirBrakes data initialization + self.air_brakes = [] + + # Aerodynamic data initialization self.aerodynamic_surfaces = Components() self.rail_buttons = Components() @@ -795,6 +811,25 @@ def add_surfaces(self, surfaces, positions): self.evaluate_stability_margin() self.evaluate_static_margin() + def _add_controllers(self, controllers): + """Adds a controller to the rocket. + + Parameters + ---------- + controllers : list of Controller objects + List of controllers to be added to the rocket. If a single + Controller object is passed, outside of a list, a try/except block + will be used to try to append the controller to the list. + + Returns + ------- + None + """ + try: + self._controllers.extend(controllers) + except TypeError: + self._controllers.append(controllers) + def add_tail( self, top_radius, bottom_radius, length, position, radius=None, name="Tail" ): @@ -1124,6 +1159,146 @@ def add_parachute( self.parachutes.append(parachute) return self.parachutes[-1] + def add_air_brakes( + self, + drag_coefficient_curve, + controller_function, + sampling_rate, + clamp=True, + reference_area=None, + initial_observed_variables=None, + override_rocket_drag=False, + return_controller=False, + name="AirBrakes", + controller_name="AirBrakes Controller", + ): + """Creates a new air brakes system, storing its parameters such as + drag coefficient curve, controller function, sampling rate, and + reference area. + + Parameters + ---------- + drag_coefficient_curve : int, float, callable, array, string, Function + This parameter represents the drag coefficient associated with the + air brakes and/or the entire rocket, depending on the value of + ``override_rocket_drag``. + + - If a constant, it should be an integer or a float representing a + fixed drag coefficient value. + - If a function, it must take two parameters: deployment level and + Mach number, and return the drag coefficient. This function allows + for dynamic computation based on deployment and Mach number. + - If an array, it should be a 2D array with three columns: the first + column for deployment level, the second for Mach number, and the + third for the corresponding drag coefficient. + - If a string, it should be the path to a .csv or .txt file. The + file must contain three columns: the first for deployment level, + the second for Mach number, and the third for the drag + coefficient. + - If a Function, it must take two parameters: deployment level and + Mach number, and return the drag coefficient. + + .. note:: For ``override_rocket_drag = False``, at + deployment level 0, the drag coefficient is assumed to be 0, + independent of the input drag coefficient curve. This means that + the simulation always considers that at a deployment level of 0, + the air brakes are completely retracted and do not contribute to + the drag of the rocket. + + controller_function : function, callable + An user-defined function responsible for controlling the simulation. + This function is expected to take the following arguments, in order: + + 1. `time` (float): The current simulation time in seconds. + 2. `sampling_rate` (float): The rate at which the controller + function is called, measured in Hertz (Hz). + 3. `state` (list): The state vector of the simulation, structured as + `[x, y, z, vx, vy, vz, e0, e1, e2, e3, wx, wy, wz]`. + 4. `state_history` (list): A record of the rocket's state at each + step throughout the simulation. The state_history is organized as a + list of lists, with each sublist containing a state vector. The last + item in the list always corresponds to the previous state vector, + providing a chronological sequence of the rocket's evolving states. + 5. `observed_variables` (list): A list containing the variables that + the controller function returns. The initial value in the first + step of the simulation of this list is provided by the + `initial_observed_variables` argument. + 6. `interactive_objects` (list): A list containing the objects that + the controller function can interact with. The objects are + listed in the same order as they are provided in the + `interactive_objects` + + This function will be called during the simulation at the specified + sampling rate. The function should evaluate and change the observed + objects as needed. The function should return None. + + .. note:: The function will be called according to the sampling rate + specified. + sampling_rate : float + The sampling rate of the controller function in Hertz (Hz). This + means that the controller function will be called every + `1/sampling_rate` seconds. + clamp : bool, optional + If True, the simulation will clamp the deployment level to 0 or 1 if + the deployment level is out of bounds. If False, the simulation will + not clamp the deployment level and will instead raise a warning if + the deployment level is out of bounds. Default is True. + reference_area : float, optional + Reference area used to calculate the drag force of the air brakes + from the drag coefficient curve. If None, which is default, use + rocket section area. Must be given in squared meters. + initial_observed_variables : list, optional + A list of the initial values of the variables that the controller + function returns. This list is used to initialize the + `observed_variables` argument of the controller function. The + default value is None, which initializes the list as an empty list. + override_rocket_drag : bool, optional + If False, the air brakes drag coefficient will be added to the + rocket's power off drag coefficient curve. If True, during the + simulation, the rocket's power off drag will be ignored and the air + brakes drag coefficient will be used for the entire rocket instead. + Default is False. + return_controller : bool, optional + If True, the function will return the controller object created. + Default is False. + name : string, optional + AirBrakes name, such as drogue and main. Has no impact in + simulation, as it is only used to display data in a more + organized matter. + controller_name : string, optional + Controller name. Has no impact in simulation, as it is only used to + display data in a more organized matter. + + Returns + ------- + air_brakes : AirBrakes + AirBrakes object created. + controller : Controller + Controller object created. + """ + reference_area = reference_area if reference_area is not None else self.area + air_brakes = AirBrakes( + drag_coefficient_curve=drag_coefficient_curve, + reference_area=reference_area, + clamp=clamp, + override_rocket_drag=override_rocket_drag, + deployment_level=0, + name=name, + ) + _controller = _Controller( + interactive_objects=air_brakes, + controller_function=controller_function, + sampling_rate=sampling_rate, + initial_observed_variables=initial_observed_variables, + name=controller_name, + ) + self.air_brakes.append(air_brakes) + self._add_controllers(_controller) + if return_controller: + return air_brakes, _controller + else: + return air_brakes + def set_rail_buttons( self, upper_button_position, lower_button_position, angular_position=45 ): diff --git a/rocketpy/simulation/flight.py b/rocketpy/simulation/flight.py index d72370140..5a0db3c43 100644 --- a/rocketpy/simulation/flight.py +++ b/rocketpy/simulation/flight.py @@ -55,6 +55,8 @@ class Flight: the beginning of the rail. Flight.name: str Name of the flight. + Flight._controllers : list + List of controllers to be used during simulation. Flight.max_time : int, float Maximum simulation time allowed. Refers to physical time being simulated, not time taken to run simulation. @@ -587,6 +589,7 @@ def __init__( if self.rail_length <= 0: raise ValueError("Rail length must be a positive value.") self.parachutes = self.rocket.parachutes[:] + self._controllers = self.rocket._controllers[:] self.inclination = inclination self.heading = heading self.max_time = max_time @@ -661,6 +664,9 @@ def __init__( phase.TimeNodes.add_parachutes( self.parachutes, phase.t, phase.time_bound ) + phase.TimeNodes.add_controllers( + self._controllers, phase.t, phase.time_bound + ) # Add lst time node to permanent list phase.TimeNodes.add_node(phase.time_bound, [], []) # Sort time nodes @@ -692,6 +698,9 @@ def __init__( for callback in node.callbacks: callback(self) + for controller in node._controllers: + controller(self.t, self.y_sol, self.solution) + for parachute in node.parachutes: # Calculate and save pressure signal pressure = self.env.pressure.get_value_opt(self.y_sol[2]) @@ -1419,7 +1428,23 @@ def u_dot(self, t, u, post_processing=False): else: drag_coeff = self.rocket.power_off_drag.get_value_opt(free_stream_mach) rho = self.env.density.get_value_opt(z) - R3 = -0.5 * rho * (free_stream_speed**2) * self.rocket.area * (drag_coeff) + R3 = -0.5 * rho * (free_stream_speed**2) * self.rocket.area * drag_coeff + for air_brakes in self.rocket.air_brakes: + if air_brakes.deployment_level > 0: + air_brakes_cd = air_brakes.drag_coefficient( + air_brakes.deployment_level, free_stream_mach + ) + air_brakes_force = ( + -0.5 + * rho + * (free_stream_speed**2) + * air_brakes.reference_area + * air_brakes_cd + ) + if air_brakes.override_rocket_drag: + R3 = air_brakes_force # Substitutes rocket drag coefficient + else: + R3 += air_brakes_force # R3 += self.__computeDragForce(z, Vector(vx, vy, vz)) # Off center moment M1 += self.rocket.cp_eccentricity_y * R3 @@ -1702,8 +1727,23 @@ def u_dot_generalized(self, t, u, post_processing=False): drag_coeff = self.rocket.power_on_drag.get_value_opt(free_stream_mach) else: drag_coeff = self.rocket.power_off_drag.get_value_opt(free_stream_mach) - R3 += -0.5 * rho * (free_stream_speed**2) * self.rocket.area * (drag_coeff) - + R3 += -0.5 * rho * (free_stream_speed**2) * self.rocket.area * drag_coeff + for air_brakes in self.rocket.air_brakes: + if air_brakes.deployment_level > 0: + air_brakes_cd = air_brakes.drag_coefficient( + air_brakes.deployment_level, free_stream_mach + ) + air_brakes_force = ( + -0.5 + * rho + * (free_stream_speed**2) + * air_brakes.reference_area + * air_brakes_cd + ) + if air_brakes.override_rocket_drag: + R3 = air_brakes_force # Substitutes rocket drag coefficient + else: + R3 += air_brakes_force ## Off center moment M1 += self.rocket.cp_eccentricity_y * R3 M2 -= self.rocket.cp_eccentricity_x * R3 @@ -2862,6 +2902,20 @@ def retrieve_temporary_values_arrays(self): return temporary_values + def get_controller_observed_variables(self): + """Retrieve the observed variables related to air brakes from the + controllers. If there is only one set of observed variables, it is + returned as a list. If there are multiple sets, the list containing + all sets is returned.""" + observed_variables = [ + controller.observed_variables for controller in self._controllers + ] + return ( + observed_variables[0] + if len(observed_variables) == 1 + else observed_variables + ) + @cached_property def __calculate_rail_button_forces(self): """Calculate the forces applied to the rail buttons while rocket is @@ -3532,6 +3586,20 @@ def add_parachutes(self, parachutes, t_init, t_end): ] self.list += parachute_node_list + def add_controllers(self, controllers, t_init, t_end): + # Iterate over controllers + for controller in controllers: + # Calculate start of sampling time nodes + controller_time_step = 1 / controller.sampling_rate + controller_node_list = [ + self.TimeNode(i * controller_time_step, [], [controller]) + for i in range( + math.ceil(t_init / controller_time_step), + math.floor(t_end / controller_time_step) + 1, + ) + ] + self.list += controller_node_list + def sort(self): self.list.sort(key=(lambda node: node.t)) @@ -3555,10 +3623,11 @@ def flush_after(self, index): del self.list[index + 1 :] class TimeNode: - def __init__(self, t, parachutes, callbacks): + def __init__(self, t, parachutes, controllers): self.t = t self.parachutes = parachutes - self.callbacks = callbacks + self.callbacks = [] + self._controllers = controllers def __repr__(self): return ( diff --git a/tests/conftest.py b/tests/conftest.py index d11652540..9afcbbdd9 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -325,6 +325,66 @@ def calisto_robust( return calisto +@pytest.fixture +def calisto_air_brakes_clamp_on(calisto_robust, controller_function): + """Create an object class of the Rocket class to be used in the tests. This + is the same Calisto rocket that was defined in the calisto_robust fixture, + but with air brakes added, with clamping. + + Parameters + ---------- + calisto_robust : rocketpy.Rocket + An object of the Rocket class. This is a pytest fixture. + controller_function : function + A function that controls the air brakes. This is a pytest fixture. + + Returns + ------- + rocketpy.Rocket + An object of the Rocket class + """ + calisto = calisto_robust + # remove parachutes + calisto.parachutes = [] + calisto.add_air_brakes( + drag_coefficient_curve="data/calisto/air_brakes_cd.csv", + controller_function=controller_function, + sampling_rate=10, + clamp=True, + ) + return calisto + + +@pytest.fixture +def calisto_air_brakes_clamp_off(calisto_robust, controller_function): + """Create an object class of the Rocket class to be used in the tests. This + is the same Calisto rocket that was defined in the calisto_robust fixture, + but with air brakes added, without clamping. + + Parameters + ---------- + calisto_robust : rocketpy.Rocket + An object of the Rocket class. This is a pytest fixture. + controller_function : function + A function that controls the air brakes. This is a pytest fixture. + + Returns + ------- + rocketpy.Rocket + An object of the Rocket class + """ + calisto = calisto_robust + # remove parachutes + calisto.parachutes = [] + calisto.add_air_brakes( + drag_coefficient_curve="data/calisto/air_brakes_cd.csv", + controller_function=controller_function, + sampling_rate=10, + clamp=False, + ) + return calisto + + @pytest.fixture def pressurant_fluid(): """An example of a pressurant fluid as N2 gas at @@ -904,6 +964,37 @@ def flight_calisto_custom_wind(calisto_robust, example_env_robust): ) +@pytest.fixture +def flight_calisto_air_brakes(calisto_air_brakes_clamp_on, example_env): + """A rocketpy.Flight object of the Calisto rocket. This uses the calisto + with the aerodynamic surfaces and air brakes. The environment is the + simplest possible, with no parameters set. The air brakes are set to clamp + the deployment level. + + Parameters + ---------- + calisto_air_brakes_clamp_on : rocketpy.Rocket + An object of the Rocket class. + example_env : rocketpy.Environment + An object of the Environment class. + + Returns + ------- + rocketpy.Flight + A rocketpy.Flight object of the Calisto rocket in a more complex + condition. + """ + return Flight( + rocket=calisto_air_brakes_clamp_on, + environment=example_env, + rail_length=5.2, + inclination=85, + heading=0, + time_overshoot=False, + terminate_on_apogee=True, + ) + + ## Dimensionless motors and rockets @@ -1168,6 +1259,47 @@ def func_2d_from_csv(): return func +## Controller +@pytest.fixture +def controller_function(): + """Create a controller function that updates the air brakes deployment level + based on the altitude and vertical velocity of the rocket. This is the same + controller function that is used in the air brakes example in the + documentation. + + Returns + ------- + function + A controller function + """ + + def controller_function( + time, sampling_rate, state, state_history, observed_variables, air_brakes + ): + z = state[2] + vz = state[5] + previous_vz = state_history[-1][5] + if time < 3.9: + return None + if z < 1500: + air_brakes.deployment_level = 0 + else: + new_deployment_level = ( + air_brakes.deployment_level + 0.1 * vz + 0.01 * previous_vz**2 + ) + if new_deployment_level > air_brakes.deployment_level + 0.2 / sampling_rate: + new_deployment_level = air_brakes.deployment_level + 0.2 / sampling_rate + elif ( + new_deployment_level < air_brakes.deployment_level - 0.2 / sampling_rate + ): + new_deployment_level = air_brakes.deployment_level - 0.2 / sampling_rate + else: + new_deployment_level = air_brakes.deployment_level + air_brakes.deployment_level = new_deployment_level + + return controller_function + + @pytest.fixture def lambda_quad_func(): """Create a lambda function based on a string. diff --git a/tests/test_flight.py b/tests/test_flight.py index 3fa49f1f9..a2e42281c 100644 --- a/tests/test_flight.py +++ b/tests/test_flight.py @@ -295,6 +295,26 @@ def test_rolling_flight( assert test_flight.all_info() == None +@patch("matplotlib.pyplot.show") +def test_air_brakes_flight(mock_show, flight_calisto_air_brakes): + """Test the flight of a rocket with air brakes. This test only validates + that a flight simulation can be performed with air brakes; it does not + validate the results. + + Parameters + ---------- + mock_show : unittest.mock.MagicMock + Mock object to replace matplotlib.pyplot.show + flight_calisto_air_brakes_clamp_on : rocketpy.Flight + Flight object to be tested. See the conftest.py file for more info + regarding this pytest fixture. + """ + test_flight = flight_calisto_air_brakes + air_brakes = test_flight.rocket.air_brakes[0] + assert air_brakes.plots.all() is None + assert air_brakes.prints.all() is None + + @patch("matplotlib.pyplot.show") def test_simpler_parachute_triggers(mock_show, example_env, calisto_robust): """Tests different types of parachute triggers. This is important to ensure diff --git a/tests/test_rocket.py b/tests/test_rocket.py index 3bd46da96..21616a5fc 100644 --- a/tests/test_rocket.py +++ b/tests/test_rocket.py @@ -136,3 +136,72 @@ def test_airfoil( static_margin = test_rocket.static_margin(0) assert test_rocket.all_info() == None or not abs(static_margin - 2.03) < 0.01 + + +@patch("matplotlib.pyplot.show") +def test_air_brakes_clamp_on(mock_show, calisto_air_brakes_clamp_on): + """Test the air brakes class with clamp on configuration. This test checks + the basic attributes and the deployment_level setter. It also checks the + all_info method. + + Parameters + ---------- + mock_show : mock + Mock of the matplotlib.pyplot.show method. + calisto_air_brakes_clamp_on : Rocket instance + A predefined instance of the calisto with air brakes in clamp on + configuration. + """ + air_brakes_clamp_on = calisto_air_brakes_clamp_on.air_brakes[0] + + # test basic attributes + assert air_brakes_clamp_on.drag_coefficient.__dom_dim__ == 2 + assert ( + air_brakes_clamp_on.reference_area + == calisto_air_brakes_clamp_on.radius**2 * np.pi + ) + air_brakes_clamp_on.deployment_level = 0.5 + assert air_brakes_clamp_on.deployment_level == 0.5 + air_brakes_clamp_on.deployment_level = 1.5 + assert air_brakes_clamp_on.deployment_level == 1 + air_brakes_clamp_on.deployment_level = -1 + assert air_brakes_clamp_on.deployment_level == 0 + air_brakes_clamp_on.deployment_level = 0 + assert air_brakes_clamp_on.deployment_level == 0 + + assert air_brakes_clamp_on.all_info() == None + + +@patch("matplotlib.pyplot.show") +def test_air_brakes_clamp_off(mock_show, calisto_air_brakes_clamp_off): + """Test the air brakes class with clamp off configuration. This test checks + the basic attributes and the deployment_level setter. It also checks the + all_info method. + + Parameters + ---------- + mock_show : mock + Mock of the matplotlib.pyplot.show method. + calisto_air_brakes_clamp_off : Rocket instance + A predefined instance of the calisto with air brakes in clamp off + configuration. + """ + air_brakes_clamp_off = calisto_air_brakes_clamp_off.air_brakes[0] + + # test basic attributes + assert air_brakes_clamp_off.drag_coefficient.__dom_dim__ == 2 + assert ( + air_brakes_clamp_off.reference_area + == calisto_air_brakes_clamp_off.radius**2 * np.pi + ) + + air_brakes_clamp_off.deployment_level = 0.5 + assert air_brakes_clamp_off.deployment_level == 0.5 + air_brakes_clamp_off.deployment_level = 1.5 + assert air_brakes_clamp_off.deployment_level == 1.5 + air_brakes_clamp_off.deployment_level = -1 + assert air_brakes_clamp_off.deployment_level == -1 + air_brakes_clamp_off.deployment_level = 0 + assert air_brakes_clamp_off.deployment_level == 0 + + assert air_brakes_clamp_off.all_info() == None